Method and apparatus for prefetching content in a data stream

Information

  • Patent Grant
  • 10101801
  • Patent Number
    10,101,801
  • Date Filed
    Wednesday, November 13, 2013
    11 years ago
  • Date Issued
    Tuesday, October 16, 2018
    6 years ago
Abstract
A data-processing system facilitates processing a data stream to assist other devices to pre-fetch elements of the data stream, out-of-sequence, for uninterrupted playback. During operation, the system can receive a data file, and segments the data file into a sequence of content objects. The system then determines a target content object that is to be processed out-of-sequence, and a corresponding source content object. The system then inserts a reference to the target content object, into the source content object, and stores the sequence of content objects. A client device can disseminate interest to obtain the data stream's content objects. Upon receiving a content object, the client device can determine whether the content object includes a reference to other content objects. If so, the client device can disseminate interests for these referenced content objects.
Description
RELATED APPLICATION

The subject matter of this application is related to the subject matter of the following application:

    • U.S. patent application Ser. No. 13/720,736, entitled “DYNAMIC ROUTING PROTOCOLS USING DATABASE SYNCHRONIZATION,” by inventors Van L. Jacobson and Marc E. Mosko, filed 19 Dec. 2012;


      the disclosures of which are incorporated by reference in their entirety herein.


BACKGROUND

Field


This disclosure is generally related to a system for transferring a data stream to a client device. More specifically, this disclosure is related to a method for segmenting a data stream into a sequence of content objects, and using a reference in a content object to obtain one or more other out-of-sequence content objects from the data stream.


Related Art


Widespread use of the Internet has made it easier for people to consume digital content without traveling to a store to purchase physical copies. A user's client device can obtain the digital content, such as streaming media and executable files, from a dedicated server. For example, media playing programs can present a media stream to the user while the media stream is being downloaded, when the media stream is encoded into a predetermined sequence of frames that are to be processed in-order.


Some media formats require a media player to seek or skip to other portions of the media stream to read the necessary portions before resuming playback. However, web browsers and download managers typically download data files in-sequence. Hence, presenting the media stream during download can require the media player to pause playback of the content until the necessary portions are downloaded, which leads to an interrupted playback experience. Similarly, when operating systems download a binary executable file to execute for the user, the entire file needs to be downloaded before the file can be executed. However, downloading complete software applications can cause the user to wait for an undesirably long period of time, especially when the executable files are significantly large.


SUMMARY

One embodiment provides a data-processing system that facilitates processing a data stream out-of-sequence for uninterrupted playback. During operation, the system can receive a data file, and segments the data file into a sequence of content objects. The system then determines a target content object that is to be processed out-of-sequence and a source content object for the target content object. Source content objects are content objects that are to be processed preceding the target content objects. The system then inserts a reference indicating the target content object into the source content object, and stores the sequence of content objects.


In some embodiments, the data file includes a plurality of data items, wherein a content object's boundaries can coincide with a data item's beginning boundary, ending boundary, or an offset between the beginning and ending boundaries.


In some embodiments, the reference comprises one or more of an identifier for a target object, and a data offset within the target content object. The target object identifier indicates which content object will be processed next, and the data offset indicates an offset within the target content object.


In some embodiments, the content object contains a name containing a hierarchically structured variable-length identifier (HSVLI).


In some embodiments, the data file includes a media stream.


In some variations to these embodiments, the system encodes the media stream into a target format, and generates a data file that includes the media stream in the target format.


In some embodiments, the file type can include a media stream, a text stream, a command sequence, an executable file, a compressed file, an image file, an encrypted file, and/or any data format now known or later developed.


In some embodiments, the system determines that the content object is stored in a local repository, and sends the content object to an interface associated with the interest.


In some embodiments, the system publishes a sequence of content objects by disseminating an advertisement for the content object over a content-centric network.


One embodiment provides a client computer that can disseminate an interest for digital content. Upon receiving a content object corresponding to the digital content, the client computer determines that the received content object includes a reference to a data item from a target content object. The client computer then disseminates an interest for the target content object to obtain the data item.


In some embodiments, the system generates an interest for a successive content object in the sequence, and disseminates the interest to obtain the successive content object. In doing so, the system processes data in-sequence when there are no references to target content objects.





BRIEF DESCRIPTION OF THE FIGURES


FIG. 1 illustrates an exemplary computer system that facilitates processing data files from various local and remote computing devices in accordance with an embodiment.



FIG. 2A illustrates a media stream which has been segmented into a plurality of content objects in accordance with an embodiment.



FIG. 2B illustrates information provided by a content object in accordance with an embodiment.



FIG. 2C illustrates information provided by reference data in accordance with an embodiment.



FIG. 3 presents a flow chart illustrating a method for segmenting a data file and inserting a reference into a content object in accordance with an embodiment.



FIG. 4 presents a flow chart illustrating a method for determining a target object for which to generate a reference in accordance with an embodiment.



FIG. 5 presents a flow chart illustrating a method for encoding a media stream to a target format in accordance with an embodiment.



FIG. 6 presents a flow chart illustrating a method for generating interests and obtaining content objects in accordance with an embodiment.



FIG. 7 illustrates an exemplary apparatus that facilitates receiving and processing a data stream over a content-centric network in accordance with an embodiment.



FIG. 8 illustrates an exemplary computer system that facilitates receiving and processing a data stream over a content-centric network in accordance with an embodiment.





In the figures, like reference numerals refer to the same figure elements.


DETAILED DESCRIPTION

The following description is presented to enable any person skilled in the art to make and use the embodiments, and is provided in the context of a particular application and its requirements. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Thus, the present invention is not limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.


Overview

Embodiments of the present invention provide a content-streaming system that solves the problem of interrupted streaming of content to a user when the streaming content includes data that is to be processed out-of-sequence. During operation, the system inserts references while segmenting the data into content objects. For example, a server can segment a media stream or file into a sequence of content objects, and can serve these content objects to satisfy interests for the file or for a specific content object. While segmenting the data file, the system can determine which target content objects are to be processed out-of-sequence, and determines source content objects that are to be processed preceding these target content objects. The system then inserts references into these source content objects to indicate the target content object, and an offset within these target content object.


In the disclosure, the term “successive” content object refers to a content object that is to be processed following a source content object in a data stream's predetermined sequence of content objects.


In some embodiments, the data file can include a plurality of data items, and the content object boundaries may not always be aligned with a data item's beginning or ending boundaries. For example, the system may generate the content objects to have a predetermined fixed length, or may generate the content objects to have a variable length for including one or more data items. In any case, the system generates the reference to indicate a content object, and to indicate an offset form which the target data item begins within the content object. A client device can decode a reference from a content object to obtain a recommendation for other content objects to cache or process next.


Streaming Data Out-of-Sequence


Typical data streaming techniques often produce adequate streaming results when the stream's data is to be processed in-sequence, but fail to produce an acceptable user experience if the stream's data items are to be processed out-of-sequence. Specifically, a client device may disseminate an interest for a data stream hosted by a remote content server, and the content server may stream the data stream in-sequence. However, if the client device needs to perform out-of-sequence processing of the stream's data items, the client device may need to interrupt the processing of the data stream until the client device receives a desired data item. For example, the client device may need to process a non-streaming video file whose index is located at the end of the file. In such a case, a typical client device would need to download the complete file in order to use the index to determine a media format for each audio or video data item, and/or to determine which data item to play next.



FIG. 1 illustrates an exemplary computer system 100 that facilitates processing data files from various local and remote computing devices in accordance with an embodiment. Computer system 100 can include a client device 104, which can include a computer, a tablet, a smartphone, or any other device with computational capability and a network-interfacing mechanism for communicating data over network 102. A client device 104 can obtain data by generating and disseminating an interest for the data. The interest may be satisfied locally by an application within the client device, or by a remote device accessible via a network 102.


For example, client device 104 can include or be coupled to a storage device 124, which may store content objects 126, content-requesting software 128, a media player 130, and an operating system 132. Media player 130 and/or operating system 132 can use content-requesting software 128 to disseminate an interest for data (e.g., a media stream). If the data's content objects are stored locally, client device can satisfy the interest using content objects 126. Otherwise, client device 104 disseminates the interest over network 102, which allows a remote network device 110 or a content server 108 to satisfy the interest.


Content server 108 can include or be coupled to a storage device 112, which may store data items 114, and a media streams 116. Further, content server 108 can process data items 114 and media streams 116 to generate content objects 118, and can store content objects 118 in storage device 112. Data items 114 can include any type of data including a media stream, a text document, an encrypted message, and executable files.


Network 102 can generally include any type of wired or wireless communication channel capable of coupling together various computing nodes. This includes, but is not limited to, a local area network, a wide area network, a wireless cellular network, or a combination of networks. In one embodiment of the present invention, network 102 implements a content-centric network.



