The subject technology provides solutions for performing wireless channel assignments in a wireless network and in particular, for determining optimal channel assignments for hierarchical groups of access points (APs).
In general, IEEE 802.11 Wireless Local Area Network (WLAN) designs are much simpler than that of the 3G networks because the IEEE 802.11 standard was devised to serve a confined area (e.g., a link distance of at most several hundred meters) with stationary and slow-moving users, while the 3G specifications were developed for greater flexibility, coverage and mobility. As a result, the IEEE 802.11 network can support data rates higher than those by the 3G networks.
Networks based on the IEEE 802.11 standard operate in the unlicensed Industrial, Scientific and Medical (ISM) band. Despite the relatively abundant spectrum (i.e., a total of 75 MHz in the 2.4 GHz Band) at the ISM band, as IEEE 802.11 networks are deployed widely, they start to interfere with each other. Such interference leads to a degradation in network throughput.
In order to describe the manner in which the above-recited and other advantages and features of the disclosure can be obtained, a more particular description of the principles briefly described above will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. Understanding that these drawings depict only example aspects of the disclosure and are not therefore to be considered to be limiting of its scope, the principles herein are described and explained with additional specificity and detail through the use of the accompanying drawings in which:
The detailed description set forth below is intended as a description of various configurations of the subject technology and is not intended to represent the only configurations in which the subject technology can be practiced. The appended drawings are incorporated herein and constitute a part of the detailed description. The detailed description includes specific details for the purpose of providing a more thorough understanding of the subject technology. However, it will be clear and apparent that the subject technology is not limited to the specific details set forth herein and may be practiced without these details. In some instances, structures and components are shown in block diagram form in order to avoid obscuring the concepts of the subject technology.
Overview:
Frequency planning, i.e., allocation of a limited number of frequencies, for an IEEE 802.11 network is different from that of a traditional cellular network. In typical cellular networks, such as those based on the Global System for Mobile Communications (GSM) and Enhanced Data GSM Evolution (EDGE) standards, two separate radio channels, namely the traffic and control channels, are used to carry user data and control traffic. After the information is successfully received and processed by a base station (BS), the terminal is assigned with a specific traffic channel for transmitting its data traffic.
There is no such distinction between control and traffic channels in IEEE 802.11 networks. Instead, all user data and control information (in both directions between terminals and APs) are carried on the same physical channel. Access to the channel by multiple transmitters is coordinated by the MAC protocol, e.g., the well-known, Carrier Sense Multiple Access (CSMA) protocol with collision avoidance feature. Although the MAC CSMA protocol helps to mitigate much of the co-channel interference in large multi-cell IEEE 802.11 networks, network performance is still often degraded by adjacent-channel interference.
Due to the multiplicity of available channels (frequency bands), APs in conventional wireless deployments typically select an initial channel, and change selections only when significant interference is detected. Due to the potentially large number of nodes in a wireless network, and changing network conditions (e.g., the addition and subtraction of nodes), it is computationally difficult to determine optimal channel assignments for each wireless node in the network. The computation difficulty of optimal channel assignment calculations increases quickly with each added node, making the problem “NP-complete.” The problem is made further intractable by the dynamic nature of modern wireless deployments; the need for more frequent channel re-assignment is increased as nodes join, leave, and move within the network.
Aspects of the disclosed technology provide solutions for calculating channel assignments for network nodes (e.g., APs), which can be performed quickly and therefore more frequently, to accommodate changing network characteristics. In some approaches, channel assignments/re-assignments can be calculated in an ordered hierarchy, wherein each “layer” of channel calculation hierarchy is performed with concurrent consideration of channel performance of a selected node and each peer node in a defined group, for example, that is based on network distance.
As discussed in further detail below, a process of channel assignment/re-assignment of the disclosed technology can include steps for identifying a multitude of wireless access points (APs) in a wireless network, each of the wireless APs being associated with an initial channel assignment, selecting an AP in the network, determining a channel quality for the channel assignment associated with the AP, and selecting a new channel for the AP based on the channel quality for the initial channel assignment associated with the first AP. In some aspects, the process can further include steps for selecting a second AP from among the APs in the network, determining a channel quality for the channel assignment associated with the second AP, and selecting a new channel for the second AP based on the channel quality for the initial channel assignment associated with the second AP.
