The present disclosure relates generally to telecommunication services and, more particularly, to adjusting the use of virtual resources providing communication services responsive to changes in load.
The telephone number mapping is a system of unifying the international telephone number system of the public switched telephone network with the Internet addressing and identification name spaces. Internationally, telephone numbers are systematically organized by the E.164 standard, while the Internet uses the Domain Name System (DNS) for linking domain names to IP addresses and other resource information. Telephone number mapping systems provide facilities to determine applicable Internet communications servers responsible for servicing a given telephone number using DNS queries.
The most prominent standard for telephone number mapping is the E.164 Telephone Number Mapping (ENUM) standard. The ENUM standard uses special DNS record types to translate a telephone number into a Uniform Resource Identifier (URI) or IP address that can be used in Internet communications. Responsive to queries from clients in networks, such as Internet Protocol Multimedia Subsystem (IMS) networks, ENUM servers return Naming Authority Pointer Resource Records (NAPTRs). NAPTR records are most commonly used for applications in Internet communication session management, e.g., in the mapping of servers and user addresses in the Session Initiation Protocol (SIP). The NAPTR record corresponding to the subscriber URI contains the subscriber contact record information.
ENUM therefore functions as a mechanism for translating a telephone number into a domain name with the requested address or number associated with it. ENUM services have become the core of national and international session management protocols for Video/Voice over IP (VoIP). ENUM services are used by VoIP service providers around the world and are expected to be employed for inter-service-provider operability.
While the ENUM standard provides important services, in the competitive world of multimedia IP solutions, there is increasing pressure to improve infrastructure resiliency and cost structures. Physical ENUMs (pENUMs) are limited in the sense that they are fixed on the underlying computing and communications infrastructure, as compared to cloud infrastructures. Once a pENUM is in place, it is not very flexible, e.g., to accommodate changes in traffic loads or location changes.
It should be appreciated that this Summary is provided to introduce a selection of concepts in a simplified form, the concepts being further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of this disclosure, nor is it intended to limit the scope of the present disclosure.
According to an illustrative embodiment a method is provided for adjusting the use of virtual resources providing communication services based on load. Information is received indicative of performance of virtual telephone number mapping service instances dedicated to a specific number range associated with requests for communication services. According to one aspect, a determination is made, for the specific number range, whether the virtual telephone number mapping service instances dedicated to the specific number range are being underutilized based on the received information. Responsive to a determination that the virtual telephone number mapping service instances dedicated to the specific number range are being underutilized, a virtual telephone number mapping service instance dedicated to the specific number range is selected for removal, and removal of the selected virtual telephone number mapping service instance for handling the requests is initiated. According to another aspect, a determination is made, for the specific number range, whether a number of virtual telephone number mapping service instances dedicated to the specific number range is sufficient to handle the requests for communication services. Responsive to determining that the number of virtual telephone number mapping service instances dedicated to the specific number range is not sufficient to handle the requests, instantiation of a virtual telephone mapping instance is initiated.
According to another illustrative embodiment, a system is provided for adjusting the use of virtual resources providing communication services based on load. The system includes a processor and a memory. The memory has instructions stored thereon which, when executed by the processor, cause the processor to perform operations. The operations include receiving information indicative of performance of virtual telephone number mapping service instances dedicated to a specific number range associated with requests for communication services. According to one aspect, the operations include determining, for the specific number range, whether the virtual telephone number mapping service instances dedicated to the specific number range are being underutilized based on the received information. The operations further include, responsive to determining that the virtual telephone number mapping service instances dedicated to the specific number range are being underutilized, selecting a virtual telephone number mapping service instance dedicated to the specific number range for removal and initiating removal of the selected virtual telephone number mapping service instance for handling the requests. According to another aspect, the operations include determining, for the specific number range, whether a number of virtual telephone number mapping service instances dedicated to the specific number range is sufficient to handle the requests for communication services, and, responsive to determining that the number of virtual telephone number mapping service instances dedicated to the specific number range is not sufficient to handle the requests, initializing instantiation of a virtual telephone mapping instance.
According to another illustrative embodiment, a computer readable storage device is provided that has instructions stored thereon which, when executed by a processor, cause the processor to perform operations for adjusting the use of virtual resources providing communication services based on load. The operations include receiving information indicative of performance of virtual telephone number mapping service instances dedicated to a specific number range associated with requests for communication services. According to one aspect, the operations include determining, for the specific number range, whether the virtual telephone number mapping service instances dedicated to the specific number range are being underutilized based on the received information. The operations further include, responsive to determining that the virtual telephone number mapping service instances dedicated to the specific number range are being underutilized, selecting a virtual telephone number mapping service instance dedicated to the specific number range for removal, and initiating removal of the selected virtual telephone number mapping service instance for handling the requests. According to another aspect, the operations include determining, for the specific number range, whether a number of virtual telephone number mapping service instances dedicated to the specific number range is sufficient to handle the requests for communication services, and, responsive to determining that the number of virtual telephone number mapping service instances dedicated to the specific number range is not sufficient to handle the requests, initializing instantiation of a virtual telephone mapping instance.
Detailed illustrative embodiments are disclosed herein. It must be understood that the embodiments described and illustrated are merely examples that may be embodied in various and alternative forms, and combinations thereof. As used herein, the word “illustrative” is used expansively to refer to embodiments that serve as examples or illustrations. The figures are not necessarily to scale and some features may be exaggerated or minimized to show details of particular components. Specific structural and functional details disclosed herein are not to be interpreted as limiting.
The ENUM standard is a core part of national and international session management protocols for providing multimedia communications ENUM servers can be queried for every session initiation.
In the description that follows, for illustrative purposes, the message flow is described as occurring between Internet Protocol (IP) Multimedia Subsystem (IMS) networks. IMS networks provide a standardized architectural framework for delivering IP multimedia services. It should be appreciated, however, that the embodiments described herein are not limited to implementation in IMS networks but are applicable to other networks having a session protocol suitable for delivering IP multimedia services.
The message flow shown in
The S-CSCF 140A also sends a mapping inquiry 5 to the ENUM 150. The ENUM 150 can translate a form of the telephone number into one or more Name Authority Pointer (NAPTR) record(s) indicating the communication end-points that may handle the communication. The ENUM 150 sends a message 6 with one of more NAPTR records, each of which can contain a server endpoint designator (IP name) to the S-CSCF 140A. The S-CSCF 140A, in turn, sends a mapping inquiry 7, including the server IP name to the DNS 160. The DNS 160 returns a message 8 with an IP address which may be used to reach the user end device 110B.
The S-CSCF 140A then sends an invite message 9 to the Interrogating Call Session Control Function (I-CSCF) 130B of the callee's network 100B. The I-CSCF 130B sends a message 10 to the S-CSCF 140A to indicate that the I-CSCF 130B is trying to set up the communication.