FIG. 2A illustrates a data stream 200 which has been segmented into a plurality of content objects 212 in accordance with an embodiment. Data stream 200 can comprise a plurality of data items 202 that includes video data items, audio data items, and metadata for data stream 200. In some embodiments, some content objects can include a reference that indicates a recommendation for data from one or more other content objects. For example, content objects 212.1-212.14 may include a reference to metadata 202.5, which indicates how a media player is to process the video and audio data items 202.1-202.4. Hence, the first content object for each video or audio item 202.1-202.4 may include a reference to the start of metadata 202.5 at content object 212.14. Metadata 202.5 can include each of video and audio segments 202.1-202.4, a media-data description that includes formatting information and a playback configuration for the corresponding media data. Each of these media-data descriptions in metadata 202.5 may also include a reference to the corresponding video or audio segment that it describes (e.g., reference 214.5 for video data 202.3, starting at an offset 216 of content object 212.7). While processing the content objects for each audio or video data item (e.g., while processing content object 212.1), the client device can generate interest for both the referenced metadata 202.5 (content object 212.14) as well as for a successive content object (e.g., content object 212.2 following content object 212.1).


In some embodiments, a content object may not include reference data, such as content objects 212.2 and 212.3. While processing these content objects, the client device can generate an interest for the successive content object in the sequence. For example, when the client device determines that content object 212.3 does not include a reference, the client device generates an interest for the successive content object 212.4 to be processed following content object 212.3.


Data stream 200 can also include information other than media streams. For example, data stream 200 can include blocks of executable code that form an application that can be executed before the complete application is downloaded. Each data item 202 can correspond to one or more basic blocks of code, and each reference 214 can correspond to a jump or branch operation to a target block of code and/or for other application resources. Specifically, the client device may execute the code before receiving the full application. As in a media stream, the client device may receive the code in the form of content objects. While executing code from one content object, the client device can disseminate interest for other content objects that are referenced by the current content object, which allows the client device to download urgent application resources before non-urgent application resources.


Data stream 200 may also be simple file formats, such as compressed image files (e.g., a graphical interchange format (GIF) file) or other compressed data. Data stream 200 can include a sequence of protocol blocks and sub-blocks representing graphics elements of the GIF file. Each data item 202 can correspond to one or more blocks of data containing protocol blocks or sub-blocks, and each reference 214 can correspond to a shift to an unrelated graphic element. Using the references, the client device may decode and display a GIF image without any unnecessary shifts to unrelated graphics elements. In doing so, the client device can minimize the number of hardware parameter resets and the delays that correspond to parameter resets when loading a GIF image.



FIG. 2B illustrates information provided by a content object 250 in accordance with an embodiment. Content object 250 can include a location-independent structured name 252, such as a hierarchically structured variable-length identifier (HSVLI). Additionally, content object 250 can include metadata 254, payload 256, and a signature 258. Metadata 254 can include general information necessary for clients and servers to send or receive the appropriate content objects. Payload 256 can include the data items located in a content object. Content object 250 may also include a reference 260, which references data from a target content object. In some embodiments, only some content objects in a data stream include reference 260 for data that is to be processed out-of-sequence.



FIG. 2C illustrates information provided by reference data 270 in accordance with an embodiment. Specifically, reference data 270 includes a content object identifier 272 and a data offset 274, which together recommend a data item to process or cache for the user. Content object identifier 272 indicates another content object that needs to be processed or cached next, and data offset 274 indicates the start of the recommended data item from the content object. In some variations, an instance of reference data 270 does not include an explicit data offset 274, which implies that the start of the referenced data item is aligned with the start of the content object.



FIG. 3 presents a flow chart illustrating a method for segmenting a data file and inserting a reference into a content object in accordance with an embodiment. During operation, the system segments a data file into a sequence of content objects (operation 302). These content objects function as data packets that facilitate transferring the data file to a remote device, and are stored in a CCN repository to satisfy interests for the data file or for a specific content object.


After segmenting the file into content objects, the system analyzes the content objects to determine one or more target content objects that are to be processed out-of-sequence by a client device (operation 304). The system then determines, for each target content object, the source object after which the target content object is to be processed (operation 306). The system inserts a reference into the source content object, which indicates a recommendation for a data item in the target content object (operation 308). A client device can use the embedded recommendation to process or cache the target content object following the source content object. In some embodiments, the reference includes information indicating a location-independent identifier for the target content object (e.g., an HSVLI name), and the data offset within the target content object. The system then determines whether there are more content objects to be processed out-of-sequence (operation 310). If target content objects remain, the system returns to operation 304. Otherwise, the system proceeds to publish the content objects that together make up the data file (operation 312). The system can publish a content object by disseminating an advertisement for the content object over a content-centric network.



FIG. 4 presents a flow chart illustrating a method for determining a target content object for which to generate a reference in accordance with an embodiment. The system begins by selecting a file-data offset of the data file, which is to be processed out-of-sequence (operation 402). For example, the data file may be an executable file or a media stream that includes data items that are to be processed out-of-sequence, and determines an offset, from the start of the data file, for each of these data items. The system then determines which content object corresponds to the file-data offset (operation 404), and determines a content-object offset, from the start of the content object, that corresponds to the target data item (operation 406). The target content object and the content object's offset together make up the reference to the data item mapped to by the file-data offset.



FIG. 5 presents a flow chart illustrating a method for encoding a media stream to a target format in accordance with an embodiment. During operation, the system selects a data file to publish (operation 502). Data files include, but are not limited to, a data item, a CCN content object, a media stream, an executable program, etc. In one embodiment, the system determines whether the data file includes a media stream (operation 504), and if so, encodes the contents of the media stream to a target format (operation 506). The system then generates a data file to include the media stream in the target format (operation 508). Subsequently, the system generates the sequence of content objects using the target-formatted data file (operation 512). Note that each content object may have a starting or ending boundary that is aligned with a data item's starting boundary, ending boundary, or an offset between the data item's starting and ending boundaries.


Otherwise, if the data file does not include a media stream, the data file is in the target format, and the server proceeds to generate the sequence of content objects for the data file (operation 510).


In some embodiments, the system can also encode other data streams into a different target format that facilitates processing data out-of-sequence, before downloading the complete file. For example, the data stream can include a presentation (e.g., a PowerPoint document), executable code, etc. Then, during operation 506, the system can encode the data stream into a target format that facilitates accessing individual data items of the data stream as needed, such as into a sequence of images, a sequence of instruction-code blocks, etc.



FIG. 6 presents a flow chart illustrating a method for generating interests and obtaining content objects in accordance with an embodiment. Recall that some content objects from a data stream may include references to a data item of a target content object. During operation, a client generates and disseminates an interest for a piece of content across a content-centric network (operation 602). After disseminating the interest, the client receives the content object corresponding to the interest (operation 604), and determines whether the received content object includes a reference to a data item from a target content object (operation 606).


If the content object is found to include a reference to a target content object, the client disseminates an interest corresponding to the reference to obtain the target content object (operation 608). In some embodiments disseminating the interest causes routers of a content-centric network to propagate the interest to a content server that stores the content object. However, if the content object does not include a reference, the system can proceed to operation 610.


The client device then determines whether more content objects exist for the data stream (operation 610). If the client determines that there are no more content objects to obtain for the data stream, the client device has received all the content objects that make up the data stream and ends the process. Otherwise, the client device generates an interest for a successive content object (operation 612), and disseminates the interest corresponding to the successive content object (operation 614).


In some embodiments, after disseminating an interest (e.g., at operation 608 or operation 614), the system returns to operation 604 to receive more content objects for the data stream.



FIG. 7 illustrates an exemplary apparatus 700 that facilitates receiving and processing a data stream over a content-centric network in accordance with an embodiment. Apparatus 700 can comprise a plurality of modules which may communicate with one another via a wired or wireless communication channel. Apparatus 700 may be realized using one or more integrated circuits, and may include fewer or more modules than those shown in FIG. 7. Further, apparatus 700 may be integrated in a computer system, or realized as a separate device which is capable of communicating with other computer systems and/or devices. Specifically, apparatus 700 can comprise an interest-disseminating module 702, a content object-receiving module 704, a reference-determining module 706, an interest-generating module 708.


During operation, once a client device generates an interest, interest-disseminating module 702 disseminates this interest over a content-centric network. After the interest is disseminated, if content objects are returned, content object-receiving module 704 receives these content objects. Reference-determining module 706 is then able to determine whether these content objects contain references to target content objects. If these content objects contain references, interest-disseminating module 702 disseminates an interest which corresponds to the reference. Otherwise, or additionally, interest-generating module 708 generates an interest which corresponds to a successive content object. Once again, interest-disseminating module 702 then disseminates an interest for the successive content object.



FIG. 8 illustrates an exemplary computer system 802 that facilitates receiving and processing a data stream over a content-centric network in accordance with the presence or lack of a reference. Computer system 802 includes a processor 804, a memory 806, and a storage device 808. Memory 806 can include a volatile memory (e.g., RAM) that serves as a managed memory, and can be used to store one or more memory pools. Furthermore, computer system 802 can be coupled to a display device 810, a keyboard 812, and a pointing device 814. Storage device 808 can store operating system 816, data processing system 818, and data 828.


