ArticleSensors (Basel, Switzerland)2019
Energy Efficient Multipath Routing Algorithm for Wireless Multimedia Sensor Network.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A Novel Technique to Mitigate the Data Redundancy and to Improvise Network Lifetime Using Fuzzy Criminal Search Ebola Optimization for WMSN.Sensors (Basel, Switzerland) · 2023Article
- Multi-Path Routing Algorithm for Wireless Sensor Network Based on Semi-Supervised Learning.Sensors (Basel, Switzerland) · 2022Article
- Green Communication in Internet of Things: A Hybrid Bio-Inspired Intelligent Approach.Sensors (Basel, Switzerland) · 2022Article
- University Archives Autonomous Management Control System under the Internet of Things and Deep Learning Professional Certification.Computational intelligence and neuroscience · 2022Article
- An Optimization Model with Network Edges for Multimedia Sensors Using Artificial Intelligence of Things.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wireless multimedia sensor networks (WMSNs) are capable of collecting multimedia events, such as traffic accidents and wildlife tracking, as well as scalar data. As a result, WMSNs are receiving a great deal of attention both from industry and academic communities. However, multimedia applications tend to generate high volume network traffic, which results in very high energy consumption. As energy is a prime resource in WMSN, an efficient routing algorithm that effectively deals with the dynamic topology of WMSN but also prolongs the lifetime of WMSN is required. To this end, we propose a routing algorithm that combines dynamic cluster formation, cluster head selection, and multipath routing formation for data communication to reduce energy consumption as well as routing overheads. The proposed algorithm uses a genetic algorithm (GA)-based meta-heuristic optimization to dynamically select the best path based on the cost function with the minimum distance and the least energy dissipation. We carried out an extensive performance analysis of the proposed algorithm and compared it with three other routing protocols. The results of the performance analysis showed that the proposed algorithm outperformed the three other routing protocols.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.