The I-CSCF 130B then sends an invite message 11 to the S-CSCF 140B, which responds with a message 12 indicating that the S-CSCF 140B is trying to set up the communication. The S-CSCF 140B, in turn, sends an invite message 13 to the P-CSCF 120B, which responds with a message 14 indicating that the P-CSCF 120B is trying to set up the communication. Finally, the P-CSCF 120B sends an invite message 15 to the user end device 110B, and the user end device 110B responds with a message 16 indicating that it is trying to answer the calling application. Once the communication is established, the call is routed via the Internet, over caller's home network 100A and the callee's home network 100B.
An example of a pENUM is shown in
Referring to
The pENUM 150 also includes a server load balancer 157. The server load balancer 157 receives requests from clients, e.g., the S-CSCF 140A, and routes the requests to the appropriate name server based on the number range associated with the request. The server load balancer 157 also provides responses to clients, e.g., the S-CSCF 140A. Provisioning of the pENUM 150 can be handled by one or more Operations Systems Servers (OSSs) 170. Although not shown, it should be appreciated that the pENUM 150 may also include a data repository for storing data related to provisioning, etc.
While physical ENUM instances have been deployed across the globe, the new industry trend is to migrate towards virtualized cloud platform environments, where virtual machines are used to host one or more services. Virtual machines are software abstractions of physical machines. Multiple virtual machines share the same physical hardware resources. Virtual machines can be hosted in infrastructures that are sometimes referred to as “clouds”.
In a virtualized computer system, a given computer having one type of CPU, called a host, includes an emulator program, referred to as a hypervisor, which allows the host computer to emulate the instructions of a related or possibly unrelated type of CPU, called a guest. The host computer executes an application that will cause one or more host instructions to be called in response to a given guest instruction. The host computer can run both software designed for its own hardware architecture and software written for a guest computer. A guest computer can run its own operating system. In this type of arrangement, the guest computer system is a “virtual machine” as it only exists in the host computer system as a pure software representation of the operation of a specific hardware architecture.
The hypervisor layer includes a hypervisor 210 that allows and manages access to a number of physical resources in the hardware layer (e.g., processor, memory, and hard drive) by at least one virtual machine executing in the virtualization layer. The hypervisor 210 functions as a software-based hardware abstraction layer that controls physical resources and firmware resources of the virtual hardware. The virtualization layer includes virtual or guest machines 220A, 220B, and 220C which may include virtual operating systems and virtual hardware resources, e.g., a processor, a virtual hard drive, a virtual memory, etc. The hypervisor 210 allows each guest operating system 220A, 220B, and 220C to interact with the virtual hardware.
The hardware layer includes physical system hardware 230 including, e.g., a hard drive for storing data, a processor for executing applications, and a memory which may include an operating system which controls scheduling of tasks and access to system resources.
Given the large numbers of subscribers and the fact that the ENUM records must be maintained in memory for real-time session initiation, ENUM is a memory-intensive application. It would be beneficial to virtualize ENUMs to conserve resources and create an ability to adjust the system ENUM resources based on the potentially time-varying load demands of ENUM. However, simply virtualizing a pENUM would not be sufficient to handle the challenges faced by service providers, as the number of subscribers and the memory capacity of virtual machines differ from one service provider to another.
According to illustrative embodiments, virtual ENUMs (vENUMs) are instantiated in a manner that is elastic, allows for easy migration to and from pENUMs and vENUMs, and maximizes the use of vENUMs without instantiating vENUMS unnecessarily. Also, the embodiments described herein allow for an incremental migration from pENUMs to vENUMs, which is important as the industry slowly migrates towards a virtualized environment.
As shown in
Similarly, the pENUM site 300B includes pENUM instances 365A, 365B, . . . , 365N. Each pENUM instance includes a name server that is dedicated to a specific number range.
As noted above, the number range served by a name server is limited based on the capacity of the name server. A pENUM name server may have more capacity than a vENUM name server. Thus, there may be many vENUM instances dedicated to a specific number range that is served by a single pENUM instance.
Referring again to
Similarly, the pENUM site 300B includes a server load balancer 367 that receives requests from clients, e.g., the S-CSCF 140B, and distributes the requests between the pENUM NS instances 365A, 365B, . . . , 365N and/or forwards the requests to the server load balancer 367 to be handled by a pENUM NS instance.
In
The Operational Support Systems (OSSs) 320 interact with the vENUM site 300A and the pENUM site 300B for provisioning, orchestration, performance monitoring, fault recognition, etc. The OSSs 320 are illustrated and described in more detail with respect to
Although not shown, it should be appreciated that the vENUM site 300A and the pENUM site 300B may each include a data repository for storing data regarding provisioned instances, such as the data shown in
The OSSs 320 include systems for configuring and orchestrating the vENUM instances and the pENUM instances. For example, the OSSs 320 may include a Fault Detecting OSS 372 for detecting faults and failure of components of vENUM and/or pENUM sites and initiating recovery and/or migration to other instances (physical and/or virtual). The OSSs 320 may also include a Configuration OSS 374 which communicates with the server load balancers 357 and 367 regarding provisioned instances (including vENUM and pENUM instances) and populates data regarding the provisioned instances in a data repository (not shown). The Fault Detecting OSS 372 may be in communication with the Configuration OSS 374 for facilitating recovery and/or migration to other instances.
The OSSs 320 may also include a Performance Monitoring OSS 376 and a Contraction/Expansion/Elasticity Manager 378. The Performance Monitoring OSS 376 monitors the performance of the ENUM* 300 in terms of capacity and detects when the ENUM* 300 is operating at maximum threshold, indicating that more capacity is needed, or at a minimum capacity, indicating that perhaps the ENUM* 300 is being underutilized.
The Performance Monitoring OSS 376 provides performance metrics to the Configuration OSS 374 and the Contraction/Expansion/Elasticity Manager 378. The Contraction/Expansion/Elasticity Manager 378 makes decisions regarding instantiation of new vENUM instances, removal of vENUM instances, and re-instantiation of removed vENUM instances, depending on the load on the vENUMs as indicated by the performance metrics. Also, the Contraction/Expansion/Elasticity Manager 378 may make decisions regarding instantiation, removal, and reinstantiation based on faults detected by the Fault Detecting OSS 372. Instances of vENUMs may be incrementally added and removed, as needed. The Configuration OSS 374 may change the configuration of pENUM instances and/or vENUM sites based on performance metrics reported by Performance Monitoring OSS 376 and based on the decisions made by the Contraction/Expansion/Elasticity Manager 378.
In addition to the Performance Monitoring OSS 376, there may also be tools 380 which monitor the performance metrics of the ENUM* 300 for other purposes, e.g., call traffic statistics.
According to one embodiment, techniques and mechanisms are provided for instantiating vENUM sites, for VMs which may have any one of several “flavors.” Instantiating flavors of vENUM sites allows for ENUM virtualization for a variety of target platforms. It also allows infeasible vENUM orchestration to be bypassed and allows for re-use of an existing pENUM.
Each service provider must accommodate a certain number of subscribers, and that number of subscribers may vary from one service provider to another. Also, the vENUM flavors available for instantiation may vary from one service provider to another. There are challenges in dealing with the different flavors of vENUMs, including how to automatically partition the service provider subscriber pool numbers, how many minimum vENUM instances to deploy, and how to map such partitions onto groups of vENUM NS instances.
