Abstract
Overloaded network devices are becoming an increasing problem especially in resource limited networks with the continuous and rapid increase of wireless devices and the huge volume of data generated. Admission and routing control policy at a network device can be used to balance the goals of maximizing throughput and ensuring sufficient resources for high priority flows. In this paper we formulate the admission and routing control problem of two types of flows where one has a higher priority than the other as a Markov decision problem. We characterize the optimal admission and routing policy, and show that it is a state-dependent threshold type policy. Furthermore, we conduct extensive numerical experiments to gain more insight into the behavior of the optimal policy under different systems’ parameters. While dynamic programming can be used to solve such problems, the large size of the state space makes it untractable and too resource intensive to run on wireless devices. Therefore, we propose a fast heuristic that exploits the structure of the optimal policy. We empirically show that the heuristic performs very well with an average reward deviation of 1.4% from the optimal while being orders of magnitude faster than the optimal policy. We further generalize the heuristic for the general case of a system with n () types of flows.
Highlights
Efficient resource utilization is a primary problem in resource constrained networks
We model node A as a two-class queueing system and assume that type-i, i ∈ {1, 2}, packets arrive at node A according to independent Poisson process with arrival rate λi ≥ 0, respectively
We prove by induction that if some structural properties of the discounted reward function wn are satisfied, these properties are satisfied for wn+1 and they hold for all n ≥ 0
Summary
Efficient resource utilization is a primary problem in resource constrained networks. By recognizing such flood of traffic, a node may either classify it as high priority traffic to identify the attacker and take the appropriate measures, or as low priority traffic and route it to another queue with a slower server This problem finds applications in computers and communication networks but in various other fields as well. Control (ARC) problem, that maximizes the network throughput by extending the life (the resources) of the efficient path and the number of flows serviced to the full extent.
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