This article put forward a resource allocation scheme aimming at maximizing system throughtput for devide-to- device （D2D） communications underlying cellular network. Firstly, user closeness is defined and calculate...This article put forward a resource allocation scheme aimming at maximizing system throughtput for devide-to- device （D2D） communications underlying cellular network. Firstly, user closeness is defined and calculated through social information including friendship, interest similarity and communication strength to represent the willingness of user to share the spectrum resource with others. Then a social-aware resource allocation problem is formulated to maximize the system throughput while guaranteeing the quality of service （QoS） requirements of both D2D pairs and cellular users （CUs）. Then the complicate problem is decomposed into three subproblems. Firstly the admissible D2D pairs are determined and then the power of both CUs and D2D pairs is efficiently allocated. Finally CUs and D2D pairs are matched to reuse the spectrum resource in consideration of both user closeness and physical conditions. Simulation results certify the effectiveness of the proposed scheme which significantly enhances the system throughput compared with the existing algorithms.展开更多
A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communic...A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms.展开更多
在5G边缘网络飞速发展的过程中,边缘用户对高带宽、低时延的网络服务的质量要求也显著提高.从移动边缘网络的角度来看,网络内的整体服务质量与边缘用户的分配息息相关,用户移动的复杂性为边缘用户分配带来困难,边缘用户分配过程中还存...在5G边缘网络飞速发展的过程中,边缘用户对高带宽、低时延的网络服务的质量要求也显著提高.从移动边缘网络的角度来看,网络内的整体服务质量与边缘用户的分配息息相关,用户移动的复杂性为边缘用户分配带来困难,边缘用户分配过程中还存在隐私泄露问题.本文提出一种移动边缘环境下基于联邦学习的动态QoS(Quality of Service)优化方法MECFLD_QoS,基于联邦学习的思想,优化边缘区域的服务缓存,在动态移动场景下根据用户位置分配边缘服务器,有效保护用户隐私,实现区域服务质量优化,对动态用户移动场景有更好的适应性.MECFLD_QoS主要做了以下几个方面的优化工作:(1)优化了传统QoS数据集,将数据集映射到边缘网络环境中,充分考虑边缘计算的移动、分布式、实时性、复杂场景等特点,形成边缘QoS特征数据集;(2)优化了边缘服务器缓存,在用户终端训练用户偏好模型,与区域公有模型交互时只传输参数,将用户的隐私数据封装在用户终端中,避免数据的传输,可以有效地保护用户特征隐私;(3)优化了用户移动场景,在动态移动场景中收集用户移动信息,利用用户接入基站的地理位置拟合用户的移动轨迹进行预测,有效地模糊了用户的真实位置,在轨迹预测的同时有效地保护了用户的位置隐私;(4)优化了用户分配方法,提出改进的基于二维解的人工蜂群算法对边缘网络中的用户分配问题进行优化,事实证明改进的人工蜂群算法针对其多变量多峰值的特点有效地优化了用户分配,达到了较优的分配效果.通过边缘QoS特征数据集实验表明,本方法在多变量多峰值的用户分配问题中能产生全局最优的分配.展开更多
Resource allocation in the context of OFDMA-based systems is challenging, given a combinatorial nature of the problem. In the context of IEEE 802.16 systems this problem is further exacerbated by additional constraint...Resource allocation in the context of OFDMA-based systems is challenging, given a combinatorial nature of the problem. In the context of IEEE 802.16 systems this problem is further exacerbated by additional constraints that are faced with its two dimensional frame nature. The main challenges associated with resource allocation in these systems are: mapping the allocated bandwidth resources to users in this two dimensional frame, power and frequency allocation, and Qo S guarantee. This optimization problem can usually be solved by an iterative algorithm. The solutions proposed have a constant step size in iterations which causes a long convergence time. For this reason, the solutions proposed are not applicable in IEEE 802.16 systems. In this paper we propose a novel resource allocation algorithm in IEEE 802.16 systems which has an adaptive step size in iterations while taking into account the minimum rate guarantee for users.展开更多
The allocation of bandwidth to unlicensed users, without significantly increasing the interference on the existing licensed users, is a challenge for Ultra Wideband （UWB） networks. Our research work presents a novel...The allocation of bandwidth to unlicensed users, without significantly increasing the interference on the existing licensed users, is a challenge for Ultra Wideband （UWB） networks. Our research work presents a novel Rake Optimization and Power Aware Scheduling （ROPAS） architecture for UWB networks. Since UWB communication is rich in multipath effects, a Rake receiver is used for path diversity. Our idea of developing an optimized Rake receiver in our ROPAS architecture stems from the intention of reducing the computation complexity in terms of the number of multiplications and additions needed for the weight derivation attached to each finger of the Rake receiver. Our proposed work uses the Cognitive Radio （CR） for dynamic channel allocation among the requesting users while limiting the average power transmitted in each sub-band. In our proposed novel ROPAS architecture, dynamic channel allocation is achieved by a CR-based cross-layer design between the PHY and Medium Access Control （MAC） layers. Additionally, the maximum number of parallel transmissions within a frame interval is formulated as an optimization problem. This optimal decision is based on the distance parameter between a transmitter-receiver pair, bit error rate and frequency of request by a particular application. Moreover, the optimization problem improvises a differentiation technique among the requesting applications by incorporating priority levels among user applications. This provides fairness and higher throughput among services with varying power constraint and data rates required for a UWB network.展开更多
基金supported by the National Natural Science Foundation of China ( 61672484,11575181)
文摘This article put forward a resource allocation scheme aimming at maximizing system throughtput for devide-to- device （D2D） communications underlying cellular network. Firstly, user closeness is defined and calculated through social information including friendship, interest similarity and communication strength to represent the willingness of user to share the spectrum resource with others. Then a social-aware resource allocation problem is formulated to maximize the system throughput while guaranteeing the quality of service （QoS） requirements of both D2D pairs and cellular users （CUs）. Then the complicate problem is decomposed into three subproblems. Firstly the admissible D2D pairs are determined and then the power of both CUs and D2D pairs is efficiently allocated. Finally CUs and D2D pairs are matched to reuse the spectrum resource in consideration of both user closeness and physical conditions. Simulation results certify the effectiveness of the proposed scheme which significantly enhances the system throughput compared with the existing algorithms.