To aid in understanding the challenges of instantiating vENUMs for a given service provider, consider the total number of telephone numbers that a service provider may need to store data for. Currently, for the 10 digits that are commonly used in North America for telephone numbers, the total number of telephone numbers for a service provider would require 1010 (10 trillion) records of data. Each record may consume, for example, 100 bytes of memory (or less or more, depending on the record and whether meta data or back-up data is included). With 100 bytes of memory needed to store each record, a storage capacity of about 1012 bytes would be required to store all the records for the subscribers for a given service provider. This is a hypothetical number which is intentionally high to illustrate the issue at hand, as opposed to exemplify the subscriber data for any specific service provider. A service provider may, for example, have only 125 million subscribers (resulting in 125×108=11.64 GBytes of needed storage).
Given the large number of subscribers for a service provider, which may differ from one service provider to another and may change for any given service provider at any time, a method of virtualizing a pENUM must be flexible. According to an illustrative embodiment, the challenges of virtualizing a pENUM are met by selecting appropriate flavors of available virtual machines for instantiation as vENUMs.
As shown in
As can be seen from
Referring again to
If the memory requirements needed to serve the subscribers is less than or equal to the available flavors, one or more copies of the same virtual machine can be instantiated as a vENUM name server instances, e.g., by the Configuration OSS 374, at step 4050. Once each copy of the same vENUM name server instance is instantiated, data regarding each such copy of vENUM name server instance is populated in a table, such as that shown in
If the available flavors do not have sufficient memory capacity, the Configuration OSS 374 determines at step 4060 that a virtual machine cannot be instantiated to handle requests for the pENUM. As an optional step, the existing pENUM may be used to fulfill a request at step 4070. Step 4070 may be performed by an entity other than the Configuration OSS 374. The process ends at step 4080.
Each service provider that has a pENUM deployment and wants to transform such a deployment to a virtual environment, may encounter different virtualization environments and constraints. As noted above, the virtual machine flavors vary from one service provider to another. A one-to-one mapping of the existing pENUM instances to vENUM instances may or may not be feasible.
Telephone numbers are partitioned for various sizing purposes. Telephone numbers can be partitioned based on various groupings of digits. For example, telephone numbers may be grouped by area codes.
Some of the data of a pENUM site may be partitioned based on telephone number ranges. For example, each pENUM NS instance may serve a number of area codes, and different pENUM NS instance sets (one or more name servers) may be dedicated to telephone numbers having a particular area code. For example, telephone numbers with area codes between 200 and 999 may be further divided into, e.g., five partitions, with a set of (one or more) pENUM NS instances dedicated to each such partition (for example, area codes 200 to 360 for one partition, area codes 361-520 to another partition, and so on). According to an illustrative embodiment, partitioning of the pENUM telephone number range data is used for automatic mapping of a pENUM NS instance to one or more names servers in one or more virtualized vENUM sites.
Beginning with a first pENUM NS instance, at step 4130, the memory footprint of that pENUM instance is computed, e.g., by the Configuration OSS 374, as a function of the number of telephone numbers that can fit in the number range to which the pENUM NS instance is dedicated. For example, the memory required to handle requests for telephone numbers beginning with a particular area code may be determined based on a target number of expected number of subscriber records and/or requests for those telephone numbers. If more than one instance of a pENUM NS instance is used for a target range (e.g., for performance and/or reliability purposes), information about one of them (e.g., the one with the largest amount of resources, or the one with the smallest amount of resources, depending on the preferences, if they are unequal) may be sufficient for this computation. For the purposes of this disclosure, it should be appreciated that the term “memory” includes not only capacity in terms of bytes but also disk space.
At step 4140, a “suitable” virtual machine flavor is selected, e.g., by the Configuration OSS 374, from among the list of available virtual machine flavors. A “suitable” virtual machine flavor may be determined based on any desirable criteria such as, for example, the virtual machine flavor having the largest memory capacity. Other variants of a definition for “suitable” are not excluded.
At step 4150, a ratio of the memory required by a pENUM NS instance to handle requests to the memory capacity of a virtual machine flavor is computed, e.g., by the Configuration OSS 374. This ratio is indicative of the number of virtual machine instances that would be needed to handle requests associated with the number range to which the pENUM NS instance is dedicated. According to an illustrative embodiment, this ratio may be a “ceiling ratio,” such that if the ratio is a fraction, the ratio is rounded up to the next integer.
According to an illustrative embodiment, different virtual machine flavors may have different amounts of memory in terms of bytes and disk space. Thus, at step 4150, different ratios may be computed for determining the number of virtual machine instances needed to accommodate the amount of memory in bytes of the pENUM NS instance and for determining the number of virtual machine NS instances needed to accommodate the disk space of the pENUM instance. If the number of virtual machine instances needed for the virtual machine flavor to accommodate the memory in bytes of the pENUM instance is not the same as the number of virtual machine instances computed to accommodate the disk space of the pENUM, the greater of the determined number of virtual machines instances needed may be selected, e.g., by the Configuration OSS 374.
At step 4160, for a selected pENUM NS, instantiation of each vENUM NS instance is started, e.g., by the Configuration OSS 374. Information about the data that may be collected allocated to each vENUM NS instance can be passed, e.g., to the server load balancers 357 and 367. Such information may also be stored in a data repository in the pENUM. Such information may include, e.g., information about the specific range of telephone numbers that were allocated to that pENUM NS instance that are allocated to a particular vENUM NS instance. More than one copy of a unique vENUM NS instance may be started (for example, for reliability and/or performance reasons). An example of the information that may be stored for a vENUM NS instance copy is shown in
At step 4170, a determination is made, e.g., by the Configuration OSS 374, whether there are any more pENUM NS instances in the list of partitioned pENUM instances. If so, the process returns to step 4130, and the steps are repeated. Otherwise, the process ends at step 4190.
Having described virtualization of pENUM name servers, the following is a description of the orchestration of an environment including vENUMs and pENUMs. Orchestration activities for virtualizations are complex, involve numerous steps, and such steps are inter-dependent. According to an illustrative embodiment, orchestration of vENUM deployment is achieved in a manner that allows for incremental virtualization and dynamic migration between a pENUM environment and a vENUM environment.
Once a minimum number of such virtual machines needed to handle requests for the pENUM has been selected, initial data is reserved and stored in a data repository for each vENUM NS instance at step 4240. An example of a minimum number of copies of any started vENUM NS instance in a sample environment may be 3, where service may be sustainable with sufficient performance, even one or two of such copies experience difficulties and/or is (are) otherwise compromised. This step may also be performed, e.g., by the Configuration OSS 374. This data may include IP addresses for the vENUM NS instances and other data, such as that depicted in
Next, dual provisioning is implemented, e.g., by the Configuration OSS 374 at step 4250. This involves duplicating new provisioning information to one or more vENUM sites and any existing pENUM sites, such as those depicted in
Next, at step 4260, fault detection and alarms are integrated for the updated deployment of vENUMs and pENUMS by the Fault Detection OSS 372 to detect failures in vENUM and pENUM performance and produce alarms. At step 4270, performance monitoring of the updated deployment of vENUMs and pENUMs is integrated by the Performance Monitoring OSS 376.