Data processing system 818 can include instructions which, when executed by computer system 802, can cause computer system 802 to perform methods and/or processes described in this disclosure. Specifically, data processing system 818 may include instructions for disseminating an interest for content over a content-centric network (interest-disseminating module 820), and can include instructions for receiving a content object that satisfies the interest (content object-receiving module 822).


Data processing system 818 can also include instructions to determine whether a content object includes a reference that recommends data from a target content object (reference-determining module 824). Data processing system 818 can also include instructions for generating an interest for a recommended content object and/or for a successive content object (interest-generating module 826). Further, interest-disseminating module 820 can disseminate the interest that has been generated for the recommended content object or the successive content object.


Data 828 can include any data that is required as input or that is generated as output by the methods and/or processes described in this disclosure.


The data structures and code described in this detailed description are typically stored on a computer-readable storage medium, which may be any device or medium that can store code and/or data for use by a computer system. The computer-readable storage medium includes, but is not limited to, volatile memory, non-volatile memory, magnetic and optical storage devices such as disk drives, magnetic tape, CDs (compact discs), DVDs (digital versatile discs or digital video discs), or other media capable of storing computer-readable media now known or later developed.


The methods and processes described in the detailed description section can be embodied as code and/or data, which can be stored in a computer-readable storage medium as described above. When a computer system reads and executes the code and/or data stored on the computer-readable storage medium, the computer system performs the methods and processes embodied as data structures and code and stored within the computer-readable storage medium.


Furthermore, the methods and processes described above can be included in hardware modules. For example, the hardware modules can include, but are not limited to, application-specific integrated circuit (ASIC) chips, field-programmable gate arrays (FPGAs), and other programmable-logic devices now known or later developed. When the hardware modules are activated, the hardware modules perform the methods and processes included within the hardware modules.


The foregoing descriptions of embodiments of the present invention have been presented for purposes of illustration and description only. They are not intended to be exhaustive or to limit the present invention to the forms disclosed. Accordingly, many modifications and variations will be apparent to practitioners skilled in the art. Additionally, the above disclosure is not intended to limit the present invention. The scope of the present invention is defined by the appended claims.

