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In-network processing (INP) is a promising method that allows aggregation of data while it is being transferred along the communication paths as a means to optimize the utilization of network resources without violating the quality of information (QoI) requirements. Given the large amount of data existing in dynamic environments, the optimization of INP requires a distributed framework that can adapt...
In this paper, a multi-objective directional sensor placement problem for wireless sensor networks is considered. The goal of the multi-objective optimization problem is to obtain sensor placement solutions with reasonable trade-offs between two conflicting objectives, namely energy consumption and detection capability. An adaptive normalized normal constraint method is proposed to solve such optimization...
In this paper we proposed a multi-objective optimization model for wireless sensor networks (WSNs). The proposed model optimized several objectives, simultaneously. Indeed, by starting from a generic configuration we found new location for sensors, that the network have appropriate performance in terms of energy consumption and travelled distance. For the monotony of energy consumption and life time...
In this paper, we utilized a multi-objective approach to balance energy consumption and performance in wireless sensor networks (WSNs) that use a maximum likelihood estimation (MLE) approach for energy-based target localization. First, we developed measures that allow energy consumption and performance to be balanced in one-dimensional sensor arrays. Next, we extended these methods for two-dimensional...
This paper presents a simple but an effective approach to restore the coverage within a wireless sensor network (WSN) when sensors fail without adding new sensors. We have considered a sensor node failure due to electrical faults or malfunctions during the initial deployment. Each sensor has a limited energy supply, and the failure of a sensor results in extra overhead during restoration of the uncovered...
LEACH (low-energy adaptive clustering hierarchy) is a well-known self-organizing, adaptive clustering protocol of wireless sensor networks. However it has some shortcomings when it faces such problems as the cluster construction and energy management. In this paper, LEICP (low energy intelligent clustering protocol), an improvement of the LEACH protocol is proposed to overcome the shortcomings of...
We study the minimum range assignment problem that consists in finding the range assignment that minimizes energy consumption in the network. We exhibit one bad behavior of classical graph reduction-based approaches: they only consider the sum of edges' weight as an optimization criterion. We then design a new graph reduction algorithm (the minimum power tree protocol) and its associated topology...
In this paper we propose some innovative optimization models for wireless sensor networks. The models are chosen depending on the task the network is called to execute and they focus on the optimization of some specific performance objectives. Indeed, starting from a generic configuration, the optimal solution defines a specific sensors displacement, which allows the network to achieve high performance,...
Energy minimization is a central issue for wireless sensor networks (WSNs). We propose an energy minimization model and suggest a solution algorithm for multi-hop flat routing for WSN. This model is based on some directed minimum spanning trees and the related tree packing problem. We compare this model and some known optimization model and algorithms for two-hop hierarchical routings. In our computational...
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