With the rapid development of wireless sensor network （WSN）, the demands of limited radio frequency spectrum rise sharply, thereby dealing with the frequency assignment of WSN scientifically and efficiently becomes ...With the rapid development of wireless sensor network （WSN）, the demands of limited radio frequency spectrum rise sharply, thereby dealing with the frequency assignment of WSN scientifically and efficiently becomes a popular topic. To improve the frequency utilization rate in WSN, a spectrum management system for WSN combined with cloud computing technology should be considered. From the optimization point of view, the study of dynamic spectrum management can be divided into three kinds of methods, including Nash equilibrium, social utility maximization, and competitive economy equilibrium. In this paper, we propose a genetic algorithm based approach to allocate the power spectrum dynamically. The objective is to maximize the sum of individual Shannon utilities with the background interference and crosstalk consideration. Compared to the approach in [1], the experimental result shows better balance between efficiency and effectiveness of our approach.展开更多
This work develops an equilibrium model for finding the optimal distribution strategy to maximize performance of key predistribution protocols in terms of cost, resilience, connectivity, and lifetime. As an essential ...This work develops an equilibrium model for finding the optimal distribution strategy to maximize performance of key predistribution protocols in terms of cost, resilience, connectivity, and lifetime. As an essential attribute of wireless sensor networks, heterogeneity and its impacts on random key predistribution protocols are first discussed. Using supernetworks theory, the optimal node deployment model is proposed and illustrated. In order to find the equilibrium performance of our model, all optimal performance functions are changed into variational inequalities so that this optimization problem can be solved. A small-scale example is presented to illustrate the applicability of our model.展开更多
文摘With the rapid development of wireless sensor network （WSN）, the demands of limited radio frequency spectrum rise sharply, thereby dealing with the frequency assignment of WSN scientifically and efficiently becomes a popular topic. To improve the frequency utilization rate in WSN, a spectrum management system for WSN combined with cloud computing technology should be considered. From the optimization point of view, the study of dynamic spectrum management can be divided into three kinds of methods, including Nash equilibrium, social utility maximization, and competitive economy equilibrium. In this paper, we propose a genetic algorithm based approach to allocate the power spectrum dynamically. The objective is to maximize the sum of individual Shannon utilities with the background interference and crosstalk consideration. Compared to the approach in [1], the experimental result shows better balance between efficiency and effectiveness of our approach.
基金supported by the National Natural Science Foundation of China (Nos.61170241 and 61472097)the Specialized Research Fund for the Doctoral Program of Higher Education (No.20132304110017)the Open Fund of the Key Lab of Network Security and Cryptography of Fujian Province (No.150003)
文摘This work develops an equilibrium model for finding the optimal distribution strategy to maximize performance of key predistribution protocols in terms of cost, resilience, connectivity, and lifetime. As an essential attribute of wireless sensor networks, heterogeneity and its impacts on random key predistribution protocols are first discussed. Using supernetworks theory, the optimal node deployment model is proposed and illustrated. In order to find the equilibrium performance of our model, all optimal performance functions are changed into variational inequalities so that this optimization problem can be solved. A small-scale example is presented to illustrate the applicability of our model.
