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Internet of Things (IoT) is a new network paradigm that allows the virtual presence of physical objects in our life. The main idea of IoT is origin from equipping daily life objects with embedded devices. Meanwhile, due to the low cost and high availability of sensor devices, wireless sensor networks (WSNs) have a great role in overspreading of IoT. This paper presents a new routing algorithm in order...
Routing plays a major role in increasing the energy efficiency of a wireless sensor network. In a cluster based wireless sensor network, cluster head can forward the data to the base station either directly or indirectly (multi-hoping). However, in multi-hop routing energy saving is more as compared to direct transmission. Further, the selection of energy efficient routing schedules helps in increasing...
Maximising the network lifetime is a challenging problem in sensor networks. This paper proposes an evolutionary clustering routing algorithm for heterogeneous wireless sensor networks (WSN). The method combines genetic algorithms (GA), ant colony optimisation algorithms (ACO) and clustering method. It explores the tradeoff between the algorithm complexity and transmitted energy. Experiment results...
Clustering in wireless sensor networks improves lifetime of the network by load distribution, data aggregation and use of clusterheads to efficiently route messages to the central gateway. Parameters governing creation of optimal clusters are often numerous and domain-specific. The challenges increase with mobile nodes due to faster temporal change in one or more parameter values like speed and distance...
This paper presents a novel pheromone update strategy for improving the clustering results of ant colony optimization (ACO). The proposed algorithm is motivated by the observation that most of the ACOs only keep track of the promising foraging information, which has the potential to lead to better solutions than all the other search directions in the pheromone table. This eventually makes the search...
To solve the hierarchical topology optimization issue in overlay network for multicast service, this paper proposed a hybrid clustering model (HCGA) combining k-means method with genetic algorithm. The hybrid model formulated the related issue as a multiple-objective optimization, and then modeled it as a weighted clustering problem. HCGA made fully use of genetic algorithm for better clustering performance...
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