A query forwarding mechanism for the existing deployed name servers can be updated to integrate the new vENUM name servers of vENUM sites at step 4280. This may involve the Configuration OSS 374 instructing any or all name servers 355A, 355B, . . . 355N, 365A, 365B, . . . 365N and/or the server load balancers 357 and 367 to forward queries as desired. For example, pENUM NS instances may be configured to just forward queries to corresponding vENUM NS instances 355A-N as records for each number range populated in the correct vENUM NS instances 355A-N.
Finally, the new vENUM zone(s) can be updated to advertise their addresses (e.g., using an AnyCast address that can be shared with the pENUM sites) at step 4290. This step may be performed by the Configuration OSS 374. As migration occurs from a pENUM to a vENUM, the name server in the pENUM needs to be modified to indicate that migration is complete. Alternatively, or in addition, the clients (e.g., the S-CSCF 140A) can be updated to incorporate the query address(es) of the new virtual site. The process ends at step 4295.
Having described instantiation and orchestration of vENUM name servers, the following description explains how the number of vENUM name server instances may be adjusted depending on load according to illustrative embodiments.
The data partitioning characteristics of ENUM described above make an ENUM system susceptible to activity storms occurring in various areas. Examples of such activity storms include natural events, such as weather events, and/or man-made events, such as festivals and concerts, at one or more location(s). These activity storms may result in peaks of requests for communication services being presented to the ENUM system for telephone number ranges assigned to those locations.
According to illustrative embodiments, techniques and mechanisms are provided for identifying “hot spots” of heavy activity within vENUM name server instances and automatically adjusting system instantiation engines to gracefully accommodate man-made and/or natural activity storms automatically and without need for human interventions. Techniques and mechanisms are described herein which automatically allow for capacity expansion for the virtualized cloud ENUM using live performance metric data. Persons skilled in the art recognize that manual interventions are also possible and are not excluded to address such adjustments.
According to an illustrative embodiment, the number of vENUM instances may be adjusted in a granular manner, such that a minimum number of vENUM instances are provided to handle hot spots. This allows problem areas to be addressed to handle unexpected load without the over-deployment of precious virtualization resources.
Next, at step 4330, a determination is made whether there are enough vENUM name server instances to handle requests for each telephone number range of interest. This determination may be made, e.g., by the Contraction/Expansion/Elasticity Manager 378 based on the performance metrics data collected by the Performance OSS 376. For example, the Performance OSS 376 may detect that the requests received by the vENUM name server instances for a particular range of telephone numbers have reached or exceeded a predetermined threshold. This threshold may be, for example, a predetermined rate of receipt of such requests or a predetermined CPU utilization rate, memory capacity, or disk space capacity of the physical machine which hosts the vENUM name server instances. Such pre-determined values may be statically defined, or may be dynamically defined (e.g., using historical data).
The telephone number range of interest may include, e.g., all the telephone numbers having a particular area code, all the telephone numbers having a particular telephone area code and exchange prefix (NXX), or any other desired grouping of the digits of a telephone number (typically, for example, beginning with and including the first digit of the area code within a country). For a large metropolitan area, the telephone number range of interest may include, e.g., telephone numbers having more than one area code serving that area.
If, at step 4330, the determination is made that there are enough vENUM name server instances to handle the requests for the telephone number range(s) of interest, the process returns to step 4320. Otherwise, the process proceeds to step 4340.
At step 4340, the number of vENUM name server instances is increased for the telephone number range(s) which need increased responsiveness. The adjustment may be performed by the Contraction/Expansion/Elasticity Manager 378, in conduction with the Configuration OSS 374. At step 4350, the database in the ENUM* is updated, e.g., by the Configuration OSS 374, with information about the new vENUM instances, e.g., information such as that shown in
According to an illustrative embodiment, the expansion of vENUM name server instances may be performed with repetitive instantiations of vENUM name server instances that are associated with the telephone number ranges of interest until the total number of instantiated vENUM name server instances sufficiently supports the increased load.
From step 4350, the process returns to step 4320 and repeats.
In addition to addressing situations in which there are not enough vENUM name server instances to handle requests, it is important that situations are addressed in which there are too many vENUM name server instances, e.g., situations in which vENUM name server instances are underutilized.
Resource under-utilization can be a result of over-engineering. As described above, vENUM name server instances are assigned to specific number ranges. Such vENUM name server instances can be inefficiently pre-engineered with a minimum numbers of instances to handle predicted maximum loads, which may never occur.
Resource under-utilization may also be caused by dynamic events. Such “cool spot” events may be man-made or natural, such as the seasonal closing of schools or businesses in a particular area, during which the number of requests for communication services for a telephone number range may decrease.
Furthermore, as described above with reference to
According to an illustrative embodiment, techniques and mechanisms are provided for real-time, dynamic and graceful resource recovery in vENUM environments in which vENUM name server instances are underutilized. It is desirable to recover underutilized virtual resources so that they may be made available for other purposes.
Next, at step 4430, a determination is made whether there are too many vENUM name server instances dedicated to any telephone number range or to a telephone number range of interest. This determination may be made, e.g., by the Contraction/Expansion/Elasticity Manager 378 based on the performance metrics data collected by the Performance OSS 376. For example, the Performance OSS 376 may detect that the requests received by the vENUM name server instances dedicated to a particular range of telephone numbers have reached or fallen below a predetermined threshold. This threshold may be, e.g., a predetermined rate of receipt of such requests or a predetermined CPU utilization rate, memory capacity, or disk space capacity of the physical machine which hosts the vENUM name server instances, etc. The threshold may represent a point at which the load may be handled by fewer vENUM name server instances. It should be noted that at least one vENUM name server instance dedicated to each telephone number range may be maintained, though it may be underutilized, to prevent disruption of service.
As described above with reference to
If, at step 4430, if it is determined that that there are not too many vENUM name server instances, the process returns to step 4420. If, at step 4430, it is determined that there are too many vENUM name server instances, the number of such instances may be decreased at step 4440, e.g., by the Contraction/Expansion/Elasticity Manager 378, in conjunction with the Configuration OSS 374. A minimum number of vENUM name server instances may be retained to serve the experienced maximum load.
The database in the ENUM* 300 is updated, e.g., by the Configuration OSS 374, at step 4450 by removing records corresponding to deleted vENUM instances and removing these instances from the IP address pool of a front-end server load balancer, e.g., the server load balancer 357.
According to an illustrative embodiment, the contraction of vENUM name server instances may be performed with repetitive removal of vENUM name serer instances that are associated with the telephone number ranges of interest until the total number of instantiated vENUM name server instances is sufficient to support the required load but not over the number needed to support the required load.
From step 4450, the process returns to step 4420 and repeats.
