Traffic Grooming in Wavelength Routed Path Networks

Traffic Grooming;Complexity;Approximability

Huang, Shu ; Dr. Rudra Dutta, Committee Chair,Dr. G.N.Rouskas, Committee Member,Dr. M.Stallmann, Committee Member,Huang, Shu ; Dr. Rudra Dutta ; Committee Chair ; Dr. G.N.Rouskas ; Committee Member ; Dr. M.Stallmann ; Committee Member

University:North Carolina State University

关键词: Traffic Grooming;    Complexity;    Approximability;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/2276/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

Recent increase in bandwidth and development of wavelength routing techniques has prompted the study of traffic grooming in wide area wavelength routed optical networks.These networks are widely expected to form the high speed high performance backbone networks of the future.We have studied the grooming problem as applied to the path network, where the physical topology of fibers simply forms a path.Path networks are important in themselves, because they arise naturally in different realistic scenarios, but also because they are simple elemental topologies which can contribute to the understanding of more complex topologies.We show that the problem of traffic grooming is NP-Complete in both unidirectional and bidirectional path networks under the objective of minimizing network-wide amount of electronic switching, whether bifurcation of traffic components into integral sub-components is allowed or not. These results are somewhat surprising in such a simple topology as the path, and underline the inherent complexity of the grooming problem.Our results have implications for grooming problems with other topologies, which we explore.We also explore the approximability of the problem in path networks.We prove that there is no such a polynomial approximation algorithm that it can guarantee an approximation ratio less than infinity, unless $P=NP$.We propose a heuristic approach to solve the problem practically. Our approach is loosely based on the idea of flow deviation.After defining the deviation framework in the context of our problem, we show that it is a family of algorithms rather than a single one, the different members of the family obtained by choosing different candidate approaches to two key subtasks.Some of these members possess practically important performance guarantees, which we define.We present numerical results obtained by applying our technique to traffic instances of various patterns to validate our theoretical claims.