Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks.

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) rely on battery-powered nodes, making energy efficiency critical for operational longevity.
• Message bundling reduces transmissions but can increase delays, packet error rate (PER), and impact time synchronization.
• Delay-sensitive applications require careful consideration of end-to-end latency and retransmission impacts.

Purpose of the Study:

• To propose an optimal message bundling scheme for WSNs that minimizes total energy consumption.
• To balance the trade-offs between message bundling, packet retransmissions, and link quality.
• To address the limitations of existing methods regarding delays and PER in WSNs.

Main Methods:

• Formulated an optimal message bundling problem as an integer nonlinear programming problem.
• Developed and applied a self-adaptive global-best harmony search (SGHS) algorithm to solve the optimization problem.
• Evaluated the scheme using the Cooja emulator with the Contiki-NG operating system.

Main Results:

• The proposed optimal bundling scheme achieved significant energy savings compared to baseline and state-of-the-art methods.
• Demonstrated up to 51.8% total energy consumption reduction compared to no bundling.
• Showed an 8.8% improvement in energy savings over an existing integer linear programming model.

Conclusions:

• The novel optimal message bundling scheme effectively reduces WSN energy consumption.
• The SGHS algorithm provides an efficient solution for the complex optimization problem.
• This approach offers a practical method for enhancing WSN performance in delay-sensitive applications.