Self-management in chaotic wireless deployments

Abstract

Over the past few years, wireless networking technologies have made vast forays into our daily lives. Today, one can find 802.11 hardware and other personal wireless technology employed at homes, shopping malls, coffee shops and airports. Present-day wireless network deployments bear two important properties: they are unplanned, with most access points (APs) deployed by users in a spontaneous manner, resulting in highly variable AP densities; and they are unmanaged, since manually configuring and managing a wireless network is very complicated. We refer to such wireless deployments as being chaotic.In this paper, we present a study of the impact of interference in chaotic 802.11 deployments on end-client performance. First, using large-scale measurement data from several cities, we show that it is not uncommon to have tens of APs deployed in close proximity of each other. Moreover, most APs are not configured to minimize interference with their neighbors. We then perform trace-driven simulations to show that the performance of end-clients could suffer significantly in chaotic deployments. We argue that end-client experience could be significantly improved by making chaotic wireless networks self-managing. We design and evaluate automated power control and rate adaptation algorithms to minimize interference among neighboring APs, while ensuring robust end-client performance.

QoS provisioning for large-scale multi-ap WLANs

“…There have also been numerous efforts to mitigate the inter-cell interference problem, including channel assignment [17,28,34], power control (or carrier sense control) [8,26,36], and association control [9,10].…”

“…Proper management of transmission power reduces interference and thus improves the overall network performance. In [8], Akella et al presented a power-control and rate-selection (called PERF) algorithm. The PERF algorithm reduces the transmission power as much as possible without reducing the transmission rate, thus improving aggregate throughput.…”

“…In general, 802.11 WLAN deployments can be classified into two categories [8], depending on whether to be managed centrally or not: (i) centralized deployments and (ii) uncoordinated deployments (also referred to as 'chaotic' deployments [8]). In the former architecture, the entire network is observed and managed by a central control element.…”

Joint transmit power and physical carrier sensing adaptation based on loss differentiation for high density IEEE 802.11 WLAN

“…Muqattash et al [19] used an access window to allow for a series of RTS/CTS exchanges prior to data transmissions so that neighboring nodes can determine the optimal transmit power based on the information provided in the RTS and CTS packets to maximize spatial reuse. Akella et al [20] proposed a power control algorithm called PERF that reduces transmit power as long as the links between an AP and all its clints can maintain the highest datarate. However, most of the above TPC schemes (except [18] [20]) require additional hardware or signalling overhead.…”

Handover Incentives for WLANs with Overlapping Coverage

“…The main assumption of these scenarios is that two or more access points operate in the same channel. Indeed, it is common that there are more than three access points within the range of each other [2]. Hence, the three orthogonal channels available in 802.11b and 802.11g are not sufficient to assign orthogonal channels to different access points.…”