A Spawn Mobile Agent Itinerary Planning Approach for Energy-Efficient Data Gathering in Wireless Sensor Networks

Area of Science:

• Mobile Computing
• Wireless Sensor Networks (WSNs)
• Distributed Systems

Background:

• Mobile agents (MAs) are used for energy-efficient data gathering in Wireless Sensor Networks (WSNs).
• Existing Multi-mobile agent Itinerary Planning (MIP) algorithms face challenges in optimizing the number and itineraries of distributed MAs.
• Current MIP approaches often increase energy and time consumption due to MA migration hops and code-carrying requirements.

Purpose of the Study:

• To propose a novel Spawn Multi-mobile agent Itinerary Planning (SMIP) approach for energy-efficient data gathering in WSNs.
• To mitigate the high energy and time costs associated with existing mobile agent itinerary planning methods.
• To improve the integrated energy-delay performance in WSN data collection.

Main Methods:

• Developed a Spawn Multi-mobile agent Itinerary Planning (SMIP) approach where a main MA spawns subordinate MAs with distinct tasks.
• Implemented a task delegation strategy allowing MAs to spawn other MAs for distributed data gathering.
• Conducted extensive simulation experiments to compare SMIP against selected MIP algorithms.

Main Results:

• The proposed SMIP approach demonstrated superior performance compared to existing MIP algorithms.
• SMIP significantly reduced energy consumption during the data gathering process.
• Task delay (time) was substantially decreased, leading to improved overall energy-delay performance.

Conclusions:

• The SMIP approach effectively addresses the limitations of current MIP algorithms in WSNs.
• Agent spawning is a viable strategy for optimizing energy and time efficiency in WSN data gathering.
• SMIP offers a promising solution for enhancing the performance of mobile computing in WSN environments.