Transmission power and data rate aware routing on wireless networks
ABSTRACT Wireless networks can vary both the transmission power and modulation of links. Existing routing protocols do not take transmission power control (TPC) and modulation adaptation (also known as rate adaptation – RA) into account at the same time, even though the performance of wireless networks can be significantly improved when routing algorithms use link characteristics to build their routes. This article proposes and evaluates extensions to routing protocols to cope with TPC and RA. The enhancements can be applied to any link state or distance vector routing protocols. An evaluation considering node density, node mobility and link error show that TPC- and RA-aware routing algorithms improve the average latency and the end-to-end throughput, while consuming less energy than traditional protocols.
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ABSTRACT: Traffic in an infrastructure wireless mesh network is routed over multiple hops between clients and gateways, hence performance can be significantly reduced where links interfere with each other. In this paper we consider the problem of optimising link scheduling for wireless mesh networks, making a number of contributions. Adopting a protocol-based model, we introduce an integer programming approach for an optimised schedule using a time-slot model. This model compares favourably against previously published methods and we introduce a rapid heuristic approximation that can present near-optimal solutions in a fraction of the time. We show that taking into consideration the affect of varying data rates across individual links during different time slots can further enhance the throughput achieved. This decreases the local data rate on some links but concurrently reduces the interference range of the transmitted signal which increases spatial reuse across the network. We present efficient heuristics to rapidly find near-optimal solutions to an integer programming model of this problem and provide rigorous justification on benchmark problems.Computer Communications 09/2012; 35(16):2014–2024. · 1.08 Impact Factor