HRDSS-WMSN: A Multi-objective Function for Optimal Routing Protocol in Wireless Multimedia Sensor Networks using Hybrid Red Deer Salp Swarm algorithm
Autor: | S. Ambareesh, A. Neela Madheswari |
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Rok vydání: | 2021 |
Předmět: |
Routing protocol
Computer science Network packet Real-time computing Swarm behaviour 020206 networking & telecommunications 02 engineering and technology Grid Computer Science Applications Transmission (telecommunications) Packet loss Path (graph theory) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering Routing (electronic design automation) |
Zdroj: | Wireless Personal Communications. 119:117-146 |
ISSN: | 1572-834X 0929-6212 |
DOI: | 10.1007/s11277-021-08201-z |
Popis: | In general, WMSN follows many-to-one technique to transmit the data and to sense the information. There occurs a rapid increase in congestion or network traffic due to the generation of a large number of sensors. Moreover, the performances are jeopardized due to transmission and a high rate of packet losses. In order to address such shortcomings, this paper aims in developing a Hybrid Red Deer Salp Swarm (HRDSS) based routing approach. The HRDSS approach is the integration of a red deer and the salp swarm optimization algorithm. The work outlined in this paper is to minimize four different objectives namely packet loss, memory, delay and expected transmission cost. The main intention of the multi-objective function involves generating a diverse optimal solution set that is utilized to evaluate the trade-off among various objectives. We also presented the simulation results for two different scenarios comprising of the network grid and the optimization test functions that are carried out to determine the effectiveness of the system. In addition to this, the comparative analysis is done and the results reveal that the proposed HDRSS approach provides the best optimal routing path when compared with various approaches. |
Databáze: | OpenAIRE |
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