The downlink (i.e., forward link) is the communication link from a given access point 110 to the respectively serviced access terminal 120, and the uplink (i.e., reverse link) is the communication link from one of access terminals 120 to the respective access point 110. In the illustrated example, AP 110a is associated with ATs 120a and 120b; AP110b is associated with ATs 120c and 120d; AP 110c is associated with AT 120e; and AP 110d is associated with AT 120f. It is understood that an AT may also communicate peer-to-peer with another ATs. A system controller 130 couples to and provides coordination and control for the APs. Additionally APs 110 can communicate with other devices coupled to a backbone network (not shown).
In environment 100, each of APs 110a, 110b, and 110c are configured for wireless communication with one another. That is, AP 110d communicates directly with AP 110c. Communication between AP 110d and 110a is facilitated via an intervening node, i.e., AP 100c. In this configuration, each of APs 110a, 110b, and 110c, are “one-hop” neighbors, i.e., they are in direct communication, without intervening network nodes. However, access point 110d is a “two-hop” neighbor of APs 110a, and 110b, since any transmissions sent/received at AP 110d must pass through an intervening node, i.e., AP 110c.
In practice, communication amongst ATs 120 is facilitated by wireless connectivity between APs 110. To reduce the occurrence of wireless collisions, each AP 110 is assigned to an initial channel that corresponds with a specific frequency band in which the AP operates. As discussed above, the likelihood of packet collisions increases if two proximately positioned APs share similar or adjacent channels.
To ensure that channel assignments of adjacent APs afford a high channel quality, a channel reassignment process of the subject technology can be utilized in which channel assignments are made based on a hierarchy of node groupings. In some implementations, channel assignments are made one an AP-by-AP basis, and subsequently updated, for example, by calculating channel assignments of all one-hop neighbors, and the two-hop neighbors, etc.
AP channel calculations are performed in a hierarchy of “layers”, in which channel assignments are determined for each node (or group of nodes) in a selected layer, and then re-iterated for each lower layer in the hierarchy. After channel calculations are performed for the selected layer (and iterated for all layers beneath the selected layer), channel calculations can then be made for the next layer up the hierarchy. By way of example, channel calculations begin at the lowest layer in the channel hierarchy (i.e., “layer 0”), in which channel determinations are made for each individual node. Because layer 0 represents the lowest layer in the channel hierarchy, the layer 0 calculation ends after each individual AP channel assignment has been made. Channel calculations are subsequently made for higher layers in the channel hierarchy, that is, the calculation process proceeds up to “layer 1.”
In the layer 1 calculation, channel determinations are performed for groups of nodes, for example, all one-hop neighbors of a selected node. After, one-hop group channel assignments have been made, layer 0 calculations are re-iterated, and the layer 1 calculation is complete. The channel calculation algorithm then proceeds up the hierarchy, e.g., to “layer 2” in which channel determinations are performed for groups of nodes comprising all two-hop neighbors of a selected node, followed by layer 1 calculations, and ending with layer 0 calculations. Those of skill in the art will recognize that there are no inherent limitations to the size of groups for which channel calculations can be performed. That is, there are no inherent limitations to the number of layers in a channel hierarchy, and channel calculations could be performed at a hierarchical layer in which a selected group includes every node in the network, without departing from the scope of the technology.
Additionally, in some aspects, the periodicity for computing channel assignments for a particular layer can vary on a layer-by-layer basis. By way of non-limiting example, layer 0 calculations may be performed with a periodicity of p0. Layer 1 calculations (including re-calculations of layer 0) may be performed with a periodicity of p1; and layer 2 calculations (including re-calculations for layer 1 and layer 0) performed with a periodicity of p2, where p0, p1, and p2 are all configured for different time values, such as, 15 minutes, 3 hours, and 1 day, respectively.
As illustrated, channel determinations for each of APs 210a, 210b, 210c, and 210d are independently determined, without regard to joint channel switching. For example, a channel is selected for AP 210a, based on frequency availability and other quality metrics with respect to AP 210a, but without consideration for the potential of switching to any currently assigned channels for APs 210b, 210c, or 210d. Similarly independent channel determinations are made for each of APs 210b, 210c, and 210d. Once new channel determinations have been made for each AP in the network, all layer 0 channel assignments are complete, and the process can move up to layer 1.
