A genetic algorithm of high-throughput and low-jitter scheduling for input-queued switches

Authors:
Yaohui Jin;Jingjing Zhang;Weisheng Hu
Affiliations:
State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University, Shanghai, China;State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University, Shanghai, China;State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University, Shanghai, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Year:
2005

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Abstract

This paper presents a novel genetic algorithm (GA) for the scheduling problem of input-Queued switch, which can be applied in various networks besides the design of high speed routers. The scheduler should satisfy quality of service (QoS) constraints such as throughput and jitter. Solving the scheduling problem for the input-Queued switches can be divided into two steps: Firstly, decomposing the given rate matrix into a sum of permutation matrices with their corresponding weights; secondly, allocating the permutation matrices in one scheduling period based on their weights. It has been proved that scheduling problem in input-Queued switch with throughput and jitter constraints is NP-complete. The main contribution of this paper is a GA based algorithm to solve this NP-complete problem. We devise chromosome codes, fitness function, crossover and mutation operations for this specific problem. Experimental results show that our GA provides better performances in terms of throughput and jitter than a greedy heuristic.