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Optimal Placement of a certain number of sinks at appropriate locations in WSNs reduces the number of hops between a sensor and its sink. This reduction ensures less exchanged messages between nodes and consequently less energy consumption. Since finding the optimal number of the sinks and their locationsis an NP Hard problem, a meta-heuristic evolutionary approach has been adopted as a Sink Placement...
Deploying and maintaining wireless sensor networks (WSN) in remote places like volcano eruption, battle field, nuclear reactors and dense forest areas is pretty difficult or even sometimes impossible. Therefore there is a need to make a WSN which can function for long duration of time. Lifetime enhancement of WSN is a critical issue to be addressed before its being deployed in such remote areas. Since...
Optimization of communication among sensors to serve data in short latency and minimal energy is necessitated for some of the wireless sensor network applications. For a self-organizing wireless sensor network Genetic Algorithm based multi-objective methodology is developed and is used as a technique in the selection of sensor nodes which play special roles in running caching and request forwarding...
Wireless sensor networks are emerged as a new technology in different applications to get information from environment in recent years. On of the most important challenges in this type of networks is energy shortage of sensors. Where as energy restriction, it should be mentioned a fundamental solution to providence energy consumption. The most suitable solution is clustering. In this paper the clustering...
Wireless Sensor Network (WSN) technology is employed in monitoring system to prevent the spontaneous combustion of coal gangue. A temperature monitoring system was designed, which monitor environment of gangue and prevent the occurrence of spontaneous combustion networking strategy through the collection of temperature in real-time or fix time. According to the energy-constrained problem of WSN, pseudo-parallel...
The Wireless Sensor Networks (WSN) technology is employed in the open-pit mine slope detection system. When the open-pit mine slope is found abnormal, the WSN transmit data to the monitors timely in case of the unnecessary losses. Quantum genetic algorithm (QGA) is used in the multi-objective optimization problem of slope detection with WSN. It's for designing networking strategy of slope detection...
There is a growing need for tools that could help Wireless Network system designers in selection of different protocols before a practical network deployment. A Genetic Algorithm(GA)-based Sensor Network Design Tool(SNDT) is proposed in this work for wireless sensor network design in terms of performance, considering application-specific requirements, deployment constrains and energy characteristics...
Integrating mobility into WSNs can significantly reduce the energy consumption of sensor nodes. However, this may lead to unacceptable data collection latency at the same time. In our previous work, we alleviated the problem under the assumption of a mobile base station (BS). In this paper, we discuss how the problem can be solved when the BS itself is not capable of moving, but it can instead employ...
We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal coverage and improved battery life using dynamic power scaling (DPS) and improved fitness function. DPS exploits idle times, packet delay guarantees, performance and workload data using additional controls related to sensor...
Location knowledge of sensor nodes in a network is essential for many tasks such as routing, cooperative sensing, or service delivery in ad hoc, mobile, or sensor networks, and it is hard to get the precision solution by traditional node localization algorithm, while genetic algorithm is an effective methodology for solving combinatorial optimization problems, so, in this paper, a real-coded version...
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