Using the layer 0 calculation illustrated in
By way of example, suppose that APs 210a, AP 210b, and AP 210c are assigned to channels 2, 4, and 6, respectively. However, channel calculations indicate that the optimal assignment would be to move APs 210a, 210b, and 210c to channels 6, 4, and 2. Based on the channel availability created by concurrent channel swapping, APs 210a, 210b, and 210c can be reassigned to channels 6, 4, and 2, without any conflict. That is, by taking consideration of each channel change jointly (as a layer 1 group), channel re-assignments can be made for each of APs 210a, 210b, and 210c, thereby optimizing the selected group.
Subsequently, any node that has not been re-assigned can be selected, i.e., AP 210d. In this example, AP 210 exists in a layer 1 (one-hop neighbor) group with AP 210b. However, since the channel with AP 210b has already been re-assigned in layer 1, channel reassignment calculations are only performed for AP 210d. Once the channel assignments are determined for one-hop groups across the network, layer 0 calculations can be re-iterated, as discussed above, completing channel computation for layer 1 of the hierarchy. Subsequently, layer 2 calculations can be performed, for example, in which channel calculations are performed for groups of two-hop neighbors, followed by re-calculation of layer 1 assignments, and terminating with re-calculation of layer 0 assignments, respectively.
The channel calculation process for any hierarchical layer can begin with the selection of a random network node. That is, multiple rounds of channel assignments can be simulated, e.g., by computing assignments for different groups through the selection of different initial nodes. In such approaches, different network-wide channel assignment solutions can be computed and compared without actual deployment, for example, to determine the optimal network-wide channel configuration. Once the optimal configuration is determined, changes can be physically deployed to the network.
Any number of higher-layer channel calculations can be performed, e.g. considering three-hop, four-hop, or five-hop neighbors, etc., without departing from the technology. It is understood that, given enough computing resources, channel assignments for each node in entire network may be computed.
As would be understood by those of skill in the art, performance for any given node, groups of nodes, or network-wide performance, can depend on virtually any measurable network parameters. As such, channel performance calculations may vary depending on the desired implementation.
In some aspects, a utility function can be used to estimate performance on a channel c with channel width cw using the relationship of equation (1):
where channel_metric(c,b)=airtime(c,b)×capacity(c,b), and where airtime (c,b) represents an estimated proportion of airtime th expected for a given node (AP) on a particular channel c with channel width b, and is calculated based on the channel utilization of the neighboring APs. In this example, capacity(c,b) can be estimated using the channel quality, non-wifi interference, and/or channel width, where load(b) is the channel usage, and is proportional to the number of associated clients with maximum channel width b. In the relationship provided by equation (1), NodeP can have two important properties: (i) if channel c is heavily utilized or there are many neighboring APs on the same channel, NodeP will quickly approach 0; and (ii) if associated clients do not support wider channel width, NodeP will not increase for wider channels. In such instances, an AP can avoid adjusting its channel width according to the client's capability.
Additionally, in some aspects, overall network performance (NetP) can be calculated using the relationship of equation (2):
where NetP is the product of channel_metric weighted proportionally by load. In some implementations, this performance function can provide several benefits. First, per-client usage fairness can be maintained. The metric prefers to assign wider channels to APs with higher client density and usage. Second, single node failure is avoided. If spectrum coverage or total network throughput is the performance function, it is easy to have a high metric despite assigning poor channels to several nodes. In contrast, NetP will approach 0 as a single NodeP approaches 0.
In step 304, a first AP is selected from among the identified APs in step 302. A channel quality for the currently assigned channel (i.e., the initial channel assignment) of the first AP is determined. Channel quality determinations can be based on essentially any measure or parameter that can be used to infer wireless signal quality at the AP. By way of non-limiting example, channel quality can be determined based on one or more of: received signal strength, bit or frame error rate, and/or packet loss metrics, etc.
In step 306 a first new channel for the first AP is selected, based on the channel quality determination made in step 304. In some instances, the determined channel quality for the initial channel assignment (step 304) may be compared to channel quality metrics computed for other available channels in the wireless medium. Therefore, the first new channel selected can be based on a comparison of quality metrics between current and available channel options.
Channel selection can also take into consideration a channel change penalty, such that different channels with equal, or only incrementally better quality metrics may not be preferred over a current channel assignment. Channel change penalties can prevent channel reassignment loops, for example, whereby AP channel assignments bounce between channels of comparable quality. In some aspects, channel change penalties can be function of various network parameters. For example, channel change penalties may be a function of a number of connected client nodes, or bandwidth of active traffic flows, etc.
In step 308, a second AP is selected, and a channel quality for the initial channel assignment for the second AP is determined. Similar to the process described above with respect to step 304, channel quality for the initial channel assignment associated with the second AP can be based on one or more metrics from which a received signal quality at the second AP is inferred.
