Workload prediction is critical in enabling proactive resource management of cloud *** workload prediction is valuable for cloud users and providers as it can effectively guide many practices,such as performance assur...
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Workload prediction is critical in enabling proactive resource management of cloud *** workload prediction is valuable for cloud users and providers as it can effectively guide many practices,such as performance assurance,cost reduction,and energy consumption ***,cloud workload prediction is highly challenging due to the complexity and dynamics of workloads,and various solutions have been proposed to enhance the prediction *** paper aims to provide an in-depth understanding and categorization of existing solutions through extensive literature *** existing surveys,for the first time,we comprehensively sort out and analyze the development landscape of workload prediction from a new perspective,i.e.,application-oriented rather than prediction methodologies per ***,we first introduce the basic features of workload prediction,and then analyze and categorize existing efforts based on two significant characteristics of cloud applications:variability and ***,we also investigate how workload prediction is applied to resource ***,open research opportunities in workload prediction are highlighted to foster further advancements.
Forecasting Human mobility is of great significance in the simulation and control of infectious diseases like COVID-19. To get a clear picture of potential future outbreaks, it is necessary to forecast multi-step Ori...
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Intelligent reflecting surface(IRS)assisted with the wireless powered communication network(WPCN)can enhance the desired signal energy and carry out the power-sustaining problem in ocean monitoring *** this paper,we i...
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Intelligent reflecting surface(IRS)assisted with the wireless powered communication network(WPCN)can enhance the desired signal energy and carry out the power-sustaining problem in ocean monitoring *** this paper,we investigate a reliable communication structure where multiple buoys transmit data to a base station(BS)with the help of the unmanned aerial vehicle(UAV)-mounted IRS and harvest energy from the base station *** organically combine WPCN with maritime data collection scenario,a scheduling protocol that employs the time division multiple access(TDMA)is proposed to serve multiple buoys for uplink data ***,we compare the full-duplex(FD)and half-duplex(HD)mechanisms in the maritime data collection system to illustrate different performances under these two *** maximize the fair energy efficiency under the energy harvesting constraints,a joint optimization problem on user association,BS transmit power,UAV’s trajectory and IRS’s phase shift is *** solve the non-convex problem,the original problem is decoupled into several subproblems,and successive convex optimization and block coordinate descent(BCD)methods are employed obtain the near-optimal solutions *** results demonstrate that the UAV-mounted IRS can significantly improve energy efficiency in our considered system.
Efficient resource allocation in computing networks is essential for managing fluctuating demands and optimizing system performance. Traditional auction and pricing models often fail to adapt to diverse demands and su...
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Federated Learning (FL), hailed as a potent approach in merging medical expertise, promises to elevate collaborative efforts among healthcare institutions while safeguarding the privacy and security of sensitive medic...
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Federated Learning (FL), as one of the effective methods to solve the problem of medical data silos, can promote mutual cooperation among medical institutions under the premise of safeguarding the privacy and security...
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In this article, the Kalman filter design problem is investigated for linear discrete-time systems under binary encoding schemes. Under such a scheme, the local information is quantized into a bit string by the remote...
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Amid the worsening energy crisis, wind farm layout optimization (WFLO) to increase power generation, reduce costs, and mitigate potential environmental impacts is of great significance. This paper formulates three-obj...
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Social behavior metadata has altered business models and human lifestyles. However, the inclusion of personal information in social behavior metadata poses risks of identity exposure for users. Under the requirements ...
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Recent years have witnessed rapid progress of convolutional neural networks (CNNs) and their successful application in the task of saliency prediction for omnidirectional images (ODIs). Albeit achieving tremendous per...
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