Abstract: Tabu Search is a meta-heuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of Tabu Search is its use of adaptive memory, which creates a more flexible search behaviour. A novel finding is that such principles are sometimes sufficiently potent to yield effective problem solving behaviour in their own right, with negligible reliance on memory. In rechargeable Wireless Sensor Networks (WSNs), a key concern is the max flow or data rate at one or more sinks. However, this data rate is constrained by the available energy at each node as well as link capacity. After deployment, some sensor nodes may impede the amount of data that arrive at a sink because of their low energy harvesting rate. In this work, the main goal is to construct a fast tabu search algorithm for computing solutions so that max flow rate may achieve. The main objective is to maximize the flow rate at one or more sinks and optimize the network cost. It will investigate the problem of upgrading sensor nodes to maximize the flow rate. All simulations will be implemented in MATLAB.
Keywords: WSN System, Routings in WSN, Tabu Search, QoS in WSN etc.