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A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks.

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Mobile sinks in Event-Driven Wireless Sensor Networks (EWSNs) reduce energy consumption. This study optimizes data harvesting by strategically placing Rendezvous Points (RPs) to minimize hops and conserve battery power.

Keywords:
energy efficiencyfuzzy decision systemmobile sinkrendezvous point planningwireless sensor network

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) face significant energy consumption challenges.
  • Mobile sinks offer a solution to improve data harvesting efficiency in WSNs.
  • Network topology and data gathering present complexities in large-scale WSNs.

Purpose of the Study:

  • To investigate the use of a mobile sink for data harvesting in large-scale Event-Driven Wireless Sensor Networks (EWSNs).
  • To address network topology challenges by employing a mobile sink on a predefined trajectory.
  • To optimize energy consumption by strategically selecting Rendezvous Points (RPs).

Main Methods:

  • Formulating the Rendezvous Point (RP) planning problem as a Mixed Integer Linear Programming (MILP) model.
  • Proving the NP-hardness of the RP-planning problem.
  • Developing three distributed heuristics for RP-planning, sojourn location identification, and routing tree construction.

Main Results:

  • The proposed heuristics effectively address the challenges of RP-planning in EWSNs with mobile sinks.
  • Experimental results demonstrate the efficiency of the developed approach in minimizing energy consumption.
  • The strategy balances the number of RPs with data transmission hops to conserve energy.

Conclusions:

  • Employing mobile sinks with strategic RP-planning significantly enhances energy efficiency in EWSNs.
  • The proposed heuristic-based approach provides an effective solution for data harvesting in large-scale WSNs.
  • This work contributes to the development of sustainable and efficient wireless sensor network designs.