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Joint computation offloading and parallel scheduling to maximize delay-guarantee in cooperative MEC systems

Digital Communications and Networks 2024年第3期10卷 693-705页

作者： Mian Guo Mithun Mukherjee jaime lloret Lei Li Quansheng Guan Fei Ji School of Electronics and Information Guangdong Polytechnic Normal UniversityGuangzhouChina School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjingChina Universitat Politecnica de Valencia 46022ValenciaSpain South China University of Technology China

The growing development of the Internet of Things(IoT)is accelerating the emergence and growth of new IoT services and applications,which will result in massive amounts of data being generated,transmitted and pro-cessed in wireless communication *** Edge Computing(MEC)is a desired paradigm to timely process the data from IoT for value *** MEC,a number of computing-capable devices are deployed at the network edge near data sources to support edge computing,such that the long network transmission delay in cloud computing paradigm could be *** an edge device might not always have sufficient resources to process the massive amount of data,computation offloading is significantly important considering the coop-eration among edge ***,the dynamic traffic characteristics and heterogeneous computing capa-bilities of edge devices challenge the *** addition,different scheduling schemes might provide different computation delays to the offloaded ***,offloading in mobile nodes and scheduling in the MEC server are coupled to determine service *** paper seeks to guarantee low delay for computation intensive applica-tions by jointly optimizing the offloading and scheduling in such an MEC *** propose a Delay-Greedy Computation Offloading(DGCO)algorithm to make offloading decisions for new tasks in distributed computing-enabled mobile devices.A Reinforcement Learning-based Parallel Scheduling(RLPS)algorithm is further designed to schedule offloaded tasks in the multi-core MEC *** an offloading delay broadcast mechanism,the DGCO and RLPS cooperate to achieve the goal of delay-guarantee-ratio ***,the simulation results show that our proposal can bound the end-to-end delay of various *** under slightly heavy task load,the delay-guarantee-ratio given by DGCO-RLPS can still approximate 95%,while that given by benchmarked algorithms is reduced to intolerable *** simulation resul

关键词： Edge computing Computation offloading Parallel scheduling Mobile-edge cooperation Delay guarantee

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GBP-WAHSN:A Group-Based Protocol for Large Wireless Ad Hoc and Sensor Networks

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Journal of Computer Science & Technology 2008年第3期23卷 461-480页

作者： jaime lloret Miguel Garcia Jesus Tomás Fernando Boronat Department of Communications Polytechnic University of ValenciaCamino Vera s/n46022ValenciaSpain

Grouping nodes gives better performance to the whole network by diminishing the average network delay and avoiding unnecessary message forwarding and additional overhead. Many routing protocols for ad-hoc and sensor networks have been designed but none of them are based on groups. In this paper, we will start defining group-based topologies, and then we will show how some wireless ad hoc sensor networks （WAHSN） routing protocols perform when the nodes are arranged in groups. In our proposal connections between groups are established as a function of the proximity of the nodes and the neighbor＇s available capacity （based on the node＇s energy）. We describe the architecture proposal, the messages that are needed for the proper operation and its mathematical description. We have also simulated how much time is needed to propagate information between groups. Finally, we will show a comparison with other architectures.

关键词： group-based protocol group-based architecture group-based routing algorithm large networks

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Iteration dependent interval based open‐closed‐loop iterative learning control for time varying systems with vector relative degree

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 645-660页

作者： Yun‐Shan Wei Jin‐Fan Wang Jia‐Xuan Wang Qing‐Yuan Xu jaime lloret School of Electronics and Communication Engineering Guangzhou UniversityGuangzhouChina School of Electronic and Information Guangdong Polytechnic Normal UniversityGuangzhouChina Universitat Politècnica de València ValenciaSpain

For linear time varying(LTV)multiple input multiple output(MIMO)systems with vector relative degree,an open‐closed‐loop iterative learning control(ILC)strategy is developed in this article,where the time interval of operation is iteration *** compensate the missing tracking signal caused by iteration dependent interval,the feedback control is introduced in ILC *** the tracking signal of many continuous iterations is lost in a certain interval,the feedback control part can employ the tracking signal of current iteration for *** the assumption that the initial state vibrates around the desired initial state uniformly in mathematical expectation sense,the expectation of ILC tracking error can converge to zero as the number of iteration tends to *** the circumstance that the initial state varies around the desired initial state with a bound,as the number of iteration tends to infinity,the expectation of ILC tracking error can be driven to a bounded range,whose upper bound is proportional to the *** is revealed that the convergence condition is dependent on the feed-forward control gains,while the feedback control can accelerate convergence speed by selecting appropriate feedback control *** a special case,the controlled system with integrated high relative degree is also addressed by proposing a simplified iteration dependent interval based open‐closed‐loop ILC ***,the effectiveness of the developed iteration dependent interval based open‐closed‐loop ILC is illustrated by a simulation example with two cases on initial state.

关键词： intelligent control iterative methods

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