scholarly journals Energy Efficient Particle Swarm Optimization Based Multipath Routing in WSN

2018 ◽  
Vol 4 (10) ◽  
pp. 5
Author(s):  
Roshni Jha ◽  
Dr. Shivnath Ghosh
Keyword(s):  
Particle Swarm Optimization ◽  
Shortest Path ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Energy Requirement ◽  
Shortest Paths ◽  
Multipath Routing ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Shortest Path Routing

Wireless Networks includes a larger advantage in today’s communication application like environmental, traffic, military, and health observation. To realize these applications it's necessary to possess a reliable routing protocol. discusses about the working of proposed energy efficient bandwidth aware shortest path routing protocol for multipath routing in wireless sensor network. The proposed algorithm is based for choosing energy efficient shortest path. In routing algorithm, route that have shortest path among multipaths selected by particle swarm optimization algorithm. Among these shortest paths, that path is selected which require minimum route selection parameter. The proposed algorithm uses distance as well as energy of nodes as a parameter to find optimum paths using particle swarm optimization. Among these selected paths, only one optimum path is selected which reduces the energy requirement of the network. According to this work there would be improvement in other parameters also such as end to end delay as well as throughput.

scholarly journals Energy Optimized Routing Protocol Based on Binary Particle Swarm Optimization Successive Interference Cancellation for WSN

2020 ◽  
Vol 9 (4) ◽  
pp. 2020-2026
Keyword(s):  
Particle Swarm Optimization ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Interference Cancellation ◽  
Shortest Paths ◽  
Particle Swarm ◽  
Sensor Nodes ◽  
Binary Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Limited Energy

A large variety of Wireless Sensor Network (WSN) applications encourage researchers to develop and improve protocols and algorithms for rising challenges. During data transmission, energy consumption is main issue because sensor nodes have limited energy capacity. In fact, WSN needs load balancing algorithms that keep use of the limited energy source to route the collected data to the receiving node. While considering adhoc network in sensitive areas, one amongst the necessary aspects to consider is energy as a result of while sending information all communicating nodes exhausts its battery life. For mobile nodes in adhoc situation one and only one source of energy is battery. As compared to single path multipath routing helps to find best path that needs less energy and enhances the network life. In this paper an energy efficient routing protocol is proposed. In routing algorithm, route that have shortest path among multipaths chosen by particle swarm optimization algorithm. Among these shortest paths, that path is chosen that need minimum route selection parameter. The proposed algorithm is based on selection of energy efficient paths from multiple shortest SIC path from source to destination. For selection Binary Particle Swarm Optimization (BPSO) algorithm is applied. The Binary Particle Swarm Optimization (BPSO) algorithm selects energy efficient route among different shortest paths. The k-shortest route is selected on the basis of bandwidth and minimum SIC. The performance of the proposed algorithm is compared with multipath Ad hoc On-Demand Distance Vector (AODV) routing protocol and concluded that BPSO optimized energy efficient path is more efficient with respect to remaining energy of the network. The result is analyzed with variable number of packets send.

scholarly journals Efficient Computation of Shortest Paths in Networks Using Particle Swarm Optimization and Noising Metaheuristics

2007 ◽  
Vol 2007 ◽  
pp. 1-25 ◽  
Author(s):  
Ammar W. Mohemmed ◽  
Nirod Chandra Sahoo
Keyword(s):  
Particle Swarm Optimization ◽  
Local Search ◽  
Shortest Path ◽  
Hybrid Algorithm ◽  
Shortest Paths ◽  
Particle Swarm ◽  
Elementary Transformation ◽  
Efficient Computation ◽  
Hybrid Search ◽  
Swarm Optimization

This paper presents a novel hybrid algorithm based on particle swarm optimization (PSO) and noising metaheuristics for solving the single-source shortest-path problem (SPP) commonly encountered in graph theory. This hybrid search process combines PSO for iteratively finding a population of better solutions and noising method for diversifying the search scheme to solve this problem. A new encoding/decoding scheme based on heuristics has been devised for representing the SPP parameters as a particle in PSO. Noising-method-based metaheuristics (noisy local search) have been incorporated in order to enhance the overall search efficiency. In particular, an iteration of the proposed hybrid algorithm consists of a standard PSO iteration and few trials of noising scheme applied to each better/improved particle for local search, where the neighborhood of each such particle is noisily explored with an elementary transformation of the particle so as to escape possible local minima and to diversify the search. Simulation results on several networks with random topologies are used to illustrate the efficiency of the proposed hybrid algorithm for shortest-path computation. The proposed algorithm can be used as a platform for solving other NP-hard SPPs.

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