#5872. Multi-objective particle swarm optimization based rendezvous point selection for the energy and delay efficient networked wireless sensor data acquisition

June 2026publication date
Proposal available till 17-05-2025
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Journal’s subject area:
Computer Science Applications;
Computer Networks and Communications;
Hardware and Architecture;
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Abstract:
Traditionally, the non-rendezvous points transmit data towards Rendezvous Points (RPs), and Mobile Sink (MS) visits RPs to collect data. The existing body of research mitigates the problem of data acquisition latency, load on RPs, and energy consumption by regulating the number of RPs. Fewer RPs benefit the data acquisition latency, whereas increased RPs benefit the multi-hop forwarding and load on RPs. This paper takes up these issues and models as multi-objective optimization problem attempting to minimize data collection latency, data load among RPs, and the number of RPs. Particle Swarm Optimization (PSO) is the widely used meta-heuristic method to solve a multi-objective optimization problem with better convergence and minimum overhead. This paper introduces a Multi-Objective Particle Swarm Optimization based RPs Selection (MOPSO-RPS) method for energy and delay efficient data collection. MOPSO-RPS applies a new encoding scheme to generate variable dimension particles that represent each possible set of RPs. Additionally, a new inertia weight tuner is also referred to enhance the convergence speed of multi-objective PSO towards the optimal solution. However, it might happen that after updating the location and velocity in each iteration, the particles become invalid due to the violation of the search space boundary. Thus it adopts a valid particle generator to create valid particles. Moreover, an improved ant colony optimization is also applied to construct the trajectory of MS with fast convergence speed towards the optimal solution.
Keywords:
Meta-heuristics; Mobile sink; Multi-objective optimization; Particle swarm optimization; Rendezvous points; Wireless sensor networks

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