A biased random-key genetic algorithm for OSPF and DEFT routing to minimize network congestion

被引:22
作者
Reis, Roger [1 ]
Ritt, Marcus [1 ]
Buriol, Luciana S. [1 ]
Resende, Mauricio G. C. [2 ]
机构
[1] Univ Fed Rio Grande do Sul, Inst Informat, Porto Alegre, RS, Brazil
[2] AT&T Labs Res, Algorithms & Optimizat Res Dept, Florham Pk, NJ 07932 USA
关键词
networks; networking; telecommunication networks; routing; genetic algorithm; biased random-key genetic algorithm; local search; metaheuristics; OPTIMIZATION; DESIGN;
D O I
10.1111/j.1475-3995.2010.00771.x
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Interior gateway routing protocols like Open Shortest Path First (OSPF) and Distributed Exponentially Weighted Flow Splitting (DEFT) send flow through forward links toward the destination node. OSPF routes only on shortest-weight paths, whereas DEFT sends flow on all forward links, but with an exponential penalty on longer paths. Finding suitable weights for these protocols is known as the weight setting problem (WSP). In this paper, we present a biased random-key genetic algorithm for WSP using both protocols. The algorithm uses dynamic flow and dynamic shortest path computations. We report computational experiments that show that DEFT achieves less network congestion when compared with OSPF, while, however, yielding larger delays.
引用
收藏
页码:401 / 423
页数:23
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