Game balanced multi-factor multicast routing in sensor grid networks

The application of the three-parameter game balance is proposed through an analysis of the relationship among the space, energy, and data factors.The same correlation coefficient among the vectors is used for a general game balance scheme, to find the point, list the matrix, and confirm the confidence margins of game balance.The model and system is scalable and easy to be extended to more factors.The approach can be extended to change the proportion of different factors in practice.Numbers of experiences have been done to prove that the approach can attain better efficient than former work. In increasingly important sensor grid networks, multicast routing is widely used in date aggregation and distributed query processing. It requires multicast trees for efficient data transmissions. However, sensor nodes in such networks typically have limited resources and computing power. Efforts have been made to consider the space, energy and data factors separately to optimize the network performance. Considering these factors simultaneously, this paper presents a game balance based multi-factor multicast routing approach for sensor grid networks. It integrates the three factors into a unified model through a linear combination. The model is standardized and then solved theoretically by using the concept of game balance from game theory. The solution gives Nash equilibrium, implying a well balanced result for all the three factors. The theoretic results are implemented in algorithms for cluster formation, cluster core selection, cluster tree construction, and multicast routing. Extensive simulation experiments show that the presented approach gives mostly better overall performance than benchmark methods.