Interference-Aware Joint Routing and TDMA Link Scheduling for Static Wireless Networks

Abstract

Abstract-We study efficient interference-aware joint routing and TDMA link scheduling for a multihop wireless network to maximize its throughput. Efficient link scheduling can greatly reduce the interference effect of close-by transmissions. Unlike the previous studies that often assume a unit disk graph model, we assume that different terminals could have different transmission ranges and different interference ranges. In our model, it is also possible that a communication link may not exist due to barriers or is not used by a predetermined routing protocol, while the transmission of a node always result interference to all non-intended receivers within its interference range.Using a mathematical formulation, we develop interference aware joint routing and synchronized TDMA link schedulings that optimize the networking throughput subject to various constraints. Our linear programming formulation will find a flow routing whose achieved throughput is at least a constant fraction of the optimum, and the achieved fairness is also a constant fraction of the requirement. Then, by assuming known link capacities and link traffic loads, we study link scheduling under the RTS/CTS interference model and the protocol interference model with fixed transmission power. For both models, we present both efficient centralized and distributed algorithms that use time slots within a constant factor of the optimum. We also present efficient distributed algorithms whose performances are still comparable with optimum, but with much less communications. We prove that the time-slots needed by our faster distributed algorithms are only at most O(min(log n, log ψ)) for RTS/CTS interference model and protocol interference model. Our theoretical results are corroborated by extensive simulation studies.

The impact of joint routing and link scheduling on the performance of wireless mesh networks

“…These works address the problem in an isolated fashion [2], [5], [9] or jointly with routing and topology/power control [3], [6], [8], [10]. According to the used methodology, existing works can be classified as follows: i) optimization by linear/integer programming [10]; ii) graphs coloring [6], [13] iii) approximation algorithms [2], [4]; iv) other (neural networks, genetic algorithms, etc.) [8], [11].…”

“…[8], [11]. Concerning the interference model, these studies use the protocol (or UDG) [6], [9] or physical (or SINR) models [2]. In most cases, algorithms/heuristics are centralized and require global topology knowledge and/or information about links' interference levels.…”

“…In most cases, algorithms/heuristics are centralized and require global topology knowledge and/or information about links' interference levels. However, some studies propose distributed algorithms [6], [13] based on graph coloring.…”

“…By modeling the wireless network as a graph, the scheduling problem can be translated into a graph coloring problem [6], [13], [14]. This coloring can be made both on edges (edgecoloring) and on vertices (vertex-coloring).…”

“…Those works show that the combined use of routing and link scheduling mechanisms provides a better performance than the independent use of them [3], [5], [6]. However, this joint optimization, named cross-layer, uses most of the time linear programming optimization approaches to obtain these results.…”