In step 310, a second new channel for the second AP is selected based on the channel quality for the initial channel assignment of the second AP. As discussed above with respect to
In step 316, a channel quality is determined for the first new channel associated with the first AP, and each of the one-hop neighbors. That is, channel quality assessment at the layer 1 level are made with respect to groups of APs, which include a selected AP and each of this immediate network neighbors.
By considering channel re-selection for groups of nodes, as opposed to a node-by-node basis, improved channel assignments can be made with respect to layer 0 calculations. For example, layer 1 calculations compute channel re-assignments that can depend on channel swapping between currently assigned channels for different APs. As such, channel quality determinations can be made with respect to channels that would have been deemed unavailable at the layer 0 calculation.
In step 318, a second new channel for the first AP is selected based on the channel quality for the first new channel associated with the first AP and the channel quality of the respective channel assignment of each of the single hop neighbors. Because channel selection can be performed without regard to channel occupancy of neighboring devices in the group (i.e., the group consisting of the first AP and all one-hop neighbors), better channel selections can be made for benefit of the entire group.
By way of further example, if a first AP is assigned to channel 6, and a second AP is assigned to channel 8, then channel calculations made only for the first AP would exclude channel 8, which is already assigned. Conversely, channel calculations made only for the second AP would exclude channel 6, which is also assigned. However, at the layer 1 calculation level, by performing channel selections that optimize channel quality for all nodes in the group, better channel selections can be made at the network level.
Layer 1 calculations, as described with respect to steps 312-318, can be iterated until all APs in the network have been re-assigned. It is understood that any APs that share one-hop group membership with multiple nodes in the network may be re-assigned once at the layer 1 calculation level. That is, APs are not given multiple channel re-assignments on any given calculation layer. Once all channel assignments have been made for one-hop neighbor groups across the network, layer 0 calculations can be re-iterated, e.g., as described in steps 302-310, discussed in reference to
It is understood that any number of additional higher layer calculations can be performed, without departing from the scope of the technology. For example, selection of a particular AP and all of its two-hop network neighbors can be performed in a layer 2 calculation. Similarly, selection of an AP and its three-hop network neighbors can be performed in a layer 3 calculation. Depending on implementation and the availability of computing resources, channel calculation and selection may be performed for an entire network, i.e., all wireless nodes.
Additionally, as discussed above, multiple iterations of channel assignment calculations may be performed at each hierarchical level, without pushing the physical channel assignments to the network. That is, different channel assignment configurations can be simulated and compared to determine optimal AP channel assignment associations before network changes are deployed.
Performing channel calculations on a hierarchical basis vastly reduces the computational difficulty of the channel selection process and enables channel re-assignment to be performed more quickly and frequently, while also providing assignments that optimize frequency utilization at a network (global) level.
Interfaces 468 can be provided as wireless interface cards (sometimes referred to as “network interface cards” (NICs) or “line cards”). Generally, they control the sending and receiving of data packets over a wireless network and sometimes support other peripherals used with device 410. Among the interfaces that may be provided are Ethernet interfaces, frame relay interfaces, cable interfaces, Digital Subscriber Line (DSL) interfaces, token ring interfaces, and the like. In addition, various very high-speed interfaces can be provided such as fast token ring interfaces, wireless interfaces, Ethernet interfaces, Gigabit Ethernet interfaces, Asynchronous Transfer Mode (ATM) interfaces, High Speed Serial Interfaces (HSSIs), Point of Sale (POS) interfaces, Fiber Distributed Data Interface (FDDIs), and the like. Generally, these interfaces can include ports appropriate for communication with the appropriate media. In some cases, they may also include an independent processor and, in some instances, volatile RAM. The independent processors may control such communications intensive tasks as packet switching, media control and management. By providing separate processors for the communications intensive tasks, these interfaces allow the master microprocessor 462 to efficiently perform routing computations, network diagnostics, security functions, etc.
Although the system shown in
Regardless of the network device's configuration, it may employ one or more non-transitory memories or memory modules (including memory 461) configured to store program instructions for general-purpose network operations and mechanisms necessary to implement one or more steps of a service chain auto-tuning process of the subject technology.
