As shown above, the energy and the delay requirements are not jointly optimized. An effective tradeoff between the energy and the delay is needed. The optimization should minimize the delay without a significant impact on the energy consumption. In this paper, energy and delay are introduced into a cost function, which is optimized when delivering data to the sink. Unlike previous work that reduces the energy consumption of the node by lowering the distance between the sender and the receiver [1]. Indeed, in our work, we optimize different design objective. Here, we reduce the energy consumption by minimizing the data flow through each link while satisfying the information generation rate of each node. Our contribution is threefold, we propose 1) a new formulation is introduced jointly minimize the energy and the delay as a multi-objective optimization one.
2) a MOPT-based routing and flow rate assignment methodology using the optimality conditions of
Karush-Kuhn-Tucker (KKT).
3) a sub-optimal solution based on soft computing approach of genetic algorithms (GA).