Improvement of the design and analysis of flow rate in limited energy constrained wireless sensor networks using evolutionary optimization algorithms

Wireless sensor networks (WSNs) are known to be limited resources networks. These networks depend on limited energy components called sensor nodes with limited lifetime. They can be used in many applications in many fields. There are applications having limitations and restrictions on the flow rate delivered to the sink. There are others having limitations in the receiving time and latency for data that the delay in collecting, processing and sending the data is sensitive. So the trend always is to design an optimized WSN which can achieve good levels of flow rate and lifetime. Two optimization problems for a small application WSN were studied. The first was maximization of flow rate in limited energy constrained WSN. The second was related to the maximization of lifetime for the same WSN. We used genetic algorithm and the particle swarm optimization to perform the optimization processes. A combined problem was formulated from the two problems.