As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be optimized.Although many data centers use power oversubscription to make full use o...As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be optimized.Although many data centers use power oversubscription to make full use of the power capacity,there are unavoidable power supply risks associated with it.Therefore,how to improve the data center power capacity utilization while ensuring power supply security has become an important issue.To solve this problem,we first define it and propose a risk evaluation metric called Weighted Power Supply Risk(WPSRisk).Then,a method,named Hybrid Genetic Algorithm with Ant Colony System(HGAACS),is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply system.HGAACS uses historical power data of each server to find a better placement solution by population iteration.HGAACS possesses not only the remarkable local search ability of Ant Colony System(ACS),but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm(GA).To verify the performance of HGAACS,we experimentally compare it with five other placement algorithms.The experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the riskof powersupply system.展开更多
This paper investigates network partition and edge server placement problem to exploit the benefit of edge computing for distributed state estimation.A constrained many-objective optimization problem is formulated to ...This paper investigates network partition and edge server placement problem to exploit the benefit of edge computing for distributed state estimation.A constrained many-objective optimization problem is formulated to minimize the cost of edge server deployment,operation,and maintenance,avoid the difference in the partition sizes,reduce the level of coupling between connected partitions,and maximize the inner cohesion of each partition.Capacities of edge server are constrained against underload and overload.To efficiently solve the problem,an improved non-dominated sorting genetic algorithm III(NSGA-III)is developed,with a specifically designed directed mutation operator based on topological characteristics of the partitions to accelerate convergence.Case study validates that the proposed formulations effectively characterize the practical concerns and reveal their trade-offs,and the improved algorithm outperforms existing representative ones for large-scale networks in converging to a near-optimal solution.The optimized result contributes significantly to real-time distributed state estimation.展开更多
To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched...To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched. The concept of graph partitioning for CDN was defined. The conditions of graph partitioning for CDN were demonstrated: the sum of the weights of the nodes in each subarea is as close as possible; edge cut between the subareas is as large as possible; internal nodes in each subarea are connected as far as possible. By reference to light vertex matching algorithm of graph partitioning for network simulation,a multilevel k-way algorithm of graph partitioning for CDN was proposed. The maximized edge cut k-way KL refinement algorithm was discussed. Graph partitioning is a feasible way to solve the problem of CDN servers'placement. Multilevel k-way algorithm is a feasible algorithm for CDN graph partitioning.展开更多
物联网和5G网络的快速发展产生了大量数据,通过将计算任务从移动设备卸载到具有足够计算资源的边缘服务器上,可有效减少网络拥塞和数据传播延迟等问题。边缘服务器放置是任务卸载的核心,高效的边缘服务器放置方法能有效满足移动用户访...物联网和5G网络的快速发展产生了大量数据,通过将计算任务从移动设备卸载到具有足够计算资源的边缘服务器上,可有效减少网络拥塞和数据传播延迟等问题。边缘服务器放置是任务卸载的核心,高效的边缘服务器放置方法能有效满足移动用户访问低时延、高带宽等需求。为此,文中以最小化访问延迟和最小化负载差异为优化目标,建立边缘服务器放置优化模型;然后,提出了一种基于改进启发式算法的移动边缘服务器放置方法ESPHA(Edge Server Placement Based on Heuristic Algorithm),实现多目标优化。首先将K-means算法与蚁群算法相结合,通过效仿蚁群在觅食过程中共享信息素,将信息素反馈机制引入边缘服务器放置方法中,然后,通过设置禁忌表对蚁群算法进行改进,提高算法的收敛速度;最后,用改进的启发式算法求解模型的最优放置方案。使用上海电信真实数据集进行实验,结果表明提出的ESPHA方法在保证服务质量的前提下取得了低延迟和负载均衡之间的优化平衡,其效果优于现有的其他几种代表性的方法。展开更多
基金This work was supported by the National Natural Science Foundation of China(No.62072187)the Guangdong Major Project of Basic and Applied Basic Research(No.2019B030302002)+2 种基金the Guangzhou Science and Technology Program Key Projects(No.202007040002)the Guangdong Marine Economic Development Special Fund Project(No.GDNRC[2022]17)the Guangzhou Development Zone Science and Technology Project(Nos.2021GH10 and 2020GH10).
文摘As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be optimized.Although many data centers use power oversubscription to make full use of the power capacity,there are unavoidable power supply risks associated with it.Therefore,how to improve the data center power capacity utilization while ensuring power supply security has become an important issue.To solve this problem,we first define it and propose a risk evaluation metric called Weighted Power Supply Risk(WPSRisk).Then,a method,named Hybrid Genetic Algorithm with Ant Colony System(HGAACS),is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply system.HGAACS uses historical power data of each server to find a better placement solution by population iteration.HGAACS possesses not only the remarkable local search ability of Ant Colony System(ACS),but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm(GA).To verify the performance of HGAACS,we experimentally compare it with five other placement algorithms.The experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the riskof powersupply system.
基金supported by the Shanghai Sailing Program(No.19YF1423700)the National Key Research and Development Program of China(No.2016YFB0900100)the Key Project of Shanghai Science and Technology Committee(No.18DZ1100303).
文摘This paper investigates network partition and edge server placement problem to exploit the benefit of edge computing for distributed state estimation.A