Studies On Network Optimization And Dynamic Networking Technology In Wireless Sensor Networks

Wireless sensor networks is a multi-hop self-organization networks constructed bya large number of low-cost micro-sensors deployed at the interior of detection regions.The networks is formed by wireless communication and widely used in manyapplications, such as battlefield surveillance, environment monitoring, urban traffic andwarehouse managements, etc. Wireless sensor networks as a new hot research area inthe field of information involve in the realms of wireless communication and digitalelectronics. Therefore there are many key technologies to be studied. Networkoptimization technology is one of the core issues need to be considered. To solve thisproblem and improve robustness of networks, this paper studies networks optimizationand dynamic networking technology, and presents some effective methods. The workhas been done includes five facets are listed as follows:1. According to networks characteristics like frequent changes of topologystructure, unstable of the wireless communication line, limited node energy, etc., anenergy efficient mobile agent routing algorithm (EEMAA) base on the infection sphereis presented in this paper. Mobile agent is conferred the character of ant in thisalgorithm, and the infection sphere is used to reduce the number of nodes which join inresearching and restoring the energy efficient route from processing node to target nodes.These ways can reduce energy consumer of networks in searching for the optimal route.Meanwhile, a new restore rule for the failure optimal route is presented. By using thisrule, the optimal route can restore quickly in the local of fail nodes and most of theinformation of original optimal route can be reserved. Simulation results show that ourapproach can keep away from the nodes with less residual energy and make the energyof each nodes on the optimal route overall decline. Hence improve the lifetime ofnetworks.2. Effective evaluating node importance in wireless sensor networks is importantto the optimization of topology and the reliability of networks. The existing evaluatemethods are based on center theory of complex networks, which don’t consider theinfluence of cluster in networks. Hence, they don’t suitable for wireless sensor networks.In this paper, based on agglomeration contraction principle for wireless sensor networks,we propose a novel node importance evaluation method. First, the original clusterstructure of networks can be got by using the nontrivial eigenvectors, then, by using modularity to evaluate and merge these cluster structure, a cluster structure more fits forthe real networks can be got. Finally, the backbone graph can be extracted from the basenetworks by using cluster contraction principle, and then evaluating the importance ofgateway nodes in the backbone graph and using some super energy nodes to protectvital gateway nodes, this way can prolong the life of networks and improve thesurvivability of networks effectively.3. Most wireless sensor networks utilize static sink to collect data from themonitored region, such way may result in high traffic load in static sink’s vicinity. Thenodes located near static sink will be more requested than other nodes in networks, sothese nodes will consume more energy and trigger off route hole. Mobile sink has beendeveloped to solve route hole problem. However, latency and packet delivery delaycaused by mobile sink may be intolerable. A novel mobile data collector algorithm(MDCA) which deals with the route hole and the delivery delay well is proposed in thispaper. MDCA adopts the rule of packets intercept, by this rule, the intermediate nodecan intercept data packets coming from distant nodes that do not belong to propagationtree and forward these data packets through its bypass leading to the mobile sink nearby.This rule can reduce the transmitted distance of data packets efficiently, and improve thesecurity of data packets. In addition, in current designs, sensor node does not havecongestion self-adaptive function. Dealing with congestion in these reactive mannersmay result in longer delay and unnecessary packet loss. Hence, a self-adaptive rulebased on congestion monitoring model is also presented. The congestion node canrestore quickly by using bypass to split data traffic. This strategy performs better inputting down the congestion level and improving the success rate of packettransmission.4. A combination optimization routing algorithm (CORA) based on the dualchannel wireless sensor networks is presented to put down the blocking probability ofhigh load networks. This algorithm deals with date collision and multicast suppressionin channel competitive process well by using the dual-channel communication model.At the same time, this algorithm uses the infection sphere to reduce the number of nodeswhich join in researching the optimization route from the source node to the target node;this way can reduce energy consumption of networks. At last, this paper proposes acombination optimal routing algorithm with the help of a layered-graph model. Theblocked service in control plane can use the idle resource in data plane to transmit insynchronous manner, so the blocking probability of networks and the delay of communication can be cut down by this way. Simulation results show that thisalgorithm performs better in terms of the time consumption of communication and thetotal energy consumption. Compared with the other algorithms, the blocking probabilityof networks can be cut down13%.5. Aiming at measurement errors of distances between nodes in wireless sensornetworks, a distributed local robust minimum spanning tree algorithm (LRMST) whichis based on local minimum spanning tree algorithm and the robust discrete optimizationtheory is proposed in this paper. When uncertainties affect the objective parameter in themodel of minimum spanning tree, the problem of searching the minimum spanning treeof networks can be conversion to a discrete optimization problem by means of Booleprogramming model. For the objective parameter-uncertain Boole programming model,the theory of robust discrete optimization is proved that the robust counterpart of thismodel can be solved by disposing of one deterministic programming problem. So whenall the measurement distances between nodes have measuring errors unavoidably, thealgorithm proposed in this paper can obtain the robust minimum spanning tree bysolving one deterministic problem. The simulation results show that, with the changingof laboratory conditions, the sensor nodes in minimum spanning tree which was foundby LRMST algorithm have more higher degree, this character can ensure minimumspanning tree has remarkable survivability and robustness.