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A New Dynamic Weight-Based Energy Efficient Algorithm ...
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由 A Essa 著作2017被引用 13 次 — The new DWCA algorithm is composed of two phases: a setup phase and a steady phase. The election process is similar to most known clustering ...
A New Dynamic Weight-Based Energy Efficient Algorithm ...
Springer
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Thus, this paper proposes a new Dynamic Weight Clustering based Algorithm (DWCA) for WSNs to reduce the overall energy consumption, balance the energy ...
A New Dynamic Weight-Based Energy Efficient Algorithm for ...
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A new Dynamic Weight Clustering based Algorithm for WSNs to reduce the overall energy consumption, balance the energy consumption among all nodes and ...
A new dynamic weight clustering algorithm for wireless ...
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Thus, this paper proposes a new Dynamic Weight Clustering based Algorithm (DWCA) for WSNs to reduce the overall energy consumption, balance the energy ...
Alsnousi Essa - Google 学术搜索
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A new dynamic weight clustering algorithm for wireless sensor networks. A Essa, A Al-Dubai, I Romdhani, M Eshaftri. 1, 2017.
Mohamed Eshaftri
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A new dynamic weight-based energy efficient algorithm for sensor networks. A Essa, AY Al-Dubai, I Romdhani, MA Eshaftri. Smart Grid Inspired Future Technologies ...
An Energy Efficient Dynamic Clustering Protocol Based on ...
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2024年10月22日 — In this paper, an energy efficient dynamic clustering protocol (EEDCP) based on weight for wireless sensor networks is proposed, which is able ...
Alsnousi Essa - الباحث العلمي من Google
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عدد مرات الاقتباسات ; A New Dynamic Weight-Based Energy Efficient Algorithm for Sensor Networks. A Essa, AY Al-Dubai, I Romdhani, MA Eshaftri. Smart Grid ...
Energy efficient secure routing in wireless sensor networks
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由 DPSE Christina 著作2011被引用 13 次 — We propose a Weight Based AODV protocol for the routing process in which the weight of a route is decided by four factors: the speed of nodes, the power level ...
A Systematic Review on the Energy Efficiency of Dynamic ...
MDPI
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由 MF Alomari 著作2022被引用 14 次 — In this paper, we present a Systematic Literature Review (SLR) explaining the difficulties in developing cluster-based methods, critical factors for clustering,