Research On Topology Control Algorithm In Wireless Sensor Network

Wireless sensor network (WSN) is a new type of information acquisition and processing mode which is highly combined with the micro-electro-mechanical system, the embedded system and the wireless communication technology. This network system can be widely used in national defense and military, environmental monitoring, traffic management, and medical fields. In the wireless sensor network, the topology control algorithm is a critical issue. First, reasonable and efficient topology control in ensuring the network connectivity and coverage of the situation, can save energy consumption and maximize the survival time of the network. Second, a reasonable topology control can reduce communication interference between nodes to improve the network communication efficiency. Third, a reasonable topology control can provide basic support for efficient routing protocols. Forth, Topology control can also have an impact on the network data fusion. Fifth, a reasonable topology control strategy can compensate for the impact of sensor nodes death. Therefore, it is very important to study the effective topology control algorithm to adjust real-time sensor network topology.Existing topology control algorithms can be broadly divided into two categories: power control algorithm and sleep scheduling algorithm. There are some performance indicators to evaluate, such as: 1, the coverage; 2, the connectivity; 3, the survival time; 4, the throughput; 5, interference and competition; 6, topology property. This paper will compare the widely used algorithm such as LMA/LMN algorithm, DRNG algorithm, SPAN algorithm, GAF algorithm, TopDisc algorithm. After analysis and comparison, we found that, due to the complexity of wireless sensor networks topology and the difficulties of simulation, every topology control algorithm has its own advantages and deficiencies. The current topology control algorithms focus on the studying of Levels sleep scheduling algorithm.In the many kinds of sleep scheduling algorithm, the LEACH algorithm can fairly and randomly select the cluster head, clustered quickly, greatly saved the energy consumption of the network and extend the network life cycle. However, by using the Matlab simulations of the LEACH algorithm as well as performance analysis it can be revealed that the cluster head selection algorithm does not consider node residual energy, and can not protect the low energy node, which could lead to some low-energy nodes premature death. Because the LEACH algorithm for cluster head node selection without considering the residual energy, we reference the node residual energy and made three improved algorithm of the LEACH, these algorithms consider the node's residual energy as the threshold of a weighting factor, so that the cluster head selection algorithm preferred more nodes residual energy in order to achieve the protection of low-energy nodes and extend the entire network life cycle. Then we analysis and simulate these algorithm.Comparing with the original LEACH algorithm comparison, we found that three kinds of algorithms are to some extent improved the defect of LEACH algorithm that it is not considered the residual energy, The improvement can postpone the first node in a time of death, extending the entire network the stability of the working life. However, comparing the three kinds of improved algorithm we are able to find that the first improved algorithm has better take into account the remaining energy relative to the initial maximum energy ratio, so that the remaining energy more priority to be elected as cluster head node, but when the total energy is low, the probability of cluster head election will be reduced; the second improved algorithm has better improved algorithm to solve the first algorithm's defect, but there are nodes in the first half of the inadequate protection for low-energy defects; we analysis both pre-advantages and disadvantages of two kinds of improved algorithm and proposed a third improved algorithm by using a different parameter variables A phased adjustment of the threshold T(n) and has received good experimental results. Under the same conditions, the improvement obviously delay the first node in a time of death, extending the working life of the stability of the entire network and enable the entire network of nodes tends to focus on the death ideal state.Tactical exercise is the most important way of testing a unit's combat power in time of peace. With the scientific and technological advances, more and more advanced technology applied to the red and blue against the tactical exercise. In order to be more accurate and efficient control of the exercise of the red and blue against the trend and process, using a variety of technical means to exercise, both red and blue regions of the implementation of real-time monitoring is particularly important. Wireless sensor itself has a self-organizing capacity, the ability to adapt to harsh environment characterized by relatively strong and so using a large number of sensors in wireless sensor networks laid the exercise area will become a reasonable and efficient choice.Therefore, in the end of this article, according to the needs of tactical field monitoring, we use wireless sensor network to design a set of tactical surveillance system plan. Tactical control system is a monitoring technology combine with computer hardware and software, information acquisition and processing, wireless sensors, network communications, GIS technologies, the system can be timely feedback from both offensive and defensive posture, and can be timely control the pace and progress of the exercise to provide accurate technical support. The system can be divided into two parts: control management centers and wireless sensor network exercise areas. The program features available in the system are as follows: 1 red and blue both offensive and defensive posture presents a timely manner; 2 casualty search and rescue; 3 key personnel location tracking. In this article, we also designed network architecture diagram and system disposition diagram.In order to present the wireless sensor network topology, we deeply study the wireless sensor networks and network management features. According the SNMP protocol of TCP network, we give two sets of plan for the network management of WSN.In order to be consistent with the B/S Design Patterns of the main control system, we use the RIA model to design the topology rendering subsystem. So it is easy to achieve the topology rendering capabilities for the tactical exercise monitoring system.In this paper, we have just done a relatively based research and experiments, the improved algorithm also have its own shortcomings. For example, the new algorithm did not solve the clustering uneven problem of the LEACH algorithm.As the wireless sensor network topology control algorithm research in many areas is still in a stage to try and explore, there are many aspects of ill-considered. Although the simulation can simulate the energy consumption and communication of WSN, It is difficult to simulate the real working mechanism of the WSN, because of the simple way of simulation and the uncertainty and complexity of the work environment of WSN. Therefore, the topology control algorithm, we have to be examined further, we should try our best to do more work.