As described above with reference to
For example, when capacity or other resource limitations (e.g., reserved pool of IP addresses) inhibit instantiations of new vENUM name server instances, the techniques and mechanisms described herein may be used to re-use vENUM name server instances previously removed but reserved for future use. The re-use of removed vENUM name server instances may be granular, such that the removed vENUM name server instances are only re-used when a reaction, e.g., to a hot spot, is needed (in case resources for new vENUM instances are not available). This allows service providers to respond to peak loads dynamically and automatically, even if new system resources are unavailable.
At step 4530, a determination is made, e.g., by the Contraction/Expansion/Elasticity Manager 378, whether there are underutilized VENUM instances for any telephone number range or a telephone number range of interest. This determination may be made in a manner similar to that described above with reference to step 4430 of
If it is determined at step 4530 that there are not underutilized vENUM name server instances, the process returns to step 4520.
If, at step 4530, it is determined that there are underutilized VENUM name server instances, the number of vENUM name server instances is decreased for the telephone number range(s) for which the vENUM name server instances are underutilized at step 4540, while leaving enough instances to accommodate the experienced or expected maximum load. This may be performed in a manner similar to that described above with reference to steps 4440 and 4450 of
At step 4550, data regarding the removed instances may be saved, e.g., in a database in the Contraction/Expansion/Elasticity Manager 378 and/or in the Configuration OSS 374. This data may include, e.g., the IP addresses of the removed instances.
At step 4560, a determination is made whether there are enough vENUM name server instances to handle the requests for each telephone number range of interest. This determination may be made in a manner similar to that described above with reference to step 4330 of
If it is determined at step 4560 that there are enough vENUM name server instances to handle requests for a telephone number range, the process returns to step 4520.
If, at step 4560, it is determined that there are not enough vENUM name server instances to handle the requests, e.g., because of the occurrence of a new “hot spot” in the area served by the range of telephone numbers, the process proceeds to step 4570. At step 4570, previously removed vENUM name server instances may be reinstantiated, e.g., by the Contraction/Expansion/Elasticity Manager 378, in conjunction with the Configuration OSS 374. The removed vENUM name server instances are re-instantiated using part of the saved data, e.g., the IP addresses, of the removed instance(s). If there are no more previously-removed vENUM name server instances to be re-instantiated, one or more additional new vENUM name server instances may be instantiated using reserved or dynamically-acquired IP addresses.
At step 4580, the system routing infrastructure is updated, e.g., by the Configuration OSS 374 to reflect the reinstantiation of the removed instances, or instantiations of new instances. At step 4590, the previous instantiation and configuration can be restored when appropriate, e.g., when the load reaches a predetermined level. At step 4595, the process ends.
The vENUM name server instances removed, instantiated and re-instantiated may be selected based on one or more criteria, such as utilization rate of all of the vENUM name server instances that are dedicated to the same telephone number range. For example, one vENUM name server instance may be selected for removal, while ensuring that there are enough resources to handle (e.g., directly or by forwarding) requests for the telephone number range. It should be appreciated that, as described above with reference to
According to this embodiment, selected vENUM name server instance(s) which may be removed due to, e.g., “cool spot” events occurring in a particular area associated with a telephone number range, can be reserved such that they may be re-instantiated to handle “hot spot” events that may later occur in the area associated with that same telephone number range or another range. This allows a quick response to handle a temporary increase in requests in particular area (number range). When it is appropriate, (e.g., a new virtual zone is instantiated, or another peak event for the previous cool spot” is experienced), the selected vENUM name server instances and the associated system configuration may be restored to the original configuration.
According to this embodiment, automated cloud infrastructure elasticity is provided by re-characterizing and re-deploying (e.g., temporarily) existing under-utilized resources, as opposed to relying on an assumption that new resources will be available for deployment. Even if new resources are available for deployment to handle “hot spots”, such deployments and reconfiguration may take too long to be acceptable for responsiveness to events. The techniques and mechanisms described herein provide a “self-healing” system with significant advantages.
It should be understood that the steps or other interactions of the illustrated methods are not necessarily presented in any particular order and that performance of some or all the steps in an alternative order is possible and is contemplated. The steps have been presented in the demonstrated order for ease of description and illustration. Steps can be added, omitted and/or performed simultaneously without departing from the scope of the appended claims. It should also be understood that the method can be ended at any time. In certain embodiments, some or all steps of the method, and/or substantially equivalent steps can be performed by execution of computer-executable instructions stored or included on a transitory or a non-transitory computer-readable medium.
It should further be understood that any mention of a specific virtualization platform is for exemplification purposes only, and does not imply limitations of selections.
According to illustrative embodiments, instantiation of new vENUM zones is orchestrated in a manner that allows for integration with pre-existing pENUM deployments. In the competitive world of multimedia IP solutions with the new trend towards improved infrastructure resiliency and costs structures through virtualization, the embodiments described herein are beneficial to service providers and vendors globally.
It should be appreciated that this orchestration may be part of a larger orchestration, whereby a vENUM is instantiated if possible; but the orchestration scenario can opt to complete the over-all orchestration procedure by reusing an existing non-virtualized pENUM. The embodiments described herein allow for deployment of the larger virtualization by dynamically bypassing an infeasible provisioning of a vENUM based on an attribute, e.g., memory size, that is a key property of a pENUM.
Virtual machine orchestration and other information can be maintained in a variety of fashions. An abstraction of some of the data, which may be used with an orchestration environment for a vENUM is shown in
Referring to
It should be understood that
The term “application”, or variants thereof, is used expansively herein to include routines, program modules, program, components, data structures, algorithms, and the like. Applications can be implemented on various system configurations, including single-processor or multiprocessor systems, minicomputers, mainframe computers, personal computers, handheld-computing devices, microprocessor-based, programmable consumer electronics, combinations thereof, and the like. The terminology “computer-readable media” and variants thereof, as used in the specification and claims, include non-transitory storage media. Storage media can include volatile and/or non-volatile, removable and/or non-removable media, such as, for example, RAM, ROM, EEPROM, flash memory or other memory technology, CDROM, DVD, or other optical disk storage, magnetic tape, magnetic disk storage, or other magnetic storage devices or any other medium, excluding propagating signals, that can be used to store information that can be accessed by the components shown in
According to an illustrative embodiment, the computing device 700 may be implemented in any suitable computing device and on any suitable network. For example, the computing device 700 may be implemented as a server in a cloud in communication with vENUMs and pENUMs over a communication network.
Referring to
The processor 710 executes instructions stored in the memory 730 to perform operations. It should be appreciated that performance of these operations may include the processor performing the operations directly and/or facilitating, directing, or cooperating with another device or component to perform the operations.
Referring again to
The processor 710 can also transmit information between to the pENUM and/or vENUM name servers and server load balancers, in particular to the server load balancers 357 and 367 and/or the name servers 355A, 355B, . . . , 355N and 365A, 365B, . . . 365N via the I/O Data Ports 720. This information can include name server queries and responses.
