The special scenario of the topology in the cellular Ad Hoc networks is studied and a novel cross layer game knowledge sharing algorithm based on multi-hop routing Neural Fuzzy Connection Admission Controller (NFCAC) ...
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The special scenario of the topology in the cellular Ad Hoc networks is studied and a novel cross layer game knowledge sharing algorithm based on multi-hop routing Neural Fuzzy Connection Admission Controller (NFCAC) is proposed in this paper. NFCAC has been successfully applied in the control-related problems of neural networks. However, there is no discussion about the game knowledge sharing algorithm and location recognition based on NFCAC in cellular Ad Hoc networking. We firstly propose a novel multi-hop routing NFCAC which is suitable for cellular Ad Hoc networking and then propose the algorithm to integrate the functions of both multi-hop routing NFCAC and the topology space in the special scenario. The topology and power consumption of each Mobile Host (MH) can be optimized due to the minimum link occupation with the help of the algorithm. Simulation results show that the algorithm can give more control guarantee to the networks in the variable MH loads and transmission powers, and make the MHs stable to support multi-hops at the same time. (C) 2008 Elsevier B.V. All rights reserved.
In the realm of multi-UAV-assisted mobile edge computing (MEC), the joint optimization of UAV deployment and task scheduling has emerged as a potent approach for mitigating energy consumption while ensuring highqualit...
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In the realm of multi-UAV-assisted mobile edge computing (MEC), the joint optimization of UAV deployment and task scheduling has emerged as a potent approach for mitigating energy consumption while ensuring highquality services for mobile users. Nevertheless, the intricate interdependence between UAV deployment and task scheduling presents formidable challenges when implementing this scheme. In response, we introduce a novel methodology called the Dual-Stage Hybrid Strategy with Genetic-Simulated Annealing and knowledgesharing (DSHSGSK). DSHSGSK employs an alternating optimization strategy known as HS-GSK, supplemented by an elimination operator, to simultaneously optimize UAV deployment and task scheduling. In pursuit of heightened efficiency in UAV deployment and a more effective task scheduling strategy, we propose an innovative location encoding scheme for UAVs. To harness the local search capabilities of the Harmony search (HS) algorithm and the global search capabilities of the Gaining sharingknowledge based algorithm (GSK), we introduce a coordination parameter (CP) to modulate the frequency of alternation between these two optimization techniques. Experimental results validate the superiority of our proposed method over other state-of-theart algorithms for jointly optimizing multi-UAV deployment and task scheduling. Notably, our approach excels in terms of energy consumption, underscoring its exceptional performance.
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