提出了一种基于簇结构的无线传感器网络数据收集协议EADEEG(an energy-aware data gathering protocol for wireless sensor networks).EADEEG通过最小化网络通信开销以及良好的能量负载平衡方法,可以有效地延长网络寿命.与以前的相关...提出了一种基于簇结构的无线传感器网络数据收集协议EADEEG(an energy-aware data gathering protocol for wireless sensor networks).EADEEG通过最小化网络通信开销以及良好的能量负载平衡方法,可以有效地延长网络寿命.与以前的相关研究相比,EADEEG采用了一种全新的簇头竞争参数,能够更好地解决节点能量异构问题.此外,EADEEG也采用了一种简单而有效的簇内节点调度算法,通过控制活动节点的密度,可以在不增加额外控制开销的条件下关闭冗余节点并保证覆盖要求,因此可以进一步延长网络寿命.模拟实验证明,在节点初始能量同构和异构两种情况下,EADEEG协议都能够满足用户对覆盖率的要求,并在网络寿命上大幅度优于LEACH(low energy adaptive clustering hierarchy),PEGASIS(power-efficient gathering in sensor information systems)和DEEG(distributed energy-efficient data gathering and aggregation protocol)协议.展开更多
This paper addresses the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks(EADHFSPMT)by considering two objectives simultaneously,i.e.,makespan and total energy consumption.It cons...This paper addresses the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks(EADHFSPMT)by considering two objectives simultaneously,i.e.,makespan and total energy consumption.It consists of three sub-problems,i.e.,job assignment between factories,job sequence in each factory,and machine allocation for each job.We present a mixed inter linear programming model and propose a Novel MultiObjective Evolutionary Algorithm based on Decomposition(NMOEA/D).We specially design a decoding scheme according to the characteristics of the EADHFSPMT.To initialize a population with certain diversity,four different rules are utilized.Moreover,a cooperative search is designed to produce new solutions based on different types of relationship between any solution and its neighbors.To enhance the quality of solutions,two local intensification operators are implemented according to the problem characteristics.In addition,a dynamic adjustment strategy for weight vectors is designed to balance the diversity and convergence,which can adaptively modify weight vectors according to the distribution of the non-dominated front.Extensive computational experiments are carried out by using a number of benchmark instances,which demonstrate the effectiveness of the above special designs.The statistical comparisons to the existing algorithms also verify the superior performances of the NMOEA/D.展开更多
为解决ZigBee Cluster-Tree路由算法路径选择不优的问题,提出了一种能量感知的ZigBee树型路由EZTR(Energy-Aware ZigBee tree routing)算法.该算法利用每个节点感知的地址信息,按照ZigBee网络树型结构计算下一跳邻居节点到目的节点之间...为解决ZigBee Cluster-Tree路由算法路径选择不优的问题,提出了一种能量感知的ZigBee树型路由EZTR(Energy-Aware ZigBee tree routing)算法.该算法利用每个节点感知的地址信息,按照ZigBee网络树型结构计算下一跳邻居节点到目的节点之间的跳数可避免网络的环路效应,通过引入认知概念,在跳数集合中选出最短路径以降低跳数.在ZigBee网络节点能量的感知过程中,当所选路径存在低能量节点时,及时启用备用节点,从而避免节点因能量过度消耗成为失效节点.NS2(Network simulator version 2)仿真实验表明,EZTR算法可提高网络分组递交率,有效减少节点转发跳数和平均网络延时,减小网络整体能耗,为提高网络的实时性和延长网络生命周期提供理论支持.展开更多
Cloud Datacenter Network(CDN)providers usually have the option to scale their network structures to allow for far more resource capacities,though such scaling options may come with exponential costs that contradict th...Cloud Datacenter Network(CDN)providers usually have the option to scale their network structures to allow for far more resource capacities,though such scaling options may come with exponential costs that contradict their utility objectives.Yet,besides the cost of the physical assets and network resources,such scaling may also imposemore loads on the electricity power grids to feed the added nodes with the required energy to run and cool,which comes with extra costs too.Thus,those CDNproviders who utilize their resources better can certainly afford their services at lower price-units when compared to others who simply choose the scaling solutions.Resource utilization is a quite challenging process;indeed,clients of CDNs usually tend to exaggerate their true resource requirements when they lease their resources.Service providers are committed to their clients with Service Level Agreements(SLAs).Therefore,any amendment to the resource allocations needs to be approved by the clients first.In this work,we propose deploying a Stackelberg leadership framework to formulate a negotiation game between the cloud service providers and their client tenants.Through this,the providers seek to retrieve those leased unused resources from their clients.Cooperation is not expected from the clients,and they may ask high price units to return their extra resources to the provider’s premises.Hence,to motivate cooperation in such a non-cooperative game,as an extension to theVickery auctions,we developed an incentive-compatible pricingmodel for the returned resources.Moreover,we also proposed building a behavior belief function that shapes the way of negotiation and compensation for each client.Compared to other benchmark models,the assessment results showthat our proposed models provide for timely negotiation schemes,allowing for better resource utilization rates,higher utilities,and grid-friend CDNs.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No.60573132(国家自然科学基金)the National Grand Fundamental Research973Program of China under Grant No.2006CB303000(国家重点基础研究发展规划(973))the Hong Kong Polytechnic University under Grant No.A-PF77(香港理工大学)
文摘提出了一种基于簇结构的无线传感器网络数据收集协议EADEEG(an energy-aware data gathering protocol for wireless sensor networks).EADEEG通过最小化网络通信开销以及良好的能量负载平衡方法,可以有效地延长网络寿命.与以前的相关研究相比,EADEEG采用了一种全新的簇头竞争参数,能够更好地解决节点能量异构问题.此外,EADEEG也采用了一种简单而有效的簇内节点调度算法,通过控制活动节点的密度,可以在不增加额外控制开销的条件下关闭冗余节点并保证覆盖要求,因此可以进一步延长网络寿命.模拟实验证明,在节点初始能量同构和异构两种情况下,EADEEG协议都能够满足用户对覆盖率的要求,并在网络寿命上大幅度优于LEACH(low energy adaptive clustering hierarchy),PEGASIS(power-efficient gathering in sensor information systems)和DEEG(distributed energy-efficient data gathering and aggregation protocol)协议.