According to an illustrative embodiment, the processor 710 of a Configuration OSS 374 can perform instantiation of vENUM NS instances as described above with reference to
A processor 710 can transmit data indicative of vENUM instantiation, removal, and re-instantiation via the I/O Data Ports 720. The I/O Data Ports 720 can be implemented with, e.g., an interface including a local area network interface, an antenna or other suitable type of transceiver through which data and signals may be transmitted and received wired and/or wirelessly.
The computing device 700 also includes a physical hard drive 780. The processor 710 communicates with the memory 730 and the hard drive 780 via, e.g., an address/data bus (not shown). The memory is 730 is representative of the overall hierarchy of memory devices containing the software and data used to implement the functionality of the device 700. The memory 730 can include, but is not limited to various types of storage such as, for example, but not limited to, random access memory, read-only memory. As shown in
The I/O device drivers 770 may include various routines accessed through at least one of the OS 760 by the applications 740 to communicate with devices and certain memory components.
The applications 740 can be stored in the memory 730 and/or in a firmware (not shown) as executable instructions, and can be executed by the processor 710. The applications 740 include various programs that implement the various features of the device 700. The applications 740 may include applications for implementing various steps described with reference to
The database 750 represents the static and dynamic data used by the applications 740, the OS 760, the I/O device drivers 770 and other software programs that may reside in the memory 730. The database 750 can be used to store data including listings of flavors of virtual machines available for instantiation, groupings of telephone numbers assigned to pENUM instances, a current configuration of vENUM instances and pENUM instances, memory requirements of pENUM instances, information reserved for removed vENUM instances, etc. Examples of such data are discussed above with reference to
While the memory 730 and storage (e.g., flash drive or hard drive) 780 are illustrated as residing proximate the processor 710, it should be understood that at least a portion of the memory 730 and/or hard drive 780 can be remotely accessed, for example, via another server in the cloud, a remote hard disk drive, a removable storage medium, combinations thereof, and the like. Thus, any of the data, applications, and/or software described above can be stored within the memory 730 and/or accessed via network connections to other data processing systems (not shown) that may include a local area network (LAN), a metropolitan area network (MAN), or a wide area network (WAN), for example.
Although not illustrated, it should be appreciated that other components described may be implemented with a computing device similar to that shown in
The law does not require and it is economically prohibitive to illustrate and teach every possible embodiment of the present claims. Hence, the above-described embodiments are merely illustrative illustrations of implementations set forth for a clear understanding of the principles of the invention. Variations, modifications, and combinations may be made to the above-described embodiments without departing from the scope of the claims. All such variations, modifications, and combinations are included herein by the scope of this disclosure and the following claims.
Number | Name | Date | Kind |
---|---|---|---|
4769811 | Eckberg et al. | Sep 1988 | A |
5751967 | Raab et al. | May 1998 | A |
6643262 | Larsson et al. | Nov 2003 | B1 |
7274683 | Segal | Sep 2007 | B2 |
7567804 | Mangal | Jul 2009 | B1 |
7624417 | Dua | Nov 2009 | B2 |
7706401 | Bae et al. | Apr 2010 | B2 |
7831697 | Fukushima | Nov 2010 | B2 |
7920549 | Alt et al. | Apr 2011 | B2 |
7937438 | Miller et al. | May 2011 | B1 |
8065676 | Sahai et al. | Nov 2011 | B1 |
8086808 | Ichikawa | Dec 2011 | B2 |
8165116 | Ku et al. | Apr 2012 | B2 |
8169951 | Mangal | May 2012 | B1 |
8171160 | Ward et al. | May 2012 | B1 |
8175103 | Germain et al. | May 2012 | B2 |
8250572 | Dahlstedt | Aug 2012 | B2 |
8296434 | Miller et al. | Oct 2012 | B1 |
8305932 | Qiu et al. | Nov 2012 | B2 |
8321376 | Boman et al. | Nov 2012 | B2 |
8359223 | Chi et al. | Jan 2013 | B2 |
8365156 | Sollich | Jan 2013 | B2 |
8407323 | Flavel et al. | Mar 2013 | B2 |
8423646 | Jamjoom et al. | Apr 2013 | B2 |
8429276 | Kumar et al. | Apr 2013 | B1 |
8433802 | Head et al. | Apr 2013 | B2 |
8442955 | Al Kiswany et al. | May 2013 | B2 |
8457117 | Wood et al. | Jun 2013 | B1 |
8458342 | Ku | Jun 2013 | B2 |
8560646 | Sivasubramanian et al. | Oct 2013 | B1 |
8571011 | All et al. | Oct 2013 | B2 |
8594077 | Mangal | Nov 2013 | B2 |
8612599 | Tung et al. | Dec 2013 | B2 |
8631403 | Soundararajan et al. | Jan 2014 | B2 |
8656018 | Keagy et al. | Feb 2014 | B1 |
8689292 | Williams et al. | Apr 2014 | B2 |
8724620 | Ku et al. | May 2014 | B2 |
8750884 | Gorman et al. | Jun 2014 | B1 |
8776090 | Elzur | Jul 2014 | B2 |
8792882 | Fighel | Jul 2014 | B2 |
8830878 | Van Rensburg | Sep 2014 | B1 |
8849976 | Thibeault | Sep 2014 | B2 |
8879545 | Jackson et al. | Nov 2014 | B2 |
8903888 | Hyser et al. | Dec 2014 | B1 |
8909744 | Rathore | Dec 2014 | B2 |
8914511 | Yemini et al. | Dec 2014 | B1 |
8914525 | Ku | Dec 2014 | B2 |
20060041733 | Hyser | Feb 2006 | A1 |
20060165060 | Dua | Jul 2006 | A1 |
20070019545 | All et al. | Jan 2007 | A1 |
20080005403 | Di Flora | Jan 2008 | A1 |
20080090569 | Khan et al. | Apr 2008 | A1 |
20080165706 | Bozionek | Jul 2008 | A1 |
20080166994 | Ku et al. | Jul 2008 | A1 |
20080222633 | Kami | Sep 2008 | A1 |
20080281975 | Qiu et al. | Nov 2008 | A1 |
