Minimizing Congestion in General Networks
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Impact of interference on multi-hop wireless network performance
Proceedings of the 9th annual international conference on Mobile computing and networking
Centralized channel assignment and routing algorithms for multi-channel wireless mesh networks
ACM SIGMOBILE Mobile Computing and Communications Review
Routing in multi-radio, multi-hop wireless mesh networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Characterizing flows in large wireless data networks
Proceedings of the 10th annual international conference on Mobile computing and networking
End-to-end performance and fairness in multihop wireless backhaul networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Optimal oblivious routing in polynomial time
Journal of Computer and System Sciences - Special issue: STOC 2003
Algorithmic aspects of capacity in wireless networks
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
ExOR: opportunistic multi-hop routing for wireless networks
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Proceedings of the 11th annual international conference on Mobile computing and networking
Characterizing the capacity region in multi-radio multi-channel wireless mesh networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Optimal Resource Allocation in Wireless Ad Hoc Networks: A Price-Based Approach
IEEE Transactions on Mobile Computing
COPE: traffic engineering in dynamic networks
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Optimal routing for wireless mesh networks with dynamic traffic demand
Mobile Networks and Applications
The capacity of wireless networks
IEEE Transactions on Information Theory
The impact of topology in robust routing on wireless mesh networks
ACM SIGMOBILE Mobile Computing and Communications Review
A self-adaptive routing paradigm for wireless mesh networks based on reinforcement learning
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
A routing protocol suitable for backhaul access in wireless mesh networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Traffic routing is central to the utility and scalability of wireless mesh networks. Many recent routing studies have examined this issue, but generally they have assumed that the demand is constant and given in advance. On the contrary, wireless traffic studies have shown that demand is highly variable and difficult to predict, even when aggregated at access points. There are several approaches for handling volatile traffic. On one hand, traffic may be modeled in real-time with a dynamic routing based upon forecasted traffic demand. On the other hand, routing can be made with the focus towards maximally unbalanced demand, such that the worst-case performance is contained (known as oblivious routing). The first approach can perform competitively when traffic can be forecasted with accuracy, but may result in unbounded worst-case performance when forecasts go wrong. It is an open question how these two approaches would compare with each other in real networks and if possible at all, whether a benchmark could be defined to guide the selection of the appropriate routing strategy. To answer the above open question, this paper conducts a systematic comparison study of the two approaches based on the extensive simulation study over a variety of network scenarios with real-world traffic trace. It identifies the key factors of the network topology and traffic profile that affect the performance of each routing strategy. A series of metrics are examined with varying powers of forecasting whether predictive routing or oblivious routing will perform better. Following the guidelines defined by these metrics, we present an adaptive strategy which augments the performance of the predictive routing with the worst-case bound provided by the oblivious routing through adaptive selection of routing strategies based on the degree of traffic uncertainty.