On Combining Shortest-Path and Back-Pressure Routing Over Multihop Wireless Networks

Abstract

Abstract-Back-pressure based algorithms based on the algorithm by Tassiulas and Ephremides have recently received much attention for jointly routing and scheduling over multihop wireless networks. However a significant weakness of this approach has been in routing, because the traditional back-pressure algorithm explores and exploits all feasible paths between each source and destination. While this extensive exploration is essential in order to maintain stability when the network is heavily loaded, under light or moderate loads, packets may be sent over unnecessarily long routes and the algorithm could be very inefficient in terms of end-to-end delay and routing convergence times.This paper proposes new routing/scheduling back-pressure algorithms that not only guarantees network stability (throughput optimality), but also adaptively selects a set of optimal routes based on shortest-path information in order to minimize average path-lengths between each source and destination pair. Our results indicate that under the traditional back-pressure algorithm, the end-to-end packet delay first decreases and then increases as a function of the network load (arrival rate). This surprising low-load behavior is explained due to the fact that the traditional back-pressure algorithm exploits all paths (including very long ones) even when the traffic load is light. On the otherhand, the proposed algorithm adaptively selects a set of routes according to the traffic load so that long paths are used only when necessary, thus resulting in much smaller end-to-end packet delays as compared to the traditional back-pressure algorithm.

Autonomous Traffic Balancing Routing in Wireless Mesh Networks

“…9. ALFA-A and ALFA behave as GR under lightly-loaded cases, whereas BPR traverses relatively long paths, as reported in [11]. Because BPR exploits unnecessarily long paths due to large hop counts, including frequent route loops, it is very harmful to delay-sensitive applications.…”

“…However, it unnecessarily chooses long paths and degrades network performance by keeping old data packets. This problem manifests critically in lightly-or moderately-loaded cases [11]. On the other hand, conventional geographic routing is scalable with no flooding overhead, but it is vulnerable to avoiding congested hot spots due to its simple geographical routing metric.…”

Analyzing Backpressure routing interaction with TCP for Wireless Mesh Networks

“…The algorithm in fact explores and exploits all feasible paths between each source and destination. While this extensive exploration is essential in order to maintain stability when the network is heavily loaded (load balancing over the network), under light or moderate loads, packets may be sent over unnecessarily long routes, that may eventually contain loops, which leads to poor QoS performance especially in terms of end-to-end delay [10].…”

“…It used Neely's Lyapunov drift-plus-penalty theoretical framework to implement the algorithm for Wireless Sensor Networks (WSN). A new approach combining traffic-splitting and shortest-path is defined in [10]. The shortest path concept, is incorporated in the algorithm using the hop-queue length difference in the Backpressure term [3].…”

Spectrum and storage capacity management using network economics and optimization methods

“…This scheme constitutes a proactive end-to-end flow control mechanism which may degrade the data delivery capability of the network. Therefore, these algorithms are not delay-aware and there is much ongoing research aiming at their improvement [110], [13].…”