20080285543 | Qiu et al. | Nov 2008 | A1 |
20080317000 | Jackson | Dec 2008 | A1 |
20090103707 | Mcgary et al. | Apr 2009 | A1 |
20090147770 | Ku | Jun 2009 | A1 |
20090161854 | Ku et al. | Jun 2009 | A1 |
20090248896 | Cohn | Oct 2009 | A1 |
20090249284 | Antosz et al. | Oct 2009 | A1 |
20090276228 | Isaacson | Nov 2009 | A1 |
20090276771 | Nickolov et al. | Nov 2009 | A1 |
20090282404 | Khandekar et al. | Nov 2009 | A1 |
20100042720 | Stienhans et al. | Feb 2010 | A1 |
20100157986 | Rao et al. | Jun 2010 | A1 |
20100223378 | Wei et al. | Sep 2010 | A1 |
20100232592 | Ku | Sep 2010 | A1 |
20100232593 | Ku | Sep 2010 | A1 |
20100281125 | Virtanen et al. | Nov 2010 | A1 |
20100322255 | Hao et al. | Dec 2010 | A1 |
20110019661 | Ku | Jan 2011 | A1 |
20110066597 | Mashtizadeh et al. | Mar 2011 | A1 |
20110078303 | Li et al. | Mar 2011 | A1 |
20110093847 | Shah | Apr 2011 | A1 |
20110138047 | Brown et al. | Jun 2011 | A1 |
20110150196 | Dwight et al. | Jun 2011 | A1 |
20110179184 | Breau et al. | Jul 2011 | A1 |
20110216762 | Nas | Sep 2011 | A1 |
20110235631 | Krishnaswamy et al. | Sep 2011 | A1 |
20110282739 | Mashinsky et al. | Nov 2011 | A1 |
20120066375 | Phaal | Mar 2012 | A1 |
20120130782 | Ratnakar | May 2012 | A1 |
20120173709 | Li et al. | Jul 2012 | A1 |
20120207151 | All et al. | Aug 2012 | A1 |
20120300768 | Huang et al. | Nov 2012 | A1 |
20120323852 | Jain et al. | Dec 2012 | A1 |
20130007753 | Jain | Jan 2013 | A1 |
20130016626 | Qiu et al. | Jan 2013 | A1 |
20130042239 | Mousseau et al. | Feb 2013 | A1 |
20130054813 | Bercovici et al. | Feb 2013 | A1 |
20130060839 | Van Biljon et al. | Mar 2013 | A1 |
20130067345 | Das et al. | Mar 2013 | A1 |
20130129066 | Yeung et al. | May 2013 | A1 |
20130166606 | Fricke | Jun 2013 | A1 |
20130179895 | Calder | Jul 2013 | A1 |
20130182574 | So et al. | Jul 2013 | A1 |
20130185432 | So et al. | Jul 2013 | A1 |
20130232480 | Winterfeldt et al. | Sep 2013 | A1 |
20130232497 | Jalagam et al. | Sep 2013 | A1 |
20130232498 | Mangtani et al. | Sep 2013 | A1 |
20130254854 | Moganti | Sep 2013 | A1 |
20130290499 | Radhakrishnan et al. | Oct 2013 | A1 |
20130294443 | Kahn | Nov 2013 | A1 |
20130297802 | Laribi et al. | Nov 2013 | A1 |
20130326517 | Castillo et al. | Dec 2013 | A1 |
20140052949 | Wang et al. | Feb 2014 | A1 |
20140068602 | Gember et al. | Mar 2014 | A1 |
20140068703 | Balus et al. | Mar 2014 | A1 |
20140082131 | Jagtap | Mar 2014 | A1 |
20140082612 | Breitgand et al. | Mar 2014 | A1 |
20140086253 | Yong | Mar 2014 | A1 |
20140143514 | Kulkarni et al. | May 2014 | A1 |
20140157272 | Dahlstedt | Jun 2014 | A1 |
20140161447 | Graves et al. | Jun 2014 | A1 |
20140164476 | Thomson | Jun 2014 | A1 |
20140173195 | Rossel et al. | Jun 2014 | A1 |
20140176583 | Abiezzi et al. | Jun 2014 | A1 |
20140195604 | Wyatt et al. | Jul 2014 | A1 |
20140204760 | Durrani et al. | Jul 2014 | A1 |
20140211610 | Ku et al. | Jul 2014 | A1 |
20140215033 | Ravichandran et al. | Jul 2014 | A1 |
20140241247 | Kempf et al. | Aug 2014 | A1 |
20140254603 | Banavalikar et al. | Sep 2014 | A1 |
20140269325 | Chrysos et al. | Sep 2014 | A1 |
20140282522 | Daly et al. | Sep 2014 | A1 |
20140297979 | Baron et al. | Oct 2014 | A1 |
20140334482 | Nikeyenkov et al. | Nov 2014 | A1 |
20140337500 | Lee | Nov 2014 | A1 |
20140337834 | Adogla | Nov 2014 | A1 |
20140347998 | Kim et al. | Nov 2014 | A1 |
20140351539 | Raj et al. | Nov 2014 | A1 |
20140355450 | Bhikkaji et al. | Dec 2014 | A1 |
20140362859 | Addanki et al. | Dec 2014 | A1 |
20140365662 | Dave et al. | Dec 2014 | A1 |
20150012570 | Le et al. | Jan 2015 | A1 |
20160088162 | Carlos | Mar 2016 | A1 |
Number | Date | Country |
---|---|---|
744884 | Jun 2002 | AU |
2464065 | Feb 2013 | CA |
1126681 | Aug 2001 | EP |
1820310 | Aug 2007 | EP |
2439637 | Oct 2010 | EP |
2569902 | Mar 2013 | EP |
2779590 | Sep 2014 | EP |
201403315 | Jan 2014 | TW |
WO 2013163216 | Oct 2013 | WO |
WO 2014118736 | Aug 2014 | WO |
WO 2014147480 | Sep 2014 | WO |
Entry |
---|
Verma, Akshat, Gautam Kumar, and Ricardo Koller. “The cost of reconfiguration in a cloud.” Proceedings of the 11th International Middleware Conference Industrial track. ACM, 2010. http: //www.cs.berkeley.edu/ ••gautamk/papers/migration-mwl O .pdf. |
Mi, Haibo, et al. “Online self-reconfiguration with performance guarantee for energy-efficient large-scale cloud computing data centers.” Services Computing (SCC), 2010, IEEE International Conference on. IEEE, 2010. http: //www.trustie.net/userfiles/file/scc2010 .pdf. |
Chieu, Trieu C., et al. “Dynamic scaling of web applications in a virtualized cloud computing environment.” e-Business Engineering, 2009. ICEBE'09. IEEE International Conference on. IEEE, 2009. http://wise.ajou.ac.kr/dlog2012/files/Dynamic%20Scaling%20of%20Web%20Applications%20%20%20in%20a%20Virtualized%20Cloud%20Computing%20Environment.pdf. |
Armbrust, Michael, et al. “A view of cloud computing.” Communications of the ACM 53.4 (2010): 50-58. http://ftp.cs.duke.edu/courses/cps296.4/compsci590.4/fall13/838-CloudPapers/AboveTheClouds.pdf. |
Kesavan, Mukil, Ada Gavrilovska, and Karsten Schwan. “Xerxes: Distributed load generator for cloud-scale experimentation.” Open Cirrus Summit (OCS), 2012 Seventh. IEEE, 2012. http://www.istc-cc.cmu.edu/publications/papers/2012/xerxes.pdf. |
“IBM PureFlex Systems with VMware,” vmware.com, Apr. 2012, Copyright IBM Corporation 2012. http://www.vmware.com/files/pdf/partners/ibm/IBM—PureFlex—Systems—with—VMware.pdf. |
Kakoulli, Elena, Vassos Soteriou, and Theocharis Theocharides. “Intelligent hotspot prediction for network-on-chip-based multicore systems.” Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on 31.3 (2012): 418-431. http//ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6152782&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs—all.jsp%3Farnumber%3D6152782. |
