Wireless Mesh Network Routing Under Uncertain Demands

DOI: 10.1007/978-1-84800-909-7_7


Traffic routing plays a critical role in determining the performance of a wireless mesh network. Recent research results usually
fall into two ends of the spectrum. On one end are the heuristic routing algorithms, which are highly adaptive to the dynamic
environments of wireless networks yet lack the analytical properties of how well the network performs globally. On the other
end are the optimal routing algorithms that are derived from the optimization problem formulation of mesh network routing.
They can usually claim analytical properties such as resource use optimality and throughput fairness. However, traffic demand
is usually implicitly assumed as static and known a priori in these problem formulations. In contrast, recent studies of wireless
network traces show that the traffic demand, even being aggregated at access points, is highly dynamic and hard to estimate.
Thus, to apply the optimization-based routing solution in practice, one must take into account the dynamic and uncertain nature
of wireless traffic demand. There are two basic approaches to address the traffic uncertainty in optimal mesh network routing
(1) predictive routing that infers the traffic demand with maximum possibility based in its history and optimizes the routing
strategy based on the predicted traffic demand and (2) oblivious routing that considers all the possible traffic demands and
selects the routing strategy where the worst-case network performance could be optimized. This chapter provides an overview
of the optimal routing strategies for wireless mesh networks with a focus on the above two strategies that explicitly consider
the traffic uncertainty. It also identifies the key factors that affect the performance of each routing strategy and provides
guidelines towards the strategy selection in mesh network routing under uncertain traffic demands.

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    ABSTRACT: This paper focuses on the concept of dynamic virtual optical networks (VONs) as a key enabling technology to support the requirements of the future Internet. To address the unpredictable nature of services and their characteristics, dynamic and on-demand planning and replanning of VONs is required. This paper proposes the use of novel modeling approaches to specifically consider the uncertain nature of traffic requests. In addition, it studies mechanisms to evaluate and minimize the impact of this uncertainty on the availability and efficiency of the virtual resources, considering at the same time requirements such as service resilience and security. The effect of periodic VON replanning is investigated and the relevant trade-offs are identified. Our modeling results show that taking into consideration the dynamic and uncertain nature of services provides significant benefits regarding the ability of the infrastructure to support these services and the associated resource efficiency.
    Journal of Optical Communications and Networking 10/2013; 5(10):A76-A85. DOI:10.1364/JOCN.5.000A76 · 2.06 Impact Factor


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