Biblio
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Group Consensus of Second-order Multi-agent Systems via Intermittent Sampled Control. 2021 International Conference on Security, Pattern Analysis, and Cybernetics(SPAC). :185–189.
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2021. This article considers the group consistency of second-order MAS with directly connected spanning tree communication topology. Because the MAS is divided into several groups, we proposed a group consistency control method based on intermittent control, and the range of parameters is given when the system achieves consensus. The protocol can realize periodic control and reduce the working hours of the controller in period. Furthermore, the group consistency of MAS is turn to the stability analysis of error, and a group consistency protocol of MAS with time-delays is designed. Finally, two examples are used for verify the theory.
QoE-aware Data Caching Optimization with Budget in Edge Computing. 2021 IEEE International Conference on Web Services (ICWS). :324—334.
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2021. Edge data caching has attracted tremendous attention in recent years. Service providers can consider caching data on nearby locations to provide service for their app users with relatively low latency. The key to enhance the user experience is appropriately choose to cache data on the suitable edge servers to achieve the service providers' objective, e.g., minimizing data retrieval latency and minimizing data caching cost, etc. However, Quality of Experience (QoE), which impacts service providers' caching benefit significantly, has not been adequately considered in existing studies of edge data caching. This is not a trivial issue because QoE and Quality-of-Service (QoS) are not correlated linearly. It significantly complicates the formulation of cost-effective edge data caching strategies under the caching budget, limiting the number of cache spaces to hire on edge servers. We consider this problem of QoE-aware edge data caching in this paper, intending to optimize users' overall QoE under the caching budget. We first build the optimization model and prove the NP-completeness about this problem. We propose a heuristic approach and prove its approximation ratio theoretically to solve the problem of large-scale scenarios efficiently. We have done extensive experiments to demonstrate that the MPSG algorithm we propose outperforms state-of-the-art approaches by at least 68.77%.