A Measurement Study of Multiplicative Overhead Effects in Wireless Networks

Jcamp,; Mancuso, Vincenzo; Ogurewitz,; Ewknightly,

doi:10.1109/infocom.2007.24

Cited by 8 publications

(12 citation statements)

References 11 publications

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“…In particular, it is unclear what role citywide WiFi deployments play from a user's perspective, independent of any particular network agreement or charging policy. A great deal of academic research has focused on developing and improving wireless mesh protocols, and studies of deployed wireless networks have recently begun appearing in the literature [3], [7], [10], [11]. These studies focus almost exclusively on the operation and effectiveness of the mesh backbone, however; to the best of our knowledge, none have yet to report upon how clients use a metropolitan network.…”

Section: Introductionmentioning

confidence: 99%

Usage Patterns in an Urban WiFi Network

Afanasyev

Chen

Voelker

et al. 2010

IEEE/ACM Trans. Networking

107

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Abstract-While WiFi was initially designed as a local-area access network, mesh networking technologies have led to increasingly expansive deployments of WiFi networks. In urban environments, the WiFi mesh frequently supplements a number of existing access technologies, including wired broadband networks, 3G cellular, and commercial WiFi hotspots. It is an open question what role city-wide WiFi deployments play in the increasingly diverse access network spectrum. We study the usage of the Google WiFi network deployed in Mountain View, California, and find that usage naturally falls into three classes, based almost entirely on client device type, which we divide into traditional laptop users, fixed-location access devices, and PDA-like smartphone devices. Moreover, each of these classes of use has significant geographic locality, following the distribution of residential, commercial, and transportation areas of the city. When comparing the network usage of each device class, we find a diverse set of mobility patterns that map well to the archetypal use cases for traditional access technologies. To help place our results in context, we also provide key performance measurements of the mesh backbone and, where possible, compare them to those of previously studied urban mesh networks.

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Section: Introductionmentioning

confidence: 99%

Usage Patterns in an Urban WiFi Network

Afanasyev

Chen

Voelker

et al. 2010

IEEE/ACM Trans. Networking

107

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“…Second, the capture effect in our Atheros adapters is similar to that of the adapters in [28]. Third, like the TFA testbed [10], our Atheros adapters do not employ energy detection in the Clear Channel Assessment (CCA) mechanism. Instead, the channel is considered busy if the hardware is able to successfully decode the preamble and the PLCP header.…”

Section: 11 Wireless Mesh Testbedmentioning

confidence: 94%

“…Han et al [20] also studied the effect of PLC on 802.11 WLANs, but they did not address hidden nodes collisions. PLC has been widely observed in other 802.11 adapters [10,25,27,36], and even in sensor radio [38] and cellular systems [43].…”

Section: Related Workmentioning

confidence: 99%

Mitigating Unfairness Due to Physical Layer Capture in Practical 802.11 Mesh Networks

Wang

Leong

Ooi

2015

IEEE Trans. on Mobile Comput.

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Abstract-In this paper, we describe FairMesh, which is the first attempt at mitigating the unfairness arising from physical layer capture (PLC) in 802.11 mesh networks. In the presence of PLC, which is surprisingly common in practical mesh networks, existing state-ofart solutions either fail to correctly identify the sender that needs to be throttled or are too aggressive in reducing the sending rate. FairMesh is able to accurately detect unfairness quickly and employs a simple CW min adjustment algorithm to achieve approximate max-min fairness. Our key insight is that the nodes that cause an unfair situation to arise and can act to remedy it are often distinct from the ones that can accurately assess the degree of unfairness. To the best of our knowledge, we are the first to decouple the detection and assessment of unfairness from the remedial action. A key strength of our approach is its simplicity, which makes it amenable for deployment in practical 802.11 mesh networks to allow an arbitrary number of flows to operate concurrently without modifications to the 802.11 MAC. We show via simulation and with experiments on a 20-node outdoor 802.11 wireless mesh testbed that FairMesh has many desirable properties. First, it is fully distributed and has negligible control overhead. Second, it achieves approximate max-min fairness, and can be modified to support a different notion of fairness (e.g., proportional fairness). Third, it can handle multiple (more than two) competing links and can scale up to mesh networks with tens of nodes. Fourth, it remains efficient under high data rates and high loss rates. Finally, FairMesh interacts well with TCP and maintains good fairness when a multi-hop flow competes with a single-hop flow.Index Terms-802.11 mesh network, Physical layer capture, Fairness.

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“…A lot of research has been done in recent years about wireless mesh networks, including design aspects (routing, scalability, security [28,33,25,38,13,8,27,32,31,34,9]), deployment (urban, rural, centrally-, individually-, or un-planned [14,18,23,15]), measurements and analysis (topologies, performance, usage patterns, evolution, mobility [22,35,36,26,15,11,10,16,30,12,14,17,18,23]), as well as surveys of prior work and related aspects [37,19,24,29,20].…”

Section: Related Workmentioning

confidence: 99%

“…Pioneering work on the Roofnet testbed by Bicket and Aguayo [12,14] and on the TFA-Mesh in Houston TX by Camp [18,17] are analyzing the multi-hop performance of purely 802.11b based mesh networks. While the size of these networks are in the same order as the QMPSU network (37 and 18 nodes respectively and up to 69 nodes in QMPSU), the density of Roofnet with 344 edges and a median of 18 links per node is outstanding and a consequence of the unplanned deployment with only omni-directional antennas.…”

Section: Related Workmentioning

confidence: 99%

Experimental evaluation of a wireless community mesh network

Cerdà-Alabern

Neumann

Escrich

2013

Proceedings of the 16th ACM International Conference on Modeling, Analysis &Amp; Simulation of Wireless and Mobile Systems

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Nowadays there are inexpensive WiFi devices that have fostered the deployment of wireless communities. Well known routing protocols used in the Internet do not fit well to time varying characteristic of wireless networks. This has motivated an intensive research on routing protocols for wireless mesh networks. At this time there are a number of mature and stable implementations that are being deployed in production networks. In this paper we focus on the experimental evaluation of a production Wireless Mesh network being deployed in a testbed at Universitat Politècnica de Catalunya (UPC) and a quarter of the city of Barcelona, Spain. To our best knowledge, this is the first paper where a production community wireless network using 802.11an is analyzed.

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A Measurement Study of Multiplicative Overhead Effects in Wireless Networks

Cited by 8 publications

References 11 publications

Usage Patterns in an Urban WiFi Network

Usage Patterns in an Urban WiFi Network

Mitigating Unfairness Due to Physical Layer Capture in Practical 802.11 Mesh Networks

Experimental evaluation of a wireless community mesh network

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