Article

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

Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA

IEEE/ACM Transactions on Networking (Impact Factor: 2.01). 07/2011; DOI: 10.1109/TNET.2010.2094204 Source: DBLP

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**ABSTRACT:**Motivated by the low-jitter requirements of streaming multi-media traffic, we focus on the development of scheduling strategies under fading conditions that not only maximize throughput performance but also provide regular inter-service times to users. Since the service regularity of the traffic is related to the higher-order statistics of the arrival process and the policy operation, it is highly challenging to characterize and analyze directly. We overcome this obstacle by introducing a new quantity, namely the time-since-last-service, which has a unique evolution different from a tradition queue. By combining it with the queue-length in the weight, we propose a novel maximum-weight type scheduling policy that is proven to be throughput-optimal and also provides provable service regularity guarantees. In particular, our algorithm can achieve a degree of service regularity within a constant factor of a fundamental lower bound we derive. This constant is independent of the higher-order statistics of the arrival process and can be as low as two. Our results, both analytical and numerical, exhibit significant service regularity improvements over the traditional throughput-optimal policies, which reveals the importance of incorporating the metric of time-since-last-service into the scheduling policy for providing regulated service.INFOCOM, 2013 Proceedings IEEE; 01/2013 - [Show abstract] [Hide abstract]

**ABSTRACT:**The control of large queueing networks is a notoriously difficult problem. Recently, an interesting new policy design framework for the control problem called h-MaxWeight has been proposed: h-MaxWeight is a natural generalization of the famous MaxWeight policy where instead of the quadratic any other surrogate value function can be applied. Stability of the policy is then achieved through a perturbation technique. However, stability crucially depends on parameter choice which has to be adapted in simulations. In this paper we use a different technique where the required perturbations can be directly implemented in the weight domain, which we call a scheduling field then. Specifically, we derive the theoretical arsenal that guarantees universal stability while still operating close to the underlying cost criterion. Simulation examples suggest that the new approach to policy synthesis can even provide significantly higher gains irrespective of any further assumptions on the network model or parameter choice.01/2013; - [Show abstract] [Hide abstract]

**ABSTRACT:**Motivated by the regular service requirements of video applications for improving Quality-of-Experience (QoE) of users, we consider the design of scheduling strategies in multi-hop wireless networks that not only maximize system throughput but also provide regular inter-service times for all links. Since the service regularity of links is related to the higher-order statistics of the arrival process and the policy operation, it is highly challenging to characterize and analyze directly. We overcome this obstacle by introducing a new quantity, namely the time-since-last-service (TSLS), which tracks the time since the last service. By combining it with the queue-length in the weight, we propose a novel maximum-weight type scheduling policy, called Regular Service Guarantee (RSG) Algorithm. The unique evolution of the TSLS counter poses significant challenges for the analysis of the RSG Algorithm. To tackle these challenges, we first propose a novel Lyapunov function to show the throughput optimality of the RSG Algorithm. Then, we prove that the RSG Algorithm can provide service regularity guarantees by using the Lyapunov-drift based analysis of the steady-state behavior of the stochastic processes. In particular, our algorithm can achieve a degree of service regularity within a factor of a fundamental lower bound we derive. This factor is a function of the system statistics and design parameters and can be as low as two in some special networks. Our results, both analytical and numerical, exhibit significant service regularity improvements over the traditional throughput-optimal policies, which reveals the importance of incorporating the metric of time-since-last-service into the scheduling policy for providing regulated service.05/2014;

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