Claims
  • 1. A computer-implemented method comprising: segmenting, by a computer, digital content into a sequence of content objects;determining a target content object of the sequence of content objects, wherein the target content object is to be processed out-of-sequence;determining a source content object of the sequence of content objects, wherein the target content object is to be processed after the source content object;inserting a reference into the source content object, wherein the reference indicates that the target content object is to be processed following the source content object, wherein the reference is distinct from a name for the source content object; andstoring the sequence of content objects, wherein the sequence includes the reference inserted into the source content object.
  • 2. The method of claim 1, wherein the digital content includes a plurality of data items, and wherein a content object's starting boundary or ending boundary corresponds to one or more of: a starting boundary of a data item;an ending boundary of a data item; andan offset between a data item's starting boundary and ending boundary.
  • 3. The method of claim 1, wherein the reference comprises one or more of: an identifier for the target content object; anda data offset within the target content object.
  • 4. The method of claim 3, wherein the identifier includes a hierarchically structured variable-length identifier.
  • 5. The method of claim 1, wherein the digital content includes one or more of: an audio stream;a video stream;executable instructions;a document;a graphical interchange format file;encrypted code; anda text stream.
  • 6. The method of claim 1, further comprising: encoding the contents of a source media stream to a target media-stream format; andgenerating the digital content to include the source media stream in the target media-stream format.
  • 7. The method of claim 1, wherein determining the target object involves: determining a file-data offset of the data file, which is to be processed out-of-sequence; anddetermining, from the sequence of content objects, the content object that corresponds to the file-data offset.
  • 8. The method of claim 1, further comprising: receiving an interest for a content object; andin response to determining that the content object is stored in a local repository, sending the content object through an interface associated with the interest.
  • 9. The method of claim 1, further comprising publishing the sequence of content objects, wherein publishing a respective content object involves: disseminating an advertisement for the content object over a content-centric network.
  • 10. A computer-implemented method comprising: disseminating, by a client computing device, an interest for digital content, wherein a name for the interest is a hierarchically structured variable length identifier comprised of contiguous name components ordered from a most general level to a most specific level;receiving a content object, which corresponds to the digital content and satisfies the interest;determining that the received content object includes a reference to a data item from a target content object, wherein the reference is distinct from a name for the received content object; anddisseminating an interest for the target content object to obtain the data item.
  • 11. The method of claim 10, wherein the method further comprises: generating an interest for a successive content object; anddisseminating an interest, which corresponds to the successive content object, to obtain the successive content object.
  • 12. The method of claim 10, wherein the data item's starting boundary corresponds to one or more of: a starting boundary of the target content object; andan offset from the target content object's starting boundary.
  • 13. The method of claim 10, wherein the reference indicates: an identifier for the target content object; anda data offset, from the target content object's starting boundary, for the data item.
  • 14. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising: segmenting, by a computer, digital content into a sequence of content objects;determining a target content object of the sequence of content objects, wherein the target content object is to be processed out-of-sequence;determining a source content object of the sequence of content objects, wherein the target content object is to be processed after the source content object;inserting a reference into the source content object, wherein the reference indicates that the target content object is to be processed following the source content object, wherein the reference is distinct from a name for the source content object; andstoring the sequence of content objects, wherein the sequence includes the reference inserted into the source content object.
  • 15. The storage medium of claim 14, wherein the digital content includes a plurality of data items, and wherein a content object's starting boundary or ending boundary corresponds to one or more of: a starting boundary of a data item;an ending boundary of a data item; andan offset between a data item's starting boundary and ending boundary.
  • 16. The storage medium of claim 14, wherein the reference comprises one or more of: an identifier for the target content object; anda data offset within the target content object.
  • 17. The storage medium of claim 16, wherein the identifier includes a hierarchically structured variable-length identifier.
  • 18. The storage medium of claim 14, wherein the digital content includes one or more of: an audio stream;a video stream;executable instructions;a document;a graphical interchange format file;encrypted code; anda text stream.
  • 19. The storage medium of claim 18, further comprising: encoding the contents of a source media stream to a target media-stream format; andgenerating the digital content to include the source media stream in the target media-stream format.
  • 20. The storage medium of claim 14, wherein determining the target object involves: determining a file-data offset of the data file, which is to be processed out-of-sequence; anddetermining, from the sequence of content objects, the content object that corresponds to the file-data offset.
  • 21. The storage medium of claim 14, further comprising: receiving an interest for a content object; andin response to determining that the content object is stored in a local repository, sending the content object through an interface associated with the interest.
  • 22. The storage medium of claim 14, further comprising publishing the sequence of content objects, wherein publishing a respective content object involves disseminating an advertisement for the content object over a content-centric network.
  • 23. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising: disseminating an interest for digital content, wherein a name for the interest is a hierarchically structured variable length identifier comprised of contiguous name components ordered from a most general level to a most specific level;receiving a content object, which corresponds to the digital content and satisfies the interest;determining that the received content object includes a reference to a data item from a target content object, wherein the reference is distinct from a name for the received content object; anddisseminating an interest for the target content object to obtain the data item.
  • 24. The storage medium of claim 23, wherein the method further comprises: generating an interest for a successive content object; anddisseminating an interest, which corresponds to the successive content object, to obtain the successive content object.
  • 25. The storage medium of claim 23, wherein the data item's starting boundary corresponds to one or more of: a starting boundary of the target content object; andan offset from the target content object's starting boundary.
US Referenced Citations (380)
Number Name Date Kind
817441 Niesz Apr 1906 A
4309569 Merkle Jan 1982 A
4921898 Lenney May 1990 A
5070134 Oyamada Dec 1991 A
5110856 Oyamada May 1992 A
5506844 Rao Apr 1996 A
5629370 Freidzon May 1997 A
5870605 Bracho Feb 1999 A
6052683 Irwin Apr 2000 A
6091724 Chandra Jul 2000 A
6173364 Zenchelsky Jan 2001 B1
6226618 Downs May 2001 B1
6233646 Hahm May 2001 B1
6332158 Risley Dec 2001 B1
6366988 Skiba Apr 2002 B1
6574377 Cahill Jun 2003 B1
6654792 Verma Nov 2003 B1
6667957 Corson Dec 2003 B1
6681220 Kaplan Jan 2004 B1
6681326 Son Jan 2004 B2
6769066 Botros Jul 2004 B1
