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Contextual Cluster-Based Glow-Worm Swarm Optimization (GSO) Coupled Wireless Sensor Networks for Smart Cities.

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Summary
This summary is machine-generated.

A novel routing scheme using glow-worm optimization balances energy in wireless sensor networks (WSNs). While improving network lifetime, it shows higher energy consumption than some protocols due to specific packet types and routing paths.

Keywords:
cluster headglow-wormmulti-parametersoptimization and heterogeneousretransmission ratio

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Area of Science:

  • Wireless Sensor Networks (WSNs)
  • Optimization Techniques
  • Energy Efficiency in Communication

Background:

  • Cluster-based routing is common in WSNs, using cluster heads (CH) to aggregate and transmit data from cluster members (CM).
  • Existing CH functions like routing, compression, and aggregation can lead to rapid power depletion, impacting network longevity.
  • Heterogeneous high-power nodes (HPN) and improved algorithms are needed to balance energy consumption, especially for CHs near base stations.

Purpose of the Study:

  • To propose a new routing scheme for WSNs that enhances energy balancing and network lifetime.
  • To investigate the effectiveness of a cluster-based glow-worm optimization technique for WSN routing.
  • To evaluate the trade-offs between network lifetime, energy consumption, and throughput in the proposed model.

Main Methods:

  • Utilized a cluster-based glow-worm optimization technique involving random clustering, distributed cluster leader selection, and link-based routing.
  • Implemented multi-hop communication and data aggregation at the CH to reduce network load and conserve energy.
  • Simulated the proposed routing scheme in a 260-node network to assess throughput and energy efficiency.

Main Results:

  • The proposed algorithm demonstrated improved energy utilization and faster convergence compared to standard methods.
  • The technique successfully balanced energy consumption across the WSN through optimized routing and cluster construction.
  • The model exhibited higher energy consumption than TPGF and other protocols for specific packet types (0 or 1 retransmission) due to short INFO packets and increased hop counts.

Conclusions:

  • The combined approach of cluster-based optimization and multi-hop routing effectively extends WSN network lifetime and balances energy.
  • The glow-worm optimization technique offers advantages in convergence speed and multi-parameter selection for WSN routing.
  • Further research is needed to address the identified energy consumption issues related to neighbor discovery and routing pathways for specific packet scenarios.