In recent years, wireless sensor networks are playing an increasingly pivotal role in the monitoring of energy-constrained environments. However, the limited power of nodes restricts the network's life cycle and s...
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In recent years, wireless sensor networks are playing an increasingly pivotal role in the monitoring of energy-constrained environments. However, the limited power of nodes restricts the network's life cycle and service quality. In this paper, we propose an energy-aware dynamic reorganization clusteringprotocol based on the Gini coefficient and an improved particle swarm optimization algorithm (DGIPSO). The concept of Gini coefficient is applied to address uneven clustering in this hierarchical method. An improved PSO method is proposed for optimal cluster head selection, which considers residual energy, distance, and individual Gini coefficient factors. Additionally, a dynamic reorganization mechanism based on the Gini coefficient is introduced to enhance transmission performance over the network's lifespan. Experimental results demonstrate that the proposed DGIPSO protocol significantly outperforms LEACH, R-LEACH, PSO-C, PSO-WZ, and C3HA in network lifetime, energy efficiency, data throughput, and communication stability across various network scales. By incorporating Gini coefficients and heuristic algorithms into dynamic reorganization, this approach effectively addresses uneven energy distribution in clusteringprotocols, providing innovative strategies for monitoring in resource-constrained applications.
We propose a location-service to assist location-based routing protocols, realized through our Associativity-Based clusteringprotocol. The main goal of our scheme, which employs hierarchical principles, is to minimiz...
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ISBN:
(纸本)038723148X
We propose a location-service to assist location-based routing protocols, realized through our Associativity-Based clusteringprotocol. The main goal of our scheme, which employs hierarchical principles, is to minimize the control traffic associated with location-management. In location-based routing protocols, the control traffic is mainly due to location-updates, queries and responses. Our scheme employs a novel geographically-oriented clustering scheme in order to minimize control traffic without impairing performance. In our location management scheme, nodes are assigned home-zones, and are required to send their location-updates to their respective home-zones through a dominating-set. This strategy, unlike similar location-management approaches, minimizes inevitable superfluous flooding by every node, and prevents location updates and queries from traversing the entire network unnecessarily, hence conserving bandwidth and transmission power. We evaluate our proposed scheme through simulations, and the results indicate that our protocol scales well with increasing node-count.
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