6772333 Brendel Aug 2004 B1
6862280 Bertagna Mar 2005 B1
6901452 Bertagna May 2005 B1
6917985 Madruga Jul 2005 B2
6968393 Chen Nov 2005 B1
6977934 Dalby Dec 2005 B1
6981029 Menditto Dec 2005 B1
7013389 Srivastava Mar 2006 B1
7031308 Garcia-Luna-Aceves Apr 2006 B2
7061877 Gummalla Jun 2006 B1
7206860 Murakami Apr 2007 B2
7257837 Xu Aug 2007 B2
7287275 Moskowitz Oct 2007 B2
7315541 Housel Jan 2008 B1
7339929 Zelig Mar 2008 B2
7350229 Lander Mar 2008 B1
7376790 Lango May 2008 B2
7382787 Barnes Jun 2008 B1
7444251 Nikovski Oct 2008 B2
7466703 Arunachalam Dec 2008 B1
7472422 Agbabian Dec 2008 B1
7496668 Hawkinson Feb 2009 B2
7509425 Rosenberg Mar 2009 B1
7523016 Surdulescu Apr 2009 B1
7529806 Shteyn May 2009 B1
7543064 Juncker Jun 2009 B2
7552233 Raju Jun 2009 B2
7555482 Korkus Jun 2009 B2
7555563 Ott Jun 2009 B2
7567547 Mosko Jul 2009 B2
7567946 Andreoli Jul 2009 B2
7580971 Gollapudi Aug 2009 B1
7623535 Guichard Nov 2009 B2
7647507 Feng Jan 2010 B1
7660324 Oguchi Feb 2010 B2
7685290 Satapati Mar 2010 B2
7698463 Ogier Apr 2010 B2
7747625 Gargi Jun 2010 B2
7769887 Bhattacharyya Aug 2010 B1
7779467 Choi Aug 2010 B2
7801177 Luss Sep 2010 B2
7816441 Elizalde Oct 2010 B2
7831733 Sultan Nov 2010 B2
7908337 Garcia-Luna-Aceves Mar 2011 B2
7924837 Shabtay Apr 2011 B1
7953885 Devireddy May 2011 B1
8000267 Solis Aug 2011 B2
8010691 Kollmansberger Aug 2011 B2
8074289 Carpentier Dec 2011 B1
8117441 Kurien Feb 2012 B2
8160069 Jacobson Apr 2012 B2
8204060 Jacobson Jun 2012 B2
8214364 Bigus Jul 2012 B2
8224985 Takeda Jul 2012 B2
8225057 Zheng Jul 2012 B1
8271578 Sheffi Sep 2012 B2
8312064 Gauvin Nov 2012 B1
8386622 Jacobson Feb 2013 B2
8467297 Liu Jun 2013 B2
8553562 Allan Oct 2013 B2
8572214 Garcia-Luna-Aceves Oct 2013 B2
8654649 Vasseur Feb 2014 B2
8665757 Kling Mar 2014 B2
8667172 Ravindran Mar 2014 B2
8688619 Ezick Apr 2014 B1
8699350 Kumar Apr 2014 B1
8750820 Allan Jun 2014 B2
8761022 Chiabaut Jun 2014 B2
8762477 Xie Jun 2014 B2
8762570 Qian Jun 2014 B2
8762707 Killian Jun 2014 B2
8767627 Ezure Jul 2014 B2
8817594 Gero Aug 2014 B2
8826381 Kim Sep 2014 B2
8832302 Bradford Sep 2014 B1
8836536 Marwah Sep 2014 B2
8862774 Vasseur Oct 2014 B2
8903756 Zhao Dec 2014 B2
8937865 Kumar Jan 2015 B1
9071498 Beser Jun 2015 B2
9112895 Lin Aug 2015 B1
20020010795 Brown Jan 2002 A1
20020048269 Hong Apr 2002 A1
20020054593 Morohashi May 2002 A1
20020077988 Sasaki Jun 2002 A1
20020078066 Robinson Jun 2002 A1
20020138551 Erickson Sep 2002 A1
20020176404 Girard Nov 2002 A1
20020188605 Adya Dec 2002 A1
20020199014 Yang Dec 2002 A1
20030046437 Eytchison Mar 2003 A1
20030048793 Pochon Mar 2003 A1
20030051100 Patel Mar 2003 A1
20030074472 Lucco Apr 2003 A1
20030097447 Johnston May 2003 A1
20030140257 Paterka Jul 2003 A1
20040024879 Dingman Feb 2004 A1
20040030602 Rosenquist Feb 2004 A1
20040073715 Folkes Apr 2004 A1
20040139230 Kim Jul 2004 A1
20040221047 Grover Nov 2004 A1
20040225627 Botros Nov 2004 A1
20040252683 Kennedy Dec 2004 A1
20050003832 Osafune Jan 2005 A1
20050028156 Hammond Feb 2005 A1
20050043060 Brandenberg Feb 2005 A1
20050050211 Kaul Mar 2005 A1
20050074001 Mattes Apr 2005 A1
20050149508 Deshpande Jul 2005 A1
20050159823 Hayes Jul 2005 A1
20050198351 Nog Sep 2005 A1
20050249196 Ansari Nov 2005 A1
20050259637 Chu Nov 2005 A1
20050262217 Nonaka Nov 2005 A1
20050289222 Sahim Dec 2005 A1
20060010249 Sabesan Jan 2006 A1
20060029102 Abe Feb 2006 A1
20060039379 Abe Feb 2006 A1
20060051055 Ohkawa Mar 2006 A1
20060072523 Richardson Apr 2006 A1
20060099973 Nair May 2006 A1
20060129514 Watanabe Jun 2006 A1
20060133343 Huang Jun 2006 A1
20060173831 Basso Aug 2006 A1
20060193295 White Aug 2006 A1
20060206445 Andreoli Sep 2006 A1
20060215684 Capone Sep 2006 A1
20060223504 Ishak Oct 2006 A1
20060256767 Suzuki Nov 2006 A1
20060268792 Belcea Nov 2006 A1
20070019619 Foster Jan 2007 A1
20070073888 Madhok Mar 2007 A1
20070094265 Korkus Apr 2007 A1
20070112880 Yang May 2007 A1
20070124412 Narayanaswami May 2007 A1
20070127457 Mirtorabi Jun 2007 A1
20070160062 Morishita Jul 2007 A1
20070162394 Zager Jul 2007 A1
20070189284 Kecskemeti Aug 2007 A1
20070195765 Heissenbuttel Aug 2007 A1
20070204011 Shaver Aug 2007 A1
20070209067 Fogel Sep 2007 A1
20070239892 Ott Oct 2007 A1
20070240207 Belakhdar Oct 2007 A1
20070245034 Retana Oct 2007 A1
20070253418 Shiri Nov 2007 A1
20070255699 Sreenivas Nov 2007 A1
20070255781 Li Nov 2007 A1
20070274504 Maes Nov 2007 A1
20070276907 Maes Nov 2007 A1
20070276989 Mosek Nov 2007 A1
20070294187 Scherrer Dec 2007 A1
20080005056 Stelzig Jan 2008 A1
20080010366 Duggan Jan 2008 A1
20080037420 Tang Feb 2008 A1
20080043989 Furutono Feb 2008 A1
20080046340 Brown Feb 2008 A1
20080059631 Bergstrom Mar 2008 A1
20080080440 Yarvis Apr 2008 A1
20080101357 Iovanna May 2008 A1
20080107034 Jetcheva May 2008 A1
20080123862 Rowley May 2008 A1
20080133583 Artan Jun 2008 A1
20080133755 Pollack Jun 2008 A1
20080151755 Nishioka Jun 2008 A1
20080159271 Kutt Jul 2008 A1
20080186901 Itagaki Aug 2008 A1
20080200153 Fitzpatrick Aug 2008 A1
20080215669 Gaddy Sep 2008 A1
20080216086 Tanaka Sep 2008 A1
20080243992 Jardetzky Oct 2008 A1
20080256359 Kahn Oct 2008 A1
20080270618 Rosenberg Oct 2008 A1
20080271143 Stephens Oct 2008 A1
20080287142 Keighran Nov 2008 A1
20080288580 Wang Nov 2008 A1
20080320148 Capuozzo Dec 2008 A1
20090013324 Gobara Jan 2009 A1
20090022154 Kiribe Jan 2009 A1
20090024641 Quigley Jan 2009 A1
20090030978 Johnson Jan 2009 A1
20090037763 Adhya Feb 2009 A1
20090052660 Chen Feb 2009 A1
20090067429 Nagai Mar 2009 A1
20090077184 Brewer Mar 2009 A1
20090092043 Lapuh Apr 2009 A1
20090097631 Gisby Apr 2009 A1
20090103515 Pointer Apr 2009 A1
20090113068 Fujihira Apr 2009 A1
20090144300 Chatley Jun 2009 A1
20090157887 Froment Jun 2009 A1
20090185745 Momosaki Jul 2009 A1
20090193101 Munetsugu Jul 2009 A1
20090222344 Greene Sep 2009 A1
20090228593 Takeda Sep 2009 A1
20090254572 Redlich Oct 2009 A1
20090268905 Matsushima Oct 2009 A1
20090285209 Stewart Nov 2009 A1
20090287835 Jacobson Nov 2009 A1
20090288163 Jacobson Nov 2009 A1
20090292743 Bigus Nov 2009 A1
20090293121 Bigus Nov 2009 A1
20090300079 Shitomi Dec 2009 A1
20090300407 Kamath Dec 2009 A1
20090307333 Welingkar Dec 2009 A1
20090323632 Nix Dec 2009 A1
20100005061 Basco Jan 2010 A1
20100027539 Beverly Feb 2010 A1
20100046546 Ram Feb 2010 A1
20100057929 Merat Mar 2010 A1
20100088370 Wu Apr 2010 A1
20100094767 Miltonberger Apr 2010 A1
20100098093 Ejzak Apr 2010 A1
20100100465 Cooke Apr 2010 A1
20100103870 Garcia-Luna-Aceves Apr 2010 A1
20100124191 Vos May 2010 A1
20100125911 Bhaskaran May 2010 A1
20100131660 Dec May 2010 A1
20100150155 Napierala Jun 2010 A1
20100165976 Khan Jul 2010 A1
20100169478 Saha Jul 2010 A1
20100169503 Kollmansberger Jul 2010 A1
20100180332 Ben-Yochanan Jul 2010 A1
20100182995 Hwang Jul 2010 A1
20100185753 Liu Jul 2010 A1
20100195653 Jacobson Aug 2010 A1
20100195654 Jacobson Aug 2010 A1
20100195655 Jacobson Aug 2010 A1
20100217874 Anantharaman Aug 2010 A1
20100232402 Przybysz Sep 2010 A1
20100232439 Dham Sep 2010 A1
20100235516 Nakamura Sep 2010 A1
20100246549 Zhang Sep 2010 A1
20100250497 Redlich Sep 2010 A1
20100250939 Adams Sep 2010 A1
20100268782 Zombek Oct 2010 A1
20100272107 Papp Oct 2010 A1
20100284309 Allan Nov 2010 A1
20100284404 Gopinath Nov 2010 A1
20100293293 Beser Nov 2010 A1
20100322249 Thathapudi Dec 2010 A1
20110013637 Xue Jan 2011 A1
20110022812 vanderLinden Jan 2011 A1
20110055392 Shen Mar 2011 A1
20110055921 Narayanaswamy Mar 2011 A1
20110090908 Jacobson Apr 2011 A1
20110106755 Hao May 2011 A1
20110145597 Yamaguchi Jun 2011 A1
20110145858 Philpott Jun 2011 A1
20110153840 Narayana Jun 2011 A1
20110161408 Kim Jun 2011 A1
20110202609 Chaturvedi Aug 2011 A1
20110231578 Nagappan Sep 2011 A1
20110239256 Gholmieh Sep 2011 A1
20110258049 Ramer Oct 2011 A1
20110264824 Venkata Subramanian Oct 2011 A1
20110265174 Thornton Oct 2011 A1
20110271007 Wang Nov 2011 A1
20110286457 Ee Nov 2011 A1
20110286459 Rembarz Nov 2011 A1
20110295783 Zhao Dec 2011 A1
20110299454 Krishnaswamy Dec 2011 A1
20120011170 Elad Jan 2012 A1
20120011551 Levy Jan 2012 A1
20120036180 Thornton Feb 2012 A1
20120066727 Nozoe Mar 2012 A1
20120106339 Mishra May 2012 A1
20120114313 Phillips May 2012 A1
20120120803 Farkas May 2012 A1
20120136676 Goodall May 2012 A1
20120136936 Quintuna May 2012 A1
20120136945 Lee May 2012 A1
20120141093 Yamaguchi Jun 2012 A1
20120155464 Kim Jun 2012 A1
20120158973 Jacobson Jun 2012 A1
20120163373 Lo Jun 2012 A1
20120179653 Araki Jul 2012 A1
20120197690 Agulnek Aug 2012 A1
20120198048 Ioffe Aug 2012 A1
20120221150 Arensmeier Aug 2012 A1