基金The National Natural Science Foundation of China(No60503041)the Science and Technology Commission of ShanghaiInternational Cooperation Project (No05SN07114)
文摘A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms.
文摘在5G边缘网络飞速发展的过程中,边缘用户对高带宽、低时延的网络服务的质量要求也显著提高.从移动边缘网络的角度来看,网络内的整体服务质量与边缘用户的分配息息相关,用户移动的复杂性为边缘用户分配带来困难,边缘用户分配过程中还存在隐私泄露问题.本文提出一种移动边缘环境下基于联邦学习的动态QoS(Quality of Service)优化方法MECFLD_QoS,基于联邦学习的思想,优化边缘区域的服务缓存,在动态移动场景下根据用户位置分配边缘服务器,有效保护用户隐私,实现区域服务质量优化,对动态用户移动场景有更好的适应性.MECFLD_QoS主要做了以下几个方面的优化工作:(1)优化了传统QoS数据集,将数据集映射到边缘网络环境中,充分考虑边缘计算的移动、分布式、实时性、复杂场景等特点,形成边缘QoS特征数据集;(2)优化了边缘服务器缓存,在用户终端训练用户偏好模型,与区域公有模型交互时只传输参数,将用户的隐私数据封装在用户终端中,避免数据的传输,可以有效地保护用户特征隐私;(3)优化了用户移动场景,在动态移动场景中收集用户移动信息,利用用户接入基站的地理位置拟合用户的移动轨迹进行预测,有效地模糊了用户的真实位置,在轨迹预测的同时有效地保护了用户的位置隐私;(4)优化了用户分配方法,提出改进的基于二维解的人工蜂群算法对边缘网络中的用户分配问题进行优化,事实证明改进的人工蜂群算法针对其多变量多峰值的特点有效地优化了用户分配,达到了较优的分配效果.通过边缘QoS特征数据集实验表明,本方法在多变量多峰值的用户分配问题中能产生全局最优的分配.
文摘Resource allocation in the context of OFDMA-based systems is challenging, given a combinatorial nature of the problem. In the context of IEEE 802.16 systems this problem is further exacerbated by additional constraints that are faced with its two dimensional frame nature. The main challenges associated with resource allocation in these systems are: mapping the allocated bandwidth resources to users in this two dimensional frame, power and frequency allocation, and Qo S guarantee. This optimization problem can usually be solved by an iterative algorithm. The solutions proposed have a constant step size in iterations which causes a long convergence time. For this reason, the solutions proposed are not applicable in IEEE 802.16 systems. In this paper we propose a novel resource allocation algorithm in IEEE 802.16 systems which has an adaptive step size in iterations while taking into account the minimum rate guarantee for users.
基金the National Science Foundation(NSF)of USA under Grant No.NeTS-WN0721641.
文摘The allocation of bandwidth to unlicensed users, without significantly increasing the interference on the existing licensed users, is a challenge for Ultra Wideband （UWB） networks. Our research work presents a novel Rake Optimization and Power Aware Scheduling （ROPAS） architecture for UWB networks. Since UWB communication is rich in multipath effects, a Rake receiver is used for path diversity. Our idea of developing an optimized Rake receiver in our ROPAS architecture stems from the intention of reducing the computation complexity in terms of the number of multiplications and additions needed for the weight derivation attached to each finger of the Rake receiver. Our proposed work uses the Cognitive Radio （CR） for dynamic channel allocation among the requesting users while limiting the average power transmitted in each sub-band. In our proposed novel ROPAS architecture, dynamic channel allocation is achieved by a CR-based cross-layer design between the PHY and Medium Access Control （MAC） layers. Additionally, the maximum number of parallel transmissions within a frame interval is formulated as an optimization problem. This optimal decision is based on the distance parameter between a transmitter-receiver pair, bit error rate and frequency of request by a particular application. Moreover, the optimization problem improvises a differentiation technique among the requesting applications by incorporating priority levels among user applications. This provides fairness and higher throughput among services with varying power constraint and data rates required for a UWB network.
