Sensor tasking and control
- 1. Ms.Preethma.R(17159UEL23), Final ECE Guided By Mrs.R.Chitra, Assistant Professor(SS), Department of ECE, School of Engineering, Avinashilingam Institute, Coimbatore Sensor Tasking and Control
- 2. Objective To understand the Design and analysis of self-adapted task scheduling strategies in WSN.
- 3. Introduction In a wireless sensor network (WSN), the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Task allocation and scheduling is a typical problem in the area of high performance computing. As the WSN always works in an unknown dynamic environment, sensor nodes may fail in many cases, such as when they move or die from battery depletion. Hence to solve this problem, a multi-agent-based self- adapted task scheduling strategy will be adapted.
- 4. The advantages of applying agent theories and technologies to the WSN (1) Using agent and multi-agent system theory to model and simulate the WSN contributes to formally analyze and design network activities and organization. (2) Using agent software can expand the WSN intelligence and create an autonomous network system. (3) Using agent software can reduce the redundancy of sensing data and data flow. (4) Using agent software can save the energy of the WSN and effectively extend the network lifetime. (5) Using agent-based design theory and method can achieve the dynamic application of the WSN and highly flexible strategy of task scheduling.
- 6. Algorithm for the Dynamic Alliance Model Basic Particle Swarm Optimization Discrete Particle Swarm Optimization for the Dynamic Alliance Model
- 8. The self-adapted task allocation strategy
- 9. Conclusion Due to several characteristics of wireless sensor networks, a self-adapted task scheduling strategy inspired by the multi-agent system theory. A dynamic alliance model for task allocation in WSNs and propose a DPSO-DA algorithm with a well-designed particle position code and fitness function for this dynamic alliance model.
- 10. Thank You