Research On Crosslayer-Based Resource Scheduling And Routing Algorithm In Wireless Sensor Networks

Routing selection and resource allocation over links in wireless sensor networks is a combination optimization problem. The method to solve it effectively is to adopt the cross layer optimization by combining physical layer and data link layer. In addition, since there exist the limited energy in nodes and the interference among links, it becomes a optimization problem with constraints to achieve the optimization objective. According to the maximization utility theory, first, we analyze the diversity characteristic affecting the system optimization, including frequency selection diversity, location diversity, the time diversity and queue diversity of member nodes. Then, considering resource allocation and routing node selection required by the management mechanism based on self-clustering in wireless sensor networks, we establish the cross optimization model by the combination of routing selection and resource allocation over links accordant to the system utility maximization and propose efficient algorithms for several key problems needed during the optimization implementation.After analyzing the performance of the system, we conclude that since the routing transmission performance depends on the channel quality of the link, it leads to the effect between selecting routing links and resource scheduling over links. By the utility function, we derive the efficient computation model for the correlative factors. The optimization model for system resource is formulated based on the maximization value of the total utility. Additionally, we design the set of utility function capable of achieving the fairness of resource allocation among links, as a result, improving the total performance of resource scheduling. The optimization model provides the theory analysis evidence for the problems needed to solve behind.The implementation methods to achieve the effective routing selection are analyzed by directed graph theory. For the efficient resource allocation required by the problem, we propose a resource allocation scheme based on the combination of physical layer and data link layer using cross layer mechanism and design the routing mechanism based on local clustering. The resource overhead needed by the data transmission of member nodes within each cluster is significantly decreased by the proposed the management method using the routing based on clustering, with the large numbers of load decrease and the efficiently decreased energy consumption of member nodes. The higher performance of resource allocation is achieved under different system loads.In order to solve the problem caused by scheduling frequency over routing links in OFDM wireless sensor networks, we analyze two key factors, interference among routing links using the same frequency width that affect the optimization of system model. A scheme for dynamic subcarrier allocation is proposed according to the theory analysis. Through predicting interference factors among the links using the same frequency width, we determine the statistical period for efficient subcarrier allocation, which provide the better transmission performance over routing links in OFDM wireless sensor networks.Time-varying co-channel interference results in the instability of link condition, which leads to the higher complexity of the system capacity maximization in OFDM wireless sensor networks using the reuse of subcarrier. To solve it, we present a subcarrier allocation algorithm (DSA) based on heuristic searching mechanism after investigating automatic quitting due to time expiring and automatic quitting due to the higher level of signal to noise ratio. Applying the. global fairness control to DSA, we propose a global fairness scheduling algorithm (GPCSA). It is demonstrated by theory analysis and simulation results that DSA and GPCSA improve the efficiency and fairness of transmission respectively.Using the mathematic model analysis and simulation measurement, we obtain the improved efficiency and fairness of system performance and the further optimized resource scheduling and routing link selection under some system conditions.