Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  aims at achieving optimal rate allocation for data aggregation in wireless sensor networks.  first formulate this rate allocation problem as a network utility maximization problem. Due to its non-convexity,  take a couple of variable substitutions on the original problem and transform it into an approximate problem, which is convex.  then apply duality theory to decompose this approximate problem into a rate control subproblem and a scheduling subproblem. Based on this decomposition, a distributed algorithm for joint rate control and scheduling is designed, and proved to approach arbitrarily close to the optimum of the approximate problem. Finally,  show that our approximate solution can achieve near-optimal performance through both theoretical analysis and simulations.
['Lu Su', 'Yan Gao', 'Yong Yang', 'Guohong Cao']
I am writing a research paper on a idea Towards optimal rate allocation for data aggregation in wireless sensor networks
[{"from": "human", "value": "I am writing a research paper on a idea Towards optimal rate allocation for data aggregation in wireless sensor networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  aims at achieving optimal rate allocation for data aggregation in wireless sensor networks.  first formulate this rate allocation problem as a network utility maximization problem. Due to its non-convexity,  take a couple of variable substitutions on the original problem and transform it into an approximate problem, which is convex.  then apply duality theory to decompose this approximate problem into a rate control subproblem and a scheduling subproblem. Based on this decomposition, a distributed algorithm for joint rate control and scheduling is designed, and proved to approach arbitrarily close to the optimum of the approximate problem. Finally,  show that our approximate solution can achieve near-optimal performance through both theoretical analysis and simulations."}]