Energy is one of the most important criteria in wireless sensor networks. To extend the lifetime and coverage in these networks, researchers are always looking for ways that they can reduce the energy consumption of sensor nodes. Clustering methods sensor nodes is one of the best ways that can significantly increase the lifetime of the network. The hierarchical clustering protocols will have a more effective role. In this protocols, how to build a cluster, the cluster and data transmission methods, including issues that have a significant role in energy consumption. Hence, this paper, we study the reduction of energy consumption Wireless Sensor Networks one of the following methods called W-LEACH focused and to improve the algorithm equation suggests that the density of nodes in each round clustering is used in a more effective way. Simulation of MATLAB environment, shows that the proposed method than other methods such as LEACH, DE-LEACH, LEACH-C, L-LEACH, W-LEACH is able to increase network lifetime and energy consumption of sensor nodes be less. پرونده مقاله

Wireless sensor networks (WSNs) are composed of many low cost, low power devices with sensing, local processing and wireless communication capabilities. Clustering is a useful topology-management approach to improve lifetime and reduce the energy consumption in wireless sensor networks. In this paper we have proposed a new dynamic clustering method (NDCM) where clusters are created periodically and cluster head (CH) is selected based on threshold function. Unlike the LEACH protocol that clustering are static and cluster head number is fixed in the entire scenario, CHs in our method distributed in Land dimensions and the number of cluster can be dynamically adjusted based on the number of nodes. The simulation was performed in MATLAB software and it was compared with LEACH, LEACH-C, O-LEACH, LEACH-B, M-LEACH, V-LEACH AND W-LEACH algorithms. The simulation results show that proposed method have been reduced energy conservation and enhancement of network lifetime comparing with LEACH algorithm. Coverage of the number of clusters in proposed method is shown too. The results showed that in a test network life of leach protocol was 1100 rounds, whereas network life of proposed method was 3100 rounds. پرونده مقاله

Faults in computer networks may result in millions of dollars in cost. Faults in a network need to be localized and repaired to keep the health of the network. Fault management systems are used to keep today’s complex networks running without significant cost, either by using active techniques or passive techniques. In this paper, we propose a novel approach based on imperialist competitive algorithm using passive techniques to localize faults in computer networks. The presented approach using end-to-end data detect that there are faults on the network, and then we use imperialist competitive algorithm (ICA) to localize faults on the network. The aim of proposed approach is to minimize the cost of localization of faults in the network. According to simulation results, our algorithm is better than other state-of-the-art approaches that localize and repair all faults in a network. پرونده مقاله

In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intelligent feature selection system, involving crucial, decisive and effective factors in feature selection process. The procedure increases accuracy in classification and goodness of clusters. Finally, some of the problems and challenges facing the current and future feature selection processing are also discussed. پرونده مقاله