20120224487 Hui Sep 2012 A1
20120257500 Lynch Oct 2012 A1
20120284791 Miller Nov 2012 A1
20120290669 Parks Nov 2012 A1
20120290919 Melnyk Nov 2012 A1
20120291102 Cohen Nov 2012 A1
20120314580 Hong Dec 2012 A1
20120317307 Ravindran Dec 2012 A1
20120331112 Chatani Dec 2012 A1
20130041982 Shi Feb 2013 A1
20130051392 Filsfils Feb 2013 A1
20130060962 Wang Mar 2013 A1
20130073552 Rangwala Mar 2013 A1
20130074155 Huh Mar 2013 A1
20130091539 Khurana Apr 2013 A1
20130110987 Kim May 2013 A1
20130111063 Lee May 2013 A1
20130151584 Westphal Jun 2013 A1
20130163426 Beliveau Jun 2013 A1
20130166668 Byun Jun 2013 A1
20130173822 Hong Jul 2013 A1
20130182568 Lee Jul 2013 A1
20130185406 Choi Jul 2013 A1
20130197698 Shah Aug 2013 A1
20130198119 Eberhardt, III Aug 2013 A1
20130219038 Lee Aug 2013 A1
20130219081 Qian Aug 2013 A1
20130219478 Mahamuni Aug 2013 A1
20130223237 Hui Aug 2013 A1
20130227166 Ravindran Aug 2013 A1
20130242996 Varvello Sep 2013 A1
20130250809 Hui Sep 2013 A1
20130282854 Jang Oct 2013 A1
20130282860 Zhang Oct 2013 A1
20130282920 Zhang Oct 2013 A1
20130304937 Lee Nov 2013 A1
20130329696 Xu Dec 2013 A1
20130336323 Srinivasan Dec 2013 A1
20130343408 Cook Dec 2013 A1
20140003232 Guichard Jan 2014 A1
20140006565 Muscariello Jan 2014 A1
20140029445 Hui Jan 2014 A1
20140032714 Liu Jan 2014 A1
20140040505 Barton Feb 2014 A1
20140074730 Arensmeier Mar 2014 A1
20140075567 Raleigh Mar 2014 A1
20140082135 Jung Mar 2014 A1
20140089454 Jeon Mar 2014 A1
20140096249 Dupont Apr 2014 A1
20140129736 Yu May 2014 A1
20140136814 Stark May 2014 A1
20140140348 Perlman May 2014 A1
20140143370 Vilenski May 2014 A1
20140146819 Bae May 2014 A1
20140149733 Kim May 2014 A1
20140156396 deKozan Jun 2014 A1
20140172783 Suzuki Jun 2014 A1
20140172981 Kim Jun 2014 A1
20140173034 Liu Jun 2014 A1
20140192717 Liu Jul 2014 A1
20140195328 Ferens Jul 2014 A1
20140195666 Dumitriu Jul 2014 A1
20140233575 Xie Aug 2014 A1
20140237085 Park Aug 2014 A1
20140280823 Varvello Sep 2014 A1
20140281489 Peterka Sep 2014 A1
20140281505 Zhang Sep 2014 A1
20140282816 Xie Sep 2014 A1
20140289325 Solis Sep 2014 A1
20140289790 Wilson Sep 2014 A1
20140314093 You Oct 2014 A1
20140365550 Jang Dec 2014 A1
20150006896 Franck Jan 2015 A1
20150018770 Baran Jan 2015 A1
20150032892 Narayanan Jan 2015 A1
20150063802 Bahadur Mar 2015 A1
20150095481 Ohnishi Apr 2015 A1
20150095514 Yu Apr 2015 A1
20150188770 Naiksatam Jul 2015 A1
Foreign Referenced Citations (15)
Number Date Country
1720277 Jun 1967 DE
19620817 Nov 1997 DE
0295727 Dec 1988 EP
0757065 Jul 1996 EP
1077422 Feb 2001 EP
1384729 Jan 2004 EP
2124415 Nov 2009 EP
2214357 Aug 2010 EP
03005288 Jan 2003 WO
03042254 May 2003 WO
03049369 Jun 2003 WO
03091297 Nov 2003 WO
2007113180 Oct 2007 WO
2007144388 Dec 2007 WO
2011049890 Apr 2011 WO
Non-Patent Literature Citations (147)
Entry
Jacobson, Van et al., “Content-Centric Networking, Whitepaper Describing Future Assurable Global Networks”, Palo Alto Research Center, Inc., Jan. 30, 2007, pp. 1-9.
Koponen, Teemu et al., “A Data-Oriented (and Beyond) Network Architecture”, SIGCOMM '07, Aug. 27-31, 2007, Kyoto, Japan, XP-002579021, p. 181-192.
Beben et al., “Content Aware Network based on Virtual Infrastructure”, 2012 13th ACIS International Conference on Software Engineering.
Biradar et al., “Review of multicast routing mechanisms in mobile ad hoc networks”, Aug. 2016, Journal of Network$.
Detti et al., “Supporting the Web with an information centric network that routes by name”, Aug. 2012, Computer Networks 56, pp. 3705-3702.
Garcia-Luna-Aceves et al., “Automatic Routing Using Multiple Prefix Labels”, 2012, IEEE, Ad Hoc and Sensor Networking Symposium.
Hoque et al., ‘NLSR: Named-data Link State Routing Protocol’, Aug. 12, 2013, ICN 2013, pp. 15-20.
Ishiyama, “On the Effectiveness of Diffusive Content Caching in Content-Centric Networking”, Nov. 5, 2012, IEEE, Information and Telecommunication Technologies (APSITT), 2012 9th Asia-Pacific Symposium.
L. Wang et al., ‘OSPFN: An OSPF Based Routing Protocol for Named Data Networking,’ Technical Report NDN-0003, 2012.
Merindol et al., “An efficient algorithm to enable path diversity in link state routing networks”, Jan. 10, Computer Networks 55 (2011), pp. 1132-1140.
Soh et al., “Efficient Prefix Updates for IP Router Using Lexicographic Ordering and Updateable Address Set”, Jan. 2008, IEEE Transactions on Computers, vol. 57, No. 1.
V. Jacobson et al., ‘Networking Named Content,’ Proc. IEEE CoNEXT '09, Dec. 2009.
Ao-Jan Su, David R. Choffnes, Aleksandar Kuzmanovic, and Fabian E. Bustamante. Drafting Behind Akamai: Inferring Network Conditions Based on CDN Redirections. IEEE/ACM Transactions on Networking {Feb. 2009).
C. Gentry and A. Silverberg. Hierarchical ID-Based Cryptography. Advances in Cryptology—ASIACRYPT 2002. Springer Berlin Heidelberg (2002).
D. Boneh and M. Franklin. Identity-Based Encryption from the Weil Pairing. Advances in Cryptology—CRYPTO 2001, vol. 2139, Springer Berlin Heidelberg (2001).
H. Xiong, X. Zhang, W. Zhu, and D. Yao. CloudSeal: End-to$2.
J. Bethencourt, A, Sahai, and B. Waters, ‘Ciphertext-policy attribute-based encryption,’ in Proc. IEEE Security & Privacy 2007, Berkeley, CA, USA, May 2007, pp. 321-334.
J. Lotspiech, S. Nusser, and F. Pestoni. Anonymous Trust: Digital Rights Management using Broadcast Encryption. Proceedings of the IEEE 92.6 (2004).
J. Shao and Z. Cao. CCA-Secure Proxy Re-Encryption without Pairings. Public Key Cryptography. Springer Lecture Notes in Computer Science vol. 5443 (2009).
M. Blaze, G. Bleumer, and M. Strauss, ‘Divertible protocols and atomic prosy cryptography,’ in Proc. EUROCRYPT 1998, Espoo, Finland, May-Jun. 1998, pp. 127-144.
R. H. Deng, J. Weng, S. Liu, and K. Chen. Chosen-Ciphertext Secure Proxy Re-Encryption without Pairings. CANS. Spring Lecture Notes in Computer Science vol. 5339 (2008).
RTMP (2009). Available online at http://wwwimages.adobe.com/www.adobe.com/content/dam/Adobe/en/devnet/rtmp/ pdf/rtmp specification 1.0.pdf.
S. Chow, J. Weng, Y. Yang, and R. Deng. Efficient Unidirectional Proxy Re-Encryption. Progress in Cryptology—AFRICACRYPT 2010. Springer Berlin Heidelberg (2010).
S. Kamara and K. Lauter. Cryptographic Cloud Storage. Financial Cryptography and Data Security. Springer Berlin Heidelberg (2010).
Sandvine, Global Internet Phenomena Report—Spring 2012. Located online at http://www.sandvine.com/downloads/ documents/Phenomenal H 2012/Sandvine Global Internet Phenomena Report 1H 2012.pdf.
The Despotify Project (2012). Available online at http://despotify.sourceforge.net/.
V. K. Adhikari, S. Jain, Y. Chen, and Z.-L. Zhang. Vivisecting Youtube:An Active Measurement Study. In INFOCOM12 Mini-conference (2012).
Vijay Kumar Adhikari, Yang Guo, Fang Hao, Matteo Varvello, Volker Hilt, Moritz Steiner, and Zhi-Li Zhang. Unreeling Netflix: Understanding and Improving Multi-CDN Movie Delivery. In the Proceedings of IEEE INFOCOM 2012 (2012).
Jacobson, Van et al. ‘VoCCN: Voice Over Content-Centric Networks.’ Dec. 1, 2009. ACM ReArch'09.
Rosenberg, J. “Interactive Connectivity Establishment (ICE): A Protocol for Network Address Translator (NAT) Traversal for Offer/Answer Protocols”, Apr. 2010, pp. 1-117.
Shih, Eugene et al., ‘Wake on Wireless: An Event Driven Energy Saving Strategy for Battery Operated Devices’, Sep. 23, 2002, pp. 160-171.
Fall, K. et al., “DTN: an architectural retrospective”, Selected areas in communications, IEEE Journal on, vol. 28, No. 5, Jun. 1, 2008, pp. 828-835.
Gritter, M. et al., ‘An Architecture for content routing support in the Internet’, Proceedings of 3rd Usenix Symposium on Internet Technologies and Systems, 2001, pp. 37-48.
“CCNx,” http://ccnx.org/. downloaded Mar. 11, 2015.
“Content Delivery Network”, Wikipedia, Dec. 10, 2011, http://en.wikipedia.org/w/index.php?title=Content_delivery_network&oldid=465077460.
“Digital Signature” archived on Aug. 31, 2009 at http://web.archive.org/web/20090831170721/http://en.wikipedia.org/wiki/Digital_signature.
“Introducing JSON,” http://www.json.org/. downloaded Mar. 11, 2015.
“Microsoft PlayReady,” http://www.microsoft.com/playready/.downloaded Mar. 11, 2015.
“Pursuing a pub/sub internet (PURSUIT),” http://www.fp7-pursuit.ew/PursuitWeb/. downloaded Mar. 11, 2015.
“The FP7 4WARD project,” http://www.4ward-project.eu/. downloaded Mar. 11, 2015.
A. Broder and A. Karlin, “Multilevel Adaptive Hashing”, Jan. 1990, pp. 43-53.
Detti, Andrea, et al. “CONET: a content centric inter-networking architecture.” Proceedings of the ACM SIGCOMM workshop on Information-centric networking. ACM, 2011.
