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Energy Proficient Reduced Coverage Set with Particle Swarm Optimization for Distributed Sensor Network
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作者 T.V.Chithra A.Milton 《Computer Systems Science & Engineering》 SCIE EI 2023年第5期1611-1623,共13页
Retransmission avoidance is an essential need for any type of wireless communication.As retransmissions induce the unnecessary presence of redundant data in every accessible node.As storage capacity is symmetrical to ... Retransmission avoidance is an essential need for any type of wireless communication.As retransmissions induce the unnecessary presence of redundant data in every accessible node.As storage capacity is symmetrical to the size of the memory,less storage capacity is experienced due to the restricted size of the respective node.In this proposed work,we have discussed the integration of the Energy Proficient Reduced Coverage Set with Particle Swarm Optimization(PSO).PSO is a metaheuristic global search enhancement technique that promotes the searching of the best nodes in the search space.PSO is integrated with a Reduced Coverage Set,to obtain an optimal path with only high-power transmitting nodes.Energy Proficient Reduced Coverage Set with PSO constructs a set of only best nodes based on the fitness solution,to cover the whole network.The proposed algorithm has experimented with a different number of nodes.Comparison has been made between original and improved algorithm shows that improved algorithm performs better than the existing by reducing the redundant packet transmissions by 18%~40%,thereby increasing the network lifetime. 展开更多
关键词 Wireless sensor network reduced coverage set swarm intelligence particle swarm optimization energy consumption
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Maximum-Profit Advertising Strategy Using Crowdsensing Trajectory Data
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作者 LOU Kaihao YANG Yongjian +1 位作者 YANG Funing ZHANG Xingliang 《ZTE Communications》 2021年第2期29-43,共15页
Out-door billboard advertising plays an important role in attracting potential customers.However,whether a customer can be attracted is influenced by many factors,such as the probability that he/she sees the billboard... Out-door billboard advertising plays an important role in attracting potential customers.However,whether a customer can be attracted is influenced by many factors,such as the probability that he/she sees the billboard,the degree of his/her interest,and the detour distance for buying the product.Taking the above factors into account,we propose advertising strategies for selecting an effective set of billboards under the advertising budget to maximize commercial profit.By using the data collected by Mobile Crowdsensing(MCS),we extract potential customers’implicit information,such as their trajectories and preferences.We then study the billboard selection problem under two situations,where the advertiser may have only one or multiple products.When only one kind of product needs advertising,the billboard selection problem is formulated as the probabilistic set coverage problem.We propose two heuristic advertising strategies to greedily select advertising billboards,which achieves the expected maximum commercial profit with the lowest cost.When the advertiser has multiple products,we formulate the problem as searching for an optimal solution and adopt the simulated annealing algorithm to search for global optimum instead of local optimum.Extensive experiments based on three real-world data sets verify that our proposed advertising strategies can achieve the superior commercial profit compared with the state-of-the-art strategies. 展开更多
关键词 billboard advertising mobile Crowdsensing probabilistic set coverage problem simulated annealing optimization problem
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