Topology Control In Wireless Sensor Networks

WSN (Wireless Sensor Network) is quite different from traditional wired networkand other wireless networks. In WSNs, manual intervention is not available either in thenetwork deployment or operation phase. Thus sensor nodes are required to setup theoverlay network autonomously, and relay the monitored data back to the base station inmultihop manner. Moreover, the unpredictable node failure, joining of new nodes,unstable wireless channel, and other factors also impose new challenges to the topologyconstruction and maintainenance.Topology control in WSN has to deal with the above mentioned problems andchallenges. More specifically, topology control algorithm should form and maintain aconnected global topology by distributed methods using only localized information,adapt to node failures, and evolve with the specific requirements.Topology control is considered as one of the most important techniques in WSN,not only because it forms and maintains the network topology, but also because it is oneof the most effective methods for saving energy, reducing interference, and prolongingnetwork lifespan. Besides the above, the underlying network topology is the foundationfor the execution of routing protocols, and the guarantee for the efficiency of MAC(Media Access Control) protocol.Several algorithms are proposed in this study in order to improve the performanceof topology control. A summary of our work goes as follows.1) Two different types of interference definition, the graph based interference andthe interference under physical model, are discussed. The graph based interference mayfail to reflect the real interference because of ignoring the accumulated interferenceresulted by concurrent transmission. While the computation complexity of interferenceunder physical model makes it not suitable for algorithm design and analysis.The two definitions are combined by adding consideration of accumulatedinterference to link based interference. And thus it can be more accurate and lessexpensive in computation, which is later proved by analysis and simulation.2) Two basic communications, the command broadcast and data collection, are introduced by discussion of WSN’s basic tasks. It is not hard to tell that the twocommunications have very different requirements for the underlying topology.Thereafter, designing different algorithms for particular communication becomes thenatural choice. Then the Fast Dissemination Tree (FDT) and Balanced Data CollectionTree (BDCT) are presented. Furthermore, a mechanism called addable backup link isused to improve the robustness of BDCT. At last, the simulation shows that balance isachieved among different design goals, including energy efficiency, time delay for datacollection, and load balance.3) The process of existed clustering approaches is given. And after a careful lookinside the steps of clustering, several possible problems are revealed, which are listedbelow.First of all, the cluster head election can be done without any iteration. Secondly,there is a possibility that node with less left energy be elected as cluster head rather thanthe node with a higher energy level. Thirdly, maintaining topology by simply periodicalglobal topology reformation can be both energy and time expensive. Moreover, the loadof cluster heads is not evenly distributed. At last, the process of single node cluster isneither effective nor efficient.Our solutions for those problems are cluster head election with energy constraint,restricted global topology reformation by utilizing sleeping nodes, dynamic clusterradius, and hierarchical intra-cluster topology, which are later used in designing AEEC(Adaptive Energy Efficient Clustering) and ACDCR (Adaptive Clustering withDynamic Cluster Radius). It is demonstrated by simulation that AEEC prolongs thenetwork lifespan, and ACDCR alleviates the influence of ‘funneling effect’.