A. Wolman, M. Voelker, N. Sharma N. Cardwell, A. Karlin, and H.M. Levy, “On the scale and performance of cooperative web proxy caching,” ACM SIGHOPS Operating Systems Review, vol. 33, No. 5, pp. 16-31, Dec. 1999.
Afanasyev, Alexander, et al. “Interest flooding attack and countermeasures in Named Data Networking.” IFIP Networking Conference, 2013. IEEE, 2013.
B. Ahlgren et al., ‘A Survey of Information-centric Networking’ IEEE Commun. Magazine, Jul. 2012, pp. 26-36.
Bari, MdFaizul, et al. ‘A survey of naming and routing in information-centric networks.’ Communications Magazine, IEEE 50.12 (2012): 44-53.
Baugher, Mark et al., “Self-Verifying Names for Read-Only Named Data”, 2012 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Mar. 2012, pp. 274-279.
Brambley, Michael, A novel, low-cost, reduced-sensor approach for providing smart remote monitoring and diagnostics for packaged air conditioners and heat pumps. Pacific Northwest National Laboratory, 2009.
C.A. Wood and E. Uzun, “Flexible end-to-end content security in CCN,” in Proc. IEEE CCNC 2014, Las Vegas, CA, USA, Jan. 2014.
Carzaniga, Antonio, Matthew J. Rutherford, and Alexander L. Wolf. ‘A routing scheme for content-based networking.’ INFOCOM 2004. Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies. vol. 2. IEEE, 2004.
Cho, Jin-Hee, Ananthram Swami, and Ray Chen. “A survey on trust management for mobile ad hoc networks.” Communications Surveys & Tutorials, IEEE 13.4 (2011): 562-583.
Compagno, Alberto, et al. “Poseidon: Mitigating interest flooding DDoS attacks in named data networking.” Local Computer Networks (LCN), 2013 IEEE 38th Conference on. IEEE, 2013.
Conner, William, et al. “A trust management framework for service-oriented environments.” Proceedings of the 18th international conference on World wide web. ACM, 2009.
Content Centric Networking Project (CCN) [online], http://ccnx.org/releases/latest/doc/technical/, Downloaded Mar. 9, 2015.
Content Mediator Architecture for Content-aware Networks (COMET) Project [online], http://www.comet-project.org/, Downloaded Mar. 9, 2015.
D.K. Smetters, P. Golle, and J.D. Thornton, “CCNx access control specifications,” PARC, Tech. Rep., Jul. 2010.
Dabirmoghaddam, Ali, Maziar Mirzazad Barijough, and J. J. Garcia-Luna-Aceves. ‘Understanding optimal caching and opportunistic caching at the edge of information-centric networks.’ Proceedings of the 1st international conference on Information-centric networking. ACM, 2014.
Dijkstra, Edsger W., and Carel S. Scholten. ‘Termination detection for diffusing computations.’ Information Processing Letters 11.1 (1980): 1-4.
Dijkstra, Edsger W., Wim HJ Feijen, and A_J M. Van Gasteren. “Derivation of a termination detection algorithm for distributed computations.” Control Flow and Data Flow: concepts of distributed programming. Springer Berlin Heidelberg, 1986. 507-512.
E. Rescorla and N. Modadugu, “Datagram transport layer security,” IETF RFC 4347, Apr. 2006.
E.W. Dijkstra, W. Feijen, and A.J.M. Van Gasteren, “Derivation of a Termination Detection Algorithm for Distributed Computations,” Information Processing Letter, vol. 16, No. 5, 1983.
Fayazbakhsh, S. K., Lin, Y., Tootoonchian, A., Ghodsi, A., Koponen, T., Maggs, B., & Shenker, S. {Aug. 2013). Less pain, most of the gain: Incrementally deployable ICN. In ACM SIGCOMM Computer Communication Review (vol. 43, No. 4, pp. 147-158). ACM.
G. Tyson, S. Kaune, S. Miles, Y. El-Khatib, A. Mauthe, and A. Taweel, “A trace-driven analysis of caching in content-centric networks,” in Proc. IEEE ICCCN 2012, Munich, Germany, Jul.-Aug. 2012, pp. 1-7.
G. Wang, Q. Liu, and J. Wu, “Hierarchical attribute-based encryption for fine-grained access control in cloud storage services,” in Proc. ACM CCS 2010, Chicago, IL, USA, Oct. 2010, pp. 735-737.
G. Xylomenos et al., “A Survey of Information-centric Networking Research,” IEEE Communication Surveys and Tutorials, Jul. 2013.
Garcia, Humberto E., Wen-Chiao Lin, and Semyon M. Meerkov. “A resilient condition assessment monitoring system.” Resilient Control Systems (ISRCS), 2012 5th International Symposium on. IEEE, 2012.
Garcia-Luna-Aceves, Jose J. ‘A unified approach to loop-free routing using distance vectors or link states.’ ACM SIGCOMM Computer Communication Review. vol. 19. No. 4. ACM, 1989.
Garcia-Luna-Aceves, Jose J. ‘Name-Based Content Routing in Information Centric Networks Using Distance Information’ Proc ACM ICN 2014, Sep. 2014.
Ghali, Cesar, GeneTsudik, and Ersin Uzun. “Needle in a Haystack: Mitigating Content Poisoning in Named-Data Networking.” Proceedings of NDSS Workshop on Security of Emerging Networking Technologies (SENT). 2014.
Ghodsi, Ali, et al. “Information-centric networking: seeing the forest for the trees.” Proceedings of the 10th ACM Workshop on Hot Topics in Networks. ACM, 2011.
Ghodsi, Ali, et al. “Naming in content-oriented architectures.” Proceedings of the ACM SIGCOMM workshop on Information-centric networking. ACM, 2011.
Gupta, Anjali, Barbara Liskov, and Rodrigo Rodrigues. “Efficient Routing for Peer-to-Peer Overlays.” NSDI. vol. 4. 2004.
Heckerman, David, John S. Breese, and Koos Rommelse. “Decision-Theoretic Troubleshooting.” Communications of the ACM. 1995.
Heinemeier, Kristin, et al. “Uncertainties in Achieving Energy Savings from HVAC Maintenance Measures in the Field.” ASHRAE Transactions 118.Part 2 {2012).
Herlich, Matthias et al., “Optimizing Energy Efficiency for Bulk Transfer Networks”, Apr. 13, 2010, pp. 1-3, retrieved for the Internet: URL:http://www.cs.uni-paderborn.de/fileadmin/informationik/ag-karl/publications/miscellaneous/optimizing.pdf (retrieved on Mar. 9, 2012).
I. Psaras, R.G. Clegg, R. Landa, W.K. Chai, and G. Pavlou, “Modelling and evaluation of CCN-caching trees,” in Proc. IFIP Networking 2011, Valencia, Spain, May 2011, pp. 78-91.
Intanagonwiwat, Chalermek, Ramesh Govindan, and Deborah Estrin. ‘Directed diffusion: a scalable and robust communication paradigm for sensor networks.’ Proceedings of the 6th annual international conference on Mobile computing and networking. ACM, 2000.
J. Aumasson and D. Bernstein, “SipHash: a fast short-input PRF”, Sep. 18, 2012.
J. Hur, “Improving security and efficiency in attribute-based data sharing,” IEEE Trans. Knowledge Data Eng., vol. 25, No. 10, pp. 2271-2282, Oct. 2013.
Jacobson et al., “Custodian-Based Information Sharing,” Jul. 2012, IEEE Communications Magazine: vol. 50 Issue 7 (p. 3843).
Ji, Kun, et al. “Prognostics enabled resilient control for model-based building automation systems.” Proceedings of the 12th Conference of International Building Performance Simulation Association. 2011.
K. Liang, L. Fang, W. Susilo, and D.S. Wong, “A Ciphertext-policy attribute-based proxy re-encryption with chosen-ciphertext security,” in Proc. INCoS 2013, Xian, China, Sep. 2013, pp. 552-559.
Katipamula, Srinivas, and Michael R. Brambley. “Review article: methods for fault detection, diagnostics, and prognostics for building systemsa review, Part I.” HVAC&R Research 11.1 (2005): 3-25.
Katipamula, Srinivas, and Michael R. Brambley. “Review article: methods for fault detection, diagnostics, and prognostics for building systemsa review, Part II.” HVAC&R Research 11.2 (2005): 169-187.
L. Zhou, V. Varadharajan, and M. Hitchens, “Achieving secure role-based access control on encrypted data in cloud storage,” IEEE Trans. Inf. Forensics Security, vol. 8, No. 12, pp. 1947-1960, Dec. 2013.
Li, Wenjia, Anupam Joshi, and Tim Finin. “Coping with node misbehaviors in ad hoc networks: A multi-dimensional trust management approach.” Mobile Data Management (MDM), 2010 Eleventh International Conference on. IEEE, 2010.
Lopez, Javier, et al. “Trust management systems for wireless sensor networks: Best practices.” Computer Communications 33.9 (2010): 1086-1093.
M. Green and G. Ateniese, “Identity-based proxy re-encryption,” in Proc. ACNS 2007, Zhuhai, China, Jun. 2007, pp. 288-306.
M. Ion, J. Zhang, and E.M. Schooler, “Toward content-centric privacy in ICN: Attribute-based encryption and routing,” in Proc. ACM SIGCOMM ICN 2013, Hong Kong, China, Aug. 2013, pp. 39-40.
M. Naor and B. Pinkas “Efficient trace and revoke schemes,” in Proc. FC 2000, Anguilla, British West Indies, Feb. 2000, pp. 1-20.
M. Nystrom, S. Parkinson, A. Rusch, and M. Scott, “PKCS#12: Personal information exchange syntax v. 1.1,” IETF RFC 7292, K. Moriarty, Ed., Jul. 2014.
M. Parsa and J.J. Garcia-Luna-Aceves, “A Protocol for Scalable Loop-free Multicast Routing.” IEEE JSAC, Apr. 1997.