For example, memory 461 can include a non-transitory computer-readable medium that includes instructions for causing CPU 462 to execute operations for identifying a plurality of wireless access points (APs) in the wireless network, each of the wireless APs being associated with an initial channel assignment, selecting a first AP from among the plurality of wireless APs in the wireless network, determining a channel quality for the initial channel assignment associated with the first AP, and selecting a first new channel for the first AP based on the channel quality for the initial channel assignment associated with the first AP. In some aspect, CPU 462 can further be configured to execute operations including selecting a second AP from among the plurality of wireless APs in the wireless network, determining a channel quality for the initial channel assignment associated with the second AP, and selecting a first new channel for the second AP based on the channel quality for the initial channel assignment associated with the second AP.
As discussed above, CPU 462 can also be configured to perform higher layer channel assignment calculations. For example, CPU 462 can be configured to execute operations including selecting the first AP from among the plurality of wireless APs in the wireless network, identifying one or more one-hop neighbors of the first AP, wherein each of the one or more one-hop neighbors is directly connected to the first AP in the wireless network, determining a channel quality for the first new channel associated with the first AP, determining a channel quality for a respective channel assignment of each of the one-hop neighbors of the first AP, and selecting a second new channel for the first AP based on the channel quality for the first new channel associated with the first AP, and the channel quality of the respective channel assignment of each of the one or more one-hop neighbors.
It is understood that any specific order or hierarchy of steps in the processes disclosed is an illustration of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged, or that only a portion of the illustrated steps be performed. Some of the steps may be performed simultaneously. For example, in certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but are to be accorded the full scope consistent with the language claims, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.”
A phrase such as an “aspect” does not imply that such aspect is essential to the subject technology or that such aspect applies to all configurations of the subject technology. A disclosure relating to an aspect may apply to all configurations, or one or more configurations. A phrase such as an aspect may refer to one or more aspects and vice versa. A phrase such as a “configuration” does not imply that such configuration is essential to the subject technology or that such configuration applies to all configurations of the subject technology. A disclosure relating to a configuration may apply to all configurations, or one or more configurations. A phrase such as a configuration may refer to one or more configurations and vice versa.
The word “exemplary” is used herein to mean “serving as an example or illustration.” Any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs.
This application claims the benefit of U.S. Application No. 62/507,473 filed May 17, 2017, entitled “HIERARCHAL CHANNEL ASSIGNMENT IN WIRELESS NETWORKS”, which is incorporated by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
4236068 | Walton | Nov 1980 | A |
5642303 | Small et al. | Jun 1997 | A |
