A Novel Salp Swarm Algorithm for Controller Placement Problem
| Autor: | Mayank Sharma, Ashish Mani, Sanjai Pathak, Amlan Chatterjee |
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| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
Computer science 020206 networking & telecommunications Computational intelligence 02 engineering and technology Network topology Swarm intelligence Local optimum Control theory 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing Selection (genetic algorithm) Reverse learning |
| Zdroj: | Communications in Computer and Information Science ISBN: 9783030667627 |
| Popis: | Self-adaptive control parameters and reverse learning mechanism are introduced in this paper to boost the performance of Salp Swarm Algorithm (SSA), through finding an optimal trade-off between exploitation and exploration for a class of benchmark problems. The proposed approach increases SSA’s global search ability and decreases the probability of entrapment in local optima. The Self-Adaptive Salp Swarm Algorithm relies on an integrated approach where each individual has to maintain diversity using the introduced reverse learning strategy. The obtained simulation results of the modified SSA shows, that the proposed strategy and algorithm is promising. Also, we introduced a single objective SASSA approach to the controller placement problem that minimizes propagation latency between the controller and its associated forwarding elements in a given network topology. Internet2 OS3E network topology is simulated for the placement of controllers, that includes finding position along with the selection of controllers in SDN for optimum performance. The results of implementing the modified SSA algorithm for a class of benchmark problems and the controller placement problem in SDN confirmed the effectiveness of this novel approach. |
| Databáze: | OpenAIRE |
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