M. Walfish, H. Balakrishnan, and S. Shenker, “Untangling the web from DNS,” in Proc. USENIX NSDI 2004, Oct. 2010, pp. 735-737.
Mahadevan, Priya, et al. “Orbis: rescaling degree correlations to generate annotated internet topologies.” ACM SIGCOMM Computer Communication Review. vol. 37. No. 4. ACM, 2007.
Mahadevan, Priya, et al. “Systematic topology analysis and generation using degree correlations.” ACM SIGCOMM Computer Communication Review. vol. 36. No. 4. ACM, 2006.
Matocha, Jeff, and Tracy Camp. ‘A taxonomy of distributed termination detection algorithms.’ Journal of Systems and Software 43.3 (1998): 207-221.
Matteo Varvello et al., “Caesar: A Content Router for High Speed Forwarding”, ICN 2012, Second Edition on Information-Centric Networking, New York, Aug. 2012.
McWilliams, Jennifer A., and Iain S. Walker. “Home Energy Article: A Systems Approach to Retrofitting Residential HVAC Systems.” Lawrence Berkeley National Laboratory (2005).
Mobility First Project [online], http://mobilityfirst.winlab.rutgers.edu/, Downloaded Mar. 9, 2015.
Narasimhan, Sriram, and Lee Brownston. “HyDE—A General Framework for Stochastic and Hybrid Modelbased Diagnosis.” Proc. DX 7 (2007): 162-169.
NDN Project [online], http://www.named-data.net/, Downloaded Mar. 9, 2015.
Omar, Mawloud, Yacine Challal, and Abdelmadjid Bouabdallah. “Certification-based trust models in mobile ad hoc networks: A survey and taxonomy.” Journal of Network and Computer Applications 35.1 (2012): 268-286.
P. Mahadevan, E.Uzun, S. Sevilla, and J. Garcia-Luna-Aceves, “CCN-krs: A key resolution service for ccn,” in Proceedings of the 1st International Conference on Information-centric Networking, Ser. INC 14 New York, NY, USA: ACM, 2014, pp. 97-106. [Online]. Available: http://doi.acm.org/10.1145/2660129.2660154.
S. Deering, “Multicast Routing in Internetworks and Extended LANs,” Proc. ACM SIGCOMM '88, Aug. 1988.
S. Deering et al., “The PIM architecture for wide-area multicast routing,” IEEE/ACM Trans, on Networking, vol. 4, No. 2, Apr. 1996.
S. Jahid, P. Mittal, and N. Borisov, “EASiER: Encryption-based access control in social network with efficient revocation,” in Proc. ACM ASIACCS 2011, Hong Kong, China, Mar. 2011, pp. 411-415.
S. Kamara and K. Lauter, “Cryptographic cloud storage,” in Proc. FC 2010, Tenerife, Canary Islands, Spain, Jan. 2010, pp. 136-149.
S. Kumar et al. “Peacock Hashing: Deterministic and Updatable Hashing for High Performance Networking,” 2008, pp. 556-564.
S. Misra, R. Tourani, and N.E. Majd, “Secure content delivery in information-centric networks: Design, implementation, and analyses,” in Proc. ACM SIGCOMM ICN 2013, Hong Kong, China, Aug. 2013, pp. 73-78.
S. Yu, C. Wang, K. Ren, and W. Lou, “Achieving secure, scalable, and fine-grained data access control in cloud computing,” in Proc. IEEE INFOCOM 2010, San Diego, CA, USA, Mar. 2010, pp. 1-9.
S.J. Lee, M. Gerla, and C. Chiang, “On-demand Multicast Routing Protocol in Multihop Wireless Mobile Networks,” Mobile Networks and Applications, vol. 7, No. 6, 2002.
Scalable and Adaptive Internet Solutions (SAIL) Project [online], http://sail-project.eu/Downloaded Mar. 9, 2015.
Schein, Jeffrey, and Steven T. Bushby. A Simulation Study of a Hierarchical, Rule-Based Method for System-Level Fault Detection and Diagnostics in HVAC Systems. US Department of Commerce,[Technology Administration], National Institute of Standards and Technology, 2005.
Shani, Guy, Joelle Pineau, and Robert Kaplow. “A survey of point-based POMDP solvers.” Autonomous Agents and Multi-Agent Systems 27.1 (2013): 1-51.
Sheppard, John W., and Stephyn GW Butcher. “A formal analysis of fault diagnosis with d-matrices.” Journal of Electronic Testing 23.4 (2007): 309-322.
Shneyderman, Alex et al., ‘Mobile VPN: Delivering Advanced Services in Next Generation Wireless Systems’, Jan. 1, 2003, pp. 3-29.
Solis, Ignacio, and J. J. Garcia-Luna-Aceves. ‘Robust content dissemination in disrupted environments.’ proceedings of the third ACM workshop on Challenged networks. ACM, 2008.
Sun, Ying, and Daniel S. Weld. “A framework for model-based repair.” AAAI. 1993.
T. Ballardie, P. Francis, and J. Crowcroft, “Core Based Trees (CBT),” Proc. ACM SIGCOMM '88, Aug. 1988.
T. Dierts, “The transport layer security (TLS) protocol version 1.2,” IETF RFC 5246, 2008.
T. Koponen, M. Chawla, B.-G. Chun, A. Ermolinskiy, K.H. Kim, S. Shenker, and I. Stoica, ‘A data-oriented (and beyond) network architecture,’ ACM SIGCOMM Computer Communication Review, vol. 37, No. 4, pp. 181-192, Oct. 2007.
V. Goyal, 0. Pandey, A. Sahai, and B. Waters, “Attribute-based encryption for fine-grained access control of encrypted data,” in Proc. ACM CCS 2006, Alexandria, VA, USA, Oct.-Nov. 2006, pp. 89-98.
V. Jacobson, D.K. Smetters, J.D. Thornton, M.F. Plass, N.H. Briggs, and R.L. Braynard, ‘Networking named content,’ in Proc. ACM CoNEXT 2009, Rome, Italy, Dec. 2009, pp. 1-12.
Verma, Vandi, Joquin Fernandez, and Reid Simmons. “Probabilistic models for monitoring and fault diagnosis.” The Second IARP and IEEE/RAS Joint Workshop on Technical Challenges for Dependable Robots in Human Environments. Ed. Raja Chatila. Oct. 2002.
Vutukury, Srinivas, and J. J. Garcia-Luna-Aceves. A simple approximation to minimum-delay routing. vol. 29. No. 4. ACM, 1999.
W.-G. Tzeng and Z.-J. Tzeng, “A public-key traitor tracing scheme with revocation using dynamic shares,” in Proc. PKC 2001, Cheju Island, Korea, Feb. 2001, pp. 207-224.
Waldvogel, Marcel “Fast Longest Prefix Matching: Algorithms, Analysis, and Applications”, A dissertation submitted to the Swiss Federal Institute of Technology Zurich, 2002.
Walker, Iain S. Best practices guide for residential HVAC Retrofits. No. LBNL-53592. Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US), 2003.
Wang, Jiangzhe et al., “DMND: Collecting Data from Mobiles Using Named Data”, Vehicular Networking Conference, 2010 IEEE, pp. 49-56.
Xylomenos, George, et al. “A survey of information-centric networking research.” Communications Surveys & Tutorials, IEEE 16.2 (2014): 1024-1049.
Yi, Cheng, et al. ‘A case for stateful forwarding plane.’ Computer Communications 36.7 (2013): 779-791.
Yi, Cheng, et al. ‘Adaptive forwarding in named data networking.’ ACM SIGCOMM computer communication review 42.3 (2012): 62-67.
Zahariadis, Theodore, et al. “Trust management in wireless sensor networks.” European Transactions on Telecommunications 21.4 (2010): 386-395.
Zhang, et al., “Named Data Networking (NDN) Project”, http://www.parc.com/publication/2709/named-data-networking-ndn-project.html, Oct. 2010, NDN-0001, PARC Tech Report.
Zhang, Lixia, et al. ‘Named data networking.’ ACM SIGCOMM Computer Communication Review 44.3 {2014): 66-73.
D. Trossen and G. Parisis, “Designing and realizing and information-centric internet,” IEEE Communications Magazing, vol. 50, No. 7, pp. 60-67, Jul. 2012.
Gasti, Paolo et al., ‘DoS & DDoS in Named Data Networking’, 2013 22nd International Conference on Computer Communications and Networks (ICCCN), Aug. 2013, pp. 1-7.
J. Hur and D.K. Noh, “Attribute-based access control with efficient revocation in data outsourcing systers,” IEEE Trans. Parallel Distrib. Syst, vol. 22, No. 7, pp. 1214-1221, Jul. 2011.
Kaya et al., “A Low Power Lookup Technique for Multi-Hashing Network Applications”, 2006 IEEE Computer Society Annual Symposium on Emerging VLSI Technologies and Architectures, Mar. 2006.
Hoque et al., “NLSR: Named-data Link State Routing Protocol”, Aug. 12,2013, ICN'13.
Nadeem Javaid, “Analysis and design of quality link metrics for routing protocols in Wireless Networks”, PhD Thesis Defense, Dec. 15, 2010, Universete Paris-Est.
Wetherall, David, “Active Network vision and reality: Lessons form a capsule-based system”, ACM Symposium on Operating Systems Principles, Dec. 1, 1999. pp. 64-79.
Kulkarni A.B. et al., “Implementation of a prototype active network”, IEEE, Open Architectures and Network Programming, Apr. 3, 1998, pp. 130-142.
Anteniese et al., “Improved Proxy Re-Encryption Schemes with Applications to Secure Distributed Storage”, 2006.
Xie et al. “Collaborative Forwarding and Caching in Content Centric Networks”, Networking 2012.
Amadeo et al. “Design and Analysis of a Transport-Level Solution for Content-Centric VANETs”, University “Mediterranea” of Reggio Calabria, Jun. 15, 2013.
Lui et al. (A TLV-Structured Data Naming Scheme for Content-Oriented Networking, pp. 5822-5827, International Workshop on the Network of the Future, Communications (ICC), 2012 IEEE International Conference on Jun. 10-15, 2012).
Related Publications (1)
Number Date Country
20150134680 A1 May 2015 US