5751223 | Turner | May 1998 | A |
6812824 | Goldinger et al. | Nov 2004 | B1 |
D552603 | Tierney | Oct 2007 | S |
7573862 | Chambers et al. | Aug 2009 | B2 |
D637569 | Desai et al. | May 2011 | S |
7975262 | Cozmei | Jul 2011 | B2 |
8010079 | Mia et al. | Aug 2011 | B2 |
8102814 | Rahman et al. | Jan 2012 | B2 |
8260320 | Herz | Sep 2012 | B2 |
8284748 | Borghei | Oct 2012 | B2 |
8300594 | Bernier et al. | Oct 2012 | B1 |
8325626 | Tóth et al. | Dec 2012 | B2 |
8396485 | Grainger et al. | Mar 2013 | B2 |
8446899 | Lei et al. | May 2013 | B2 |
8458184 | Dorogusker et al. | Jun 2013 | B2 |
D691636 | Bunton | Oct 2013 | S |
8549638 | Aziz | Oct 2013 | B2 |
8644301 | Tamhankar et al. | Feb 2014 | B2 |
8650279 | Mehta et al. | Feb 2014 | B2 |
8669902 | Pandey et al. | Mar 2014 | B2 |
8676182 | Bell et al. | Mar 2014 | B2 |
8682279 | Rudolf et al. | Mar 2014 | B2 |
8693367 | Chowdhury et al. | Apr 2014 | B2 |
8718644 | Thomas et al. | May 2014 | B2 |
8768389 | Nenner et al. | Jul 2014 | B2 |
8849283 | Rudolf et al. | Sep 2014 | B2 |
8909698 | Parmar et al. | Dec 2014 | B2 |
8958318 | Hastwell et al. | Feb 2015 | B1 |
9060352 | Chan et al. | Jun 2015 | B2 |
9130859 | Knappe | Sep 2015 | B1 |
9173084 | Foskett | Oct 2015 | B1 |
9173158 | Varma | Oct 2015 | B2 |
D744464 | Snyder et al. | Dec 2015 | S |
D757424 | Phillips et al. | May 2016 | S |
D759639 | Moon et al. | Jun 2016 | S |
9389992 | Gataullin et al. | Jul 2016 | B2 |
9426305 | De Foy et al. | Aug 2016 | B2 |
D767548 | Snyder et al. | Sep 2016 | S |
D776634 | Lee et al. | Jan 2017 | S |
9544337 | Eswara et al. | Jan 2017 | B2 |
9609504 | Karlqvist et al. | Mar 2017 | B2 |
9642167 | Snyder et al. | May 2017 | B1 |
9654344 | Chan et al. | May 2017 | B2 |
9713114 | Yu | Jul 2017 | B2 |
9772927 | Gounares et al. | Sep 2017 | B2 |
9820105 | Snyder et al. | Nov 2017 | B2 |
D804450 | Speil et al. | Dec 2017 | S |
9858559 | Raleigh et al. | Jan 2018 | B2 |
9860151 | Ganichev et al. | Jan 2018 | B2 |
9933224 | Dumitriu et al. | Feb 2018 | B2 |
9923780 | Rao et al. | Mar 2018 | B2 |
9967906 | Verkaik et al. | May 2018 | B2 |
9980220 | Snyder et al. | May 2018 | B2 |
9985837 | Rao et al. | May 2018 | B2 |
20030087645 | Kim et al. | May 2003 | A1 |
20030116634 | Tanaka | Jun 2003 | A1 |
20040203572 | Aerrabotu et al. | Oct 2004 | A1 |
20050090225 | Muehleisen et al. | Apr 2005 | A1 |
20050169193 | Black et al. | Aug 2005 | A1 |
20050186904 | Kowalski et al. | Aug 2005 | A1 |
20060009226 | Vicharelli | Jan 2006 | A1 |
20060022815 | Fischer et al. | Feb 2006 | A1 |
20060030290 | Rudolf et al. | Feb 2006 | A1 |
20060092964 | Park et al. | May 2006 | A1 |
20060126882 | Deng et al. | Jun 2006 | A1 |
20060187866 | Werb et al. | Aug 2006 | A1 |
20070037605 | Logan | Feb 2007 | A1 |
20070239854 | Janakiraman et al. | Oct 2007 | A1 |
20080037715 | Prozeniuk et al. | Feb 2008 | A1 |
20080084888 | Yadav et al. | Apr 2008 | A1 |
20080101381 | Sun et al. | May 2008 | A1 |
20080163207 | Reumann et al. | Jul 2008 | A1 |
20080233969 | Mergen | Sep 2008 | A1 |
20090086706 | Huang | Apr 2009 | A1 |
20090129389 | Halna DeFretay et al. | May 2009 | A1 |
20090203370 | Giles et al. | Aug 2009 | A1 |
20090232026 | Lu | Sep 2009 | A1 |
20090282048 | Ransom et al. | Nov 2009 | A1 |
20090298511 | Paulson | Dec 2009 | A1 |
20090307485 | Weniger et al. | Dec 2009 | A1 |
20100039280 | Holm et al. | Feb 2010 | A1 |
20100097969 | De Kimpe et al. | Apr 2010 | A1 |
20100301992 | Chandra | Dec 2010 | A1 |
20100304678 | Chandra | Dec 2010 | A1 |
20110051677 | Jetcheva | Mar 2011 | A1 |
20110087799 | Padhye et al. | Apr 2011 | A1 |
