The healthcare industry is rapidly adapting to new computing environments and technologies. With academics increasingly committed to developing and enhancing healthcare solutions that combine the Internet of Things (I...The healthcare industry is rapidly adapting to new computing environments and technologies. With academics increasingly committed to developing and enhancing healthcare solutions that combine the Internet of Things (IoT) and edge computing, there is a greater need than ever to adequately monitor the data being acquired, shared, processed, and stored. The growth of cloud, IoT, and edge computing models presents severe data privacy concerns, especially in the healthcare sector. However, rigorous research to develop appropriate data privacy solutions in the healthcare sector is still lacking. This paper discusses the current state of privacy-preservation solutions in IoT and edge healthcare applications. It identifies the common strategies often used to include privacy by the intelligent edges and technologies in healthcare systems. Furthermore, the study addresses the technical complexity, efficacy, and sustainability limits of these methods. The study also highlights the privacy issues and current research directions that have driven the IoT and edge healthcare solutions, with which more insightful future applications are encouraged.展开更多
Utility maximization is a major priority of prosumers participating in peer-to-peer energy trading and sharing(P2P-ETS).However,as more distributed energy resources integrate into the distribution network,the impact o...Utility maximization is a major priority of prosumers participating in peer-to-peer energy trading and sharing(P2P-ETS).However,as more distributed energy resources integrate into the distribution network,the impact of the communication link becomes significant.We present a multi-commodity formulation that allows the dual-optimization of energy and communication resources in P2P-ETS.On one hand,the proposed algorithm minimizes the cost of energy generation and communication delay.On the other hand,it also maximizes the global utility of prosumers with fair resource allocation.We evaluate the algorithm in a variety of realistic conditions including a time-varying communication network with signal delay signal loss.The results show that the convergence is achieved in a fewer number of time steps than the previously proposed algorithms.It is further observed that the entities with a higher willingness to trade the energy acquire more satisfactions than others.展开更多
文摘The healthcare industry is rapidly adapting to new computing environments and technologies. With academics increasingly committed to developing and enhancing healthcare solutions that combine the Internet of Things (IoT) and edge computing, there is a greater need than ever to adequately monitor the data being acquired, shared, processed, and stored. The growth of cloud, IoT, and edge computing models presents severe data privacy concerns, especially in the healthcare sector. However, rigorous research to develop appropriate data privacy solutions in the healthcare sector is still lacking. This paper discusses the current state of privacy-preservation solutions in IoT and edge healthcare applications. It identifies the common strategies often used to include privacy by the intelligent edges and technologies in healthcare systems. Furthermore, the study addresses the technical complexity, efficacy, and sustainability limits of these methods. The study also highlights the privacy issues and current research directions that have driven the IoT and edge healthcare solutions, with which more insightful future applications are encouraged.
基金This work was supported in part by the Peer-to-peer Energy Trading and Sharing-3M(multi-times,multi-scales,multi-qualities)project funded by EPSRC(No.EP/N03466X/1)in part,by ENERGY-IQ,a UK-Canada Power Forward Smart Grid Demonstrator project funded by The Department for Business,Energy and Industrial Strategy(BEIS)(No.7454460).
文摘Utility maximization is a major priority of prosumers participating in peer-to-peer energy trading and sharing(P2P-ETS).However,as more distributed energy resources integrate into the distribution network,the impact of the communication link becomes significant.We present a multi-commodity formulation that allows the dual-optimization of energy and communication resources in P2P-ETS.On one hand,the proposed algorithm minimizes the cost of energy generation and communication delay.On the other hand,it also maximizes the global utility of prosumers with fair resource allocation.We evaluate the algorithm in a variety of realistic conditions including a time-varying communication network with signal delay signal loss.The results show that the convergence is achieved in a fewer number of time steps than the previously proposed algorithms.It is further observed that the entities with a higher willingness to trade the energy acquire more satisfactions than others.