文摘低占空比无线传感器网络(low-duty-cycle wireless sensor networks,简称LDC-WSN)可以有效地延长网络生命周期.但是,现有的LDC-WSN中端到端的延迟非常大,并且现在很多关于LDC-WSN的算法没有充分考虑传输链路质量的问题.为了解决这两个问题,提出了一种基于链路质量和能量感知的节点休眠调度算法(link-quality and energy-aware based scheduling scheme,简称LES).仿真实验结果表明,相比现在的典型算法,LES算法能够在满足同样延迟要求的情况下很明显地节省能量,从而延长网络的工作寿命.
基金supported by the National Natural Science Fund for Distinguished Young Scholars of China(No.61525304)the National Natural Science Foundation of China(No.61873328)。
文摘This paper addresses the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks(EADHFSPMT)by considering two objectives simultaneously,i.e.,makespan and total energy consumption.It consists of three sub-problems,i.e.,job assignment between factories,job sequence in each factory,and machine allocation for each job.We present a mixed inter linear programming model and propose a Novel MultiObjective Evolutionary Algorithm based on Decomposition(NMOEA/D).We specially design a decoding scheme according to the characteristics of the EADHFSPMT.To initialize a population with certain diversity,four different rules are utilized.Moreover,a cooperative search is designed to produce new solutions based on different types of relationship between any solution and its neighbors.To enhance the quality of solutions,two local intensification operators are implemented according to the problem characteristics.In addition,a dynamic adjustment strategy for weight vectors is designed to balance the diversity and convergence,which can adaptively modify weight vectors according to the distribution of the non-dominated front.Extensive computational experiments are carried out by using a number of benchmark instances,which demonstrate the effectiveness of the above special designs.The statistical comparisons to the existing algorithms also verify the superior performances of the NMOEA/D.
文摘为解决ZigBee Cluster-Tree路由算法路径选择不优的问题,提出了一种能量感知的ZigBee树型路由EZTR(Energy-Aware ZigBee tree routing)算法.该算法利用每个节点感知的地址信息,按照ZigBee网络树型结构计算下一跳邻居节点到目的节点之间的跳数可避免网络的环路效应,通过引入认知概念,在跳数集合中选出最短路径以降低跳数.在ZigBee网络节点能量的感知过程中,当所选路径存在低能量节点时,及时启用备用节点,从而避免节点因能量过度消耗成为失效节点.NS2(Network simulator version 2)仿真实验表明,EZTR算法可提高网络分组递交率,有效减少节点转发跳数和平均网络延时,减小网络整体能耗,为提高网络的实时性和延长网络生命周期提供理论支持.
基金The Deanship of Scientific Research at Hashemite University partially funds this workDeanship of Scientific Research at the Northern Border University,Arar,KSA for funding this research work through the project number“NBU-FFR-2024-1580-08”.
文摘Cloud Datacenter Network(CDN)providers usually have the option to scale their network structures to allow for far more resource capacities,though such scaling options may come with exponential costs that contradict their utility objectives.Yet,besides the cost of the physical assets and network resources,such scaling may also imposemore loads on the electricity power grids to feed the added nodes with the required energy to run and cool,which comes with extra costs too.Thus,those CDNproviders who utilize their resources better can certainly afford their services at lower price-units when compared to others who simply choose the scaling solutions.Resource utilization is a quite challenging process;indeed,clients of CDNs usually tend to exaggerate their true resource requirements when they lease their resources.Service providers are committed to their clients with Service Level Agreements(SLAs).Therefore,any amendment to the resource allocations needs to be approved by the clients first.In this work,we propose deploying a Stackelberg leadership framework to formulate a negotiation game between the cloud service providers and their client tenants.Through this,the providers seek to retrieve those leased unused resources from their clients.Cooperation is not expected from the clients,and they may ask high price units to return their extra resources to the provider’s premises.Hence,to motivate cooperation in such a non-cooperative game,as an extension to theVickery auctions,we developed an incentive-compatible pricingmodel for the returned resources.Moreover,we also proposed building a behavior belief function that shapes the way of negotiation and compensation for each client.Compared to other benchmark models,the assessment results showthat our proposed models provide for timely negotiation schemes,allowing for better resource utilization rates,higher utilities,and grid-friend CDNs.
