Variable frame based Max-Weight algorithms for networks with switchover delay

This paper considers the scheduling problem for networks with interference constraints and switchover delays, where it takes a nonzero time to reconfigure each service schedule. Switchover delay occurs in many telecommunication applications such as satellite, optical or delay tolerant networks (DTNs...

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Bibliographic Details
Main Authors: Celik, Guner Dincer (Contributor), Borst, S. (Author), Whiting, P. (Author), Modiano, Eytan H. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2013-10-17T20:31:28Z.
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Summary:This paper considers the scheduling problem for networks with interference constraints and switchover delays, where it takes a nonzero time to reconfigure each service schedule. Switchover delay occurs in many telecommunication applications such as satellite, optical or delay tolerant networks (DTNs). Under zero switchover delay it is well known that the Max-Weight algorithm is throughput-optimal without requiring knowledge of the arrival rates. However, we show that this property of Max-Weight no longer holds when there is a nonzero switchover delay. We propose a class of variable frame based Max-Weight (VFMW) algorithms which employ the Max-Weight schedule corresponding to the beginning of the frame during an interval of duration dependent on the queue sizes. The VFMW algorithms dynamically adapt the frame sizes to the stochastic arrivals and provide throughput-optimality without requiring knowledge of the arrival rates. Numerical results regarding the application of the VFMW algorithms to DTN and optical networks demonstrate a good delay performance.
National Science Foundation (U.S.) (NSF grant CNS-0626781)
National Science Foundation (U.S.) (NSF grant CNS-0915988)
United States. Army Research Office (ARO Muri grant number W911NF-08-1-0238)