Hao, Fang, et al. “Enhancing dynamic cloud-based services using network virtualization.” Proceedings of the 1st ACM workshop on Virtualized infrastructure systems and architectures. ACM, 2009. http://www1.arl.wustl.edu/˜hs1/publication/p37.pdf. |
“Solution Brief: OpenFlow-Enabled Hybrid Cloud Services Connect Enterprise and Service Provider Data Centers,” Executive Summary, opennetworking.org, Nov. 13, 2012. https://www.opennetworking.org/ja/solution-brief-openflow-enabled-hybrid-cloudservices-connect-enterprise-and-service-provider-data-centers. |
U.S. Non-Provisional Patent Application titled “Methods, Systems, and Computer Readable Storage Devices for Handling Virtualization of a Physical Telephone Number Mapping Service”. |
U.S. Non-Provisional Patent Application titled “Methods, Systems, and Computer Readable Storage Devices for Determining Whether to Forward Requests from a Physical Telephone Number Mapping Service Server to a Virtual Telephone Number Mapping Service Server”. |
U.S. Non-Provisional Patent Application titled “Methods, Systems, and Computer Readable Storage Devices for Determining Whether to Handle a Request for Communication Services by a Physical Telephone Number Mapping Service or a Virtual Telephone Number Mapping Service”. |
http://docs.openstack.org/user-guide-admin/dashboard—manage—flavors.html, Apr. 2015. |
U.S. Office Action dated Nov. 7, 2016 in U.S. Appl. No. 14/814,095. |
Caelli, William, Vicky Liu, and She-I. Chang. “Trust in merged ERP and open data schemes in the ‘Cloud’” (2014). http://eprints.qut.edu.au/69887/1/Caelli—Liu—Chang—submit— 6.pdf. |
Singh, Kulwinder, and Dong-Won Park. “Economical Global Access to a VoiceXML Gateway Using Open Source Technologies.” 22nd International Conference on Computational Linguistics. 2008. http://www.aclweb.org/anthology/W/W08/W08-15.pdf?origin=publication—detail#page=27. |
Ulseth, T. R. O. N. D. “Telephone Number Mapping (ENUM)—A short overview.” TELEKTRONIKK 102.1 (2006): 40. http://www.telenor.com/wp-contenl/uploads/2012/05/T06— 1.pdf#page=42. |
Strand, Lars, and Wolfgang Leister. “A survey of SIP Peering.” NATO ASI—Architects of secure Networks (ASIGE10) (2010). http://larsstrand.no/NR/papers/conf/asige10/ASIGE10-presentation.pdf. |
Kantola, Raimo, Jose Costa Requena, and Nicklas Beijar. “Interoperable routing for IN and IP Telephony.” Computer Networks 35.5 (2001): 597-609. http://www.nellab.tkk.fi/tutkimus/imelio/papers/VOIP/cocom09f-00wpic.pdf. |
Voznak, Miroslay. “Advanced implementation of IP telephony at Czech universities.” WSEAS Transactions on Communications 9.10 (2010): 679-693. http://www.researchgate.net/publication/228564659—Advanced—implementation—of—IP—telephony—at—Czech—universities/file/504635117 a95f4851d. |
Ramanathan, Sakkaravarthi, et al. “Model-based provisioning and management of adaptive distributed communication in mobile cooperative systems.” (2011). http://hal.archives-ouvertes.fr/docs/00/67/69/40/PDF/BookVersion—1.1.pdf. |
Rosenberg, Jonathan. “A data model for presence.” Network Working Group, Cisco Systems, (Jul. 2006). http://tools.ietf.org/html/rfc4479.html. |
Zhang, Ge. “Towards Secure SIP Signalling Service for VoIP applications.” Karlstad University Studies (2009). http://www.cstest.kau.se/gezhang/Zhang—lic.pdf. |
Grefen, Paul, et al. “Dynamic business network process management in instant virtual enterprises.” Computers in Industry 60.2 (2009): 86-103. http://is.tm.tue.nl/staff/heshuis/BETA0/o20WP198.pdf. |
Grefen, Paul, Heiko Ludwig, and Samuii Angelov. “A three-level framework for process and data management of complex e-services.” International Journal of Cooperative Information Systems 12.04 (2003): 487-531. http://www.researchgate.net/publication/220094965—A—ThreeLevel—Framework—for—Process—and—Data—Management—of—Complex—EServices/file/d912f50bcf2dfb9067.pdf. |
Eshuis, Rik, and Paul Grefen. “Constructing customized process views.” Data and Knowledge Engineering 64.2 (2008): 419-438. http://is.ieis.tue.nl/staff/heshuis/ccpv.pdf. |
Vonk, Jochern, and Paul Grefen. “Cross-organizational transaction support for e-services in virtual enterprises.” Distributed and Parallel Databases 14.2 (2003): 137-172. hllp://alexandria.tue.nl/repository/freearticles/613435.pdf? origin=publication—detaii. |
Kecskemeti, Gabor, et al. “An approach for virtual appliance distribution for service deployment.” Future Generation Computer Systems 27.3 (2011): 280-289. http://users.iit.uni-miskolc.hu/˜kecskemeti/publications/KecskemetiFgcsAVSActiveRepo.pdf. |
“Global UNUM: The underlying infrastructure for service discovery in the migration to the all-IP communications future,” A Neustar White paper, neustar.biz, Neustar, Inc., Sterling, VA. 2010. http://www.neustar.biz/carrier/docs/whitepapers/neustar—global—enum—white—paper.pdf. |
Foster, M., T. McGarry, and J. Yu. “Number portability in the Global Switched Telephone Network (GSTN): an overview.” RFC3482, IETF, Feb. 2003. https://tools.ielf.org/html/draft-mayrhofer-enum-loc-enumservice-00. |
Malas, D. “SPEERMINT Peering Architecture,” Internet-Draft, SPEERMINT, Oct. 22, 2010. http://133.40.3.100/pdf/draft-ielf-speermint-architecture-12.pdf. |
Penno, R., “Speermint Peering Architecture,” Internet Draft, Speermint Working Group, Feb. 24, 2008. http://133.40.3.100/pdf/draft-ietf-speermint-architecture-05.pdf. |
Raatikainen, Pertti. “Next Generation Network and Reliability.” Technical Research Centre of Finland (2007). http://iplu.fi/ngn—report.pdf. |
Cakmak, Gorkem. “Internet Interconnection Ecosystem in Finland.” Diss. Aalto University, 2013. https://aaltodoc.aalto.fi/bitstream/handle/123456789/12012/master—Cakmak—G%C3%B6rkem—2013.pdf?sequence=1. |
Notice of Allowance dated Apr. 3, 2017 in U.S. Appl. No. 14/814,095. |
U.S. Office Action dated Apr. 5, 2017 in U.S. Appl. No. 14/814,111. |
Number | Date | Country | |
---|---|---|---|
20170034359 A1 | Feb 2017 | US |