20110142053 | Van Der Merwe et al. | Jun 2011 | A1 |
20110182295 | Singh et al. | Jul 2011 | A1 |
20110194553 | Sahin et al. | Aug 2011 | A1 |
20110228779 | Goergen | Sep 2011 | A1 |
20120023552 | Brown et al. | Jan 2012 | A1 |
20120044905 | Kim | Feb 2012 | A1 |
20120054367 | Ramakrishnan et al. | Mar 2012 | A1 |
20120088476 | Greenfield | Apr 2012 | A1 |
20120115512 | Grainger et al. | May 2012 | A1 |
20120157126 | Rekimoto | Jun 2012 | A1 |
20120167207 | Beckley et al. | Jun 2012 | A1 |
20120182147 | Forster | Jul 2012 | A1 |
20120311127 | Kandula et al. | Dec 2012 | A1 |
20120324035 | Cantu et al. | Dec 2012 | A1 |
20130029685 | Moshfeghi | Jan 2013 | A1 |
20130039391 | Skarp | Feb 2013 | A1 |
20130057435 | Kim | Mar 2013 | A1 |
20130077612 | Khorami | Mar 2013 | A1 |
20130088983 | Pragada et al. | Apr 2013 | A1 |
20130107853 | Pettus et al. | May 2013 | A1 |
20130108263 | Srinivas et al. | May 2013 | A1 |
20130115916 | Herz | May 2013 | A1 |
20130145008 | Kannan et al. | Jun 2013 | A1 |
20130155906 | Nachum et al. | Jun 2013 | A1 |
20130191567 | Rofougaran et al. | Jul 2013 | A1 |
20130203445 | Grainger et al. | Aug 2013 | A1 |
20130217332 | Altman et al. | Aug 2013 | A1 |
20130232433 | Krajec et al. | Sep 2013 | A1 |
20130273938 | Ng et al. | Oct 2013 | A1 |
20130317944 | Huang et al. | Nov 2013 | A1 |
20130322438 | Gospodarek et al. | Dec 2013 | A1 |
20130343198 | Chhabra et al. | Dec 2013 | A1 |
20130347103 | Veteikis et al. | Dec 2013 | A1 |
20140007089 | Bosch et al. | Jan 2014 | A1 |
20140016926 | Soto et al. | Jan 2014 | A1 |
20140025770 | Warfield et al. | Jan 2014 | A1 |
20140052508 | Pandey et al. | Feb 2014 | A1 |
20140059655 | Beckley et al. | Feb 2014 | A1 |
20140087693 | Walby et al. | Mar 2014 | A1 |
20140105213 | A K et al. | Apr 2014 | A1 |
20140118113 | Kaushik et al. | May 2014 | A1 |
20140148196 | Bassan-Eskenazi et al. | May 2014 | A1 |
20140179352 | V.M. et al. | Jun 2014 | A1 |
20140191868 | Ortiz et al. | Jul 2014 | A1 |
20140198808 | Zhou | Jul 2014 | A1 |
20140233460 | Pettus et al. | Aug 2014 | A1 |
20140269321 | Kamble et al. | Sep 2014 | A1 |
20140302869 | Rosenbaum et al. | Oct 2014 | A1 |
20140337824 | St. John et al. | Nov 2014 | A1 |
20140341568 | Zhang et al. | Nov 2014 | A1 |
20150016286 | Ganichev et al. | Jan 2015 | A1 |
20150016469 | Ganichev et al. | Jan 2015 | A1 |
20150030024 | Venkataswami et al. | Jan 2015 | A1 |
20150043581 | Devireddy et al. | Feb 2015 | A1 |
20150063166 | Sif et al. | Mar 2015 | A1 |
20150065161 | Ganesh et al. | Mar 2015 | A1 |
20150087330 | Prechner et al. | Mar 2015 | A1 |
20150103818 | Kuhn et al. | Apr 2015 | A1 |
20150163192 | Jain et al. | Jun 2015 | A1 |
20150172391 | Kasslin et al. | Jun 2015 | A1 |
20150223337 | Steinmacher-Burow | Aug 2015 | A1 |
20150256972 | Markhovsky et al. | Sep 2015 | A1 |
20150264519 | Mirzaei et al. | Sep 2015 | A1 |
20150280827 | Adiletta et al. | Oct 2015 | A1 |
20150288410 | Adiletta et al. | Oct 2015 | A1 |
20150289147 | Lou | Oct 2015 | A1 |
20150326704 | Ko et al. | Nov 2015 | A1 |
20150341939 | Sharma et al. | Nov 2015 | A1 |
20150358777 | Gupta | Dec 2015 | A1 |
20150362581 | Friedman et al. | Dec 2015 | A1 |
20160007315 | Lundgreen et al. | Jan 2016 | A1 |
20160044627 | Aggarwal et al. | Feb 2016 | A1 |
20160099847 | Melander et al. | Apr 2016 | A1 |
20160105408 | Cooper et al. | Apr 2016 | A1 |
20160127875 | Zampini, II | May 2016 | A1 |
20160146495 | Malve et al. | May 2016 | A1 |
20160344641 | Javidi et al. | Nov 2016 | A1 |
20170026974 | Dey et al. | Jan 2017 | A1 |
20170214551 | Chan et al. | Jul 2017 | A1 |
20180069311 | Pallas et al. | Mar 2018 | A1 |
