Candidate Cluster Head Research Articles

무선 센서 네트워크를 위한 신뢰 기반의 안전한 클러스터 헤드 선출

클러스터 구조를 가진 센서 네트워크에서 클러스터 헤드는 그 멤버들로부터 데이터를 모아서 모아진 데이터를 싱크에 보내는 역할을 수행하기에, 오염된 노드들이 클러스터 헤드 선출에 개입하여 선출결과를 조작하거나 변경하지 못하도록 막아야 한다. 오염된 노드들로부터 클러스터 헤드 선출 과정을 보호하기 위해서는 선출과정의 비예측성, 비조작성, 그리고 일치성을 보존해야 한다. 하지만, 기존의 클러스터 헤드 선출 방법들은 지능화된 오염노드들이 상호 협력을 통해 위의 속성들을 교묘하게 손상시키는 것을 막지 못한다. 본 논문에서는 이러한 지능화된 오염노드들을 식별하고 제거함으로써 클러스터 헤드 선출과정을 보호하는 방법을 제안한다. 클러스터 헤드 선출 라운드 마다 각 멤버는 다른 멤버들의 행위에 따라 그들에게 직접적인 신뢰값을 부여한다. 각 멤버는 자신이 부여한 직접신뢰값과 다른 멤버들에 의해 부여된 간접신뢰값을 묶어서 멤버들의 실제 신뢰값들을 추출한다. 이후에 각 멤버는 추출된 다른 멤버들의 실제 신뢰값을 평가하고 낮은 신뢰값을 가진 멤버들은 클러스터헤드 후보자에서 제거한다. 이를 통해 제안방법은 다른 경쟁방법에 비해 클러스터 헤드 선출 결과의 비조작성과 일치성을 크게 향상 시킨다. 또한, 제안방법은 메시지 손실이 발생하는 환경에서도 다른 방법들에 비해 높은 비조작성과 일치성을 제공한다.

A Mental Clustering Algorithm Based on the Embedded Agent in Wireless Sensor Network

In this paper, a clustering protocol for Embedded Agent sensor network is proposed.In LEACH protocol, the selection probability P of candidate cluster head is constant without thinking about residual energy, which caused the lower residual energy easy to be the candidate cluster head.Compared with traditional structure of wireless sensor network, parameter was optimized. The confidence of the node, select probability and residual energy are the parameter of candidate cluster head, communication cost as the parameter of final cluster node. Compared with LEACH and ASCH, EACA take more parameters than LEACH. Results show that EACA can balance the energy load in the network, and effectively reduce more energy consumption.

INCREASING THE LIFETIME OF HETEROGENEOUS SENSOR NETWORK BY USING GENETIC-FUZZY CLUSTERING

Wireless sensor network is composed of hundreds or thousands of sensor nodes which have computational, energy and memory limitation. Its duty is to receive information from its surrounding environment, analyze and process data and to send the received data to other nodes or base station. In these networks, sensor nodes are dependent on low power batteries to provide their energy. As energy is a challenging issue in these networks, clustering models are used to overcome this problem. In this paper, fuzzy logic and genetic algorithm are combined to increase the lifetime of the wireless sensor network. In other words, fuzzy logic is used to introduce the best nodes, those that in comparison to other nodes have more energy, density and centrality, to base station as cluster head candidate. Then, the number and place of cluster heads are determined in base station by using genetic algorithm. Also, the network acts heterogeneously and includes several nodes with different parameters.

Energy-Efficient Intra-Cluster Data Gathering of Wireless Sensor Networks

S ensor nodes of Wireless Sensor Networks have limited battery power, so energy efficiency is mainly considered in the design. A novel mechanism of intra-cluster data gathering is designed for reducing the energy consumption and prolonging the network lifetime. Firstly, each cluster head acts continuously as local control center and will not be replaced by the candidate cluster head until its operation times reach its optimum value, thus the energy consu mption ratio of gathering data to broadcasting message is improved. Furthermore, according to the historical data, the mutual supportability of node is obtained by its cluster head through the correlation function. And then, the radios of incompatible nodes with low mutual supportabilities and the redundant node with high mutual supportabilities can be turned off for several rounds to reduce the intra-cluster communication consumption. Finally, the simulation results demonstrate that the mechanism can effectively reduce the energy consumption used for intra-cluster broadcasting message and gathering data, and prolong the network lifetime.

Clustering hierarchy tree routing algorithm based on LEACH

Considering the characteristics of sensor nodes' limited energy and limited transmission radius, the clustering hierarchy tree routing algorithm based on LEACH was proposed. In cluster construction stage, the optimal candidate cluster heads would become the final cluster heads, which guaranteed the distance between any two heads was far enough and neither of them was in the same area of radius, so the cluster heads were uniformly distributed in the network. In the inter-cluster communication, cluster heads form a hierarchical tree and the root was Base Station (BS), which reduced the energy consumption of direct data transmission from the head to BS, thereby prolonging the life cycle of the network.

Energy efficient clustering algorithm for maximizing lifetime of wireless sensor networks

The sensor nodes deployed in wireless sensor networks are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. An energy efficient clustering algorithm with optimum parameters is designed for reducing the energy consumption and prolonging the system lifetime. An analytical clustering model with one-hop distance and clustering angle is given. The optimum one-hop distance and clustering angle are formulated by minimizing the energy consumption between inter-cluster and intra-cluster. Furthermore, the continuous working mechanism of each cluster head which acts as the local control center and will not be replaced by the candidate cluster head until its continuous working times reach the optimum values is given, and the optimum continuous working times of each cluster head can be obtained through the optimum one-hop distance and the clustering angle. With the mechanism, the frequency of updating cluster head and the energy consumption for establishing new cluster head can be reduced. The simulation results demonstrate that the clustering algorithm can effectively reduce the energy consumption and increase the system lifetime.