20180084389 | Snyder et al. | Mar 2018 | A1 |
Number | Date | Country |
---|---|---|
WO-2009094264 | Jul 2009 | WO |
WO 2013020126 | Feb 2013 | WO |
WO 2014098556 | Jun 2014 | WO |
WO 2018009340 | Jan 2018 | WO |
Entry |
---|
“I Love WiFi, The difference between L2 and L3 Roaming Events,” Apr. 1, 2010, 6 pages. |
Carter, Steve Sr., “E911 VoIP Essentials for Enterprise Deployments,” XO Communications, LLC, 2012, 9 pages. |
Chalise, Batu K., et al., “MIMO Relaying for Multiaccess Communication in Cellular Networks,” Sensor Array and MultiChannel Signal Processing Workshop, 2008, Sam 2008, 5th IEEE, Jul. 21, 2008, pp. 146-150. |
Cisco Systems, Inc., “Wi-FI Location-Based Services 4.1 Design Guide,” May 20, 2008, 206 pages. |
Cui, Wenzhi et al., “DiFS: Distributed Flow Scheduling for Data Center Networks,” Nanjing University, China, Jul. 28, 2013, 10 pages. |
Galvan T., Carlos E., et al., “Wifi bluetooth based combined positioning algorithm,” International Meeting of Electrical Engineering Research ENIINVIE 2012, Procedia Engineering 35 (2012 ), pp. 101-108. |
Gesbert, David, “Advances in Multiuser MIMO Systems (Tutorial Part II) Emerging Topics in Multiuser MIMO Networks,” IEEE PIMRC Conference, Sep. 2007, 107 pages. |
Halperin, Daniel, et al., “Augmenting Data Center Networks with Multi-Gigabit Wireless Links,” Aug. 15-19, 2011, SIGCOMM'11, ACM 978-1-4503-0797-0/11/08, pp. 38-49. |
Ji, Philip N., et al., “Demonstration of High-Speed MIMO OFDM Flexible Bandwidth Data Center Network,” Optical Society of America, 2012, 2 pages. |
Kandula, Srikanth, et al., “Flyways to De-Congest Data Center Networks,” Microsoft Research, Oct. 23, 2009, 6 pages. |
Katayama, Y. et al., “MIMO Link Design Strategy for Wireless Data Center Applications,” IEEE Wireless Communications and Networking Conference: Services, Applications, and Business, 2012, 5 pages. |
Leary, Jonathan, et al., “Wireless LAN Fundamentals: Mobility,” Jan. 9, 2004, Cisco Press, 15 pages. |
Network Heresy, “NVGRE, VXLAN and What Microsoft is Doing Right,” Oct. 3, 2011, 5 pages. |
Savvides, Andreas, et al., “Dynamic Fine-Grained Localization in Ad-Hoc Networks of Sensors”, Proceeding MobiCom '01 Proceedings of the 7th annual international conference on Mobile computing and networking, Jul. 2001, pp. 166-179. |
Afolabi, Ibrahim, et al., “Network Slicing & Softwarization: A Survey on Principles, Enabling Technologies & Solutions,” Mar. 21, 2018, pp. 1-24. |
Antonioli, Roberto, et al., “Dual Connectivity for LTE-NR Cellular Networks,” Research Gate, Sep. 3-6, 2017, pp. 171-175. |
Cisco ASR 5x00 Mobility Management Entity Administration Guide, Version 15.0, Last updated Jun. 13, 2014, Cisco, 1-266. |
Cox, Jacob H. Jr., et al., “Advancing Software-Defined Networks: A Survey,” IEEE, Oct. 12, 2017, pp. 25487-25526. |
Saraiva de Sousa, Nathan F., et al., “Network Service Orchestration: A Survey,” IEEE Communications Surveys & Tutorials, Mar. 23, 2018, pp. 1-30. |
Geller, Michael, et al. , “5G Security Innovation with Cisco,” Whitepaper Cisco Public, Jun. 8, 2018, pp. 1-29. |
Ventre, Pier Luigi, et al., “Performance Evaluation and Tuning of Virtual Infrastructure Managers for (Micro) Virtual Network Functions,” ieee.org, Nov. 7-10, 2016, pp. 1-7. |
International Search Report and Written Opinion from the International Searching Authority, dated Jul. 18, 2018, 10 pages, for the corresponding International Patent Application No. PCT/US18/32908. |
Number | Date | Country | |
---|---|---|---|
20180338315 A1 | Nov 2018 | US |
Number | Date | Country | |
---|---|---|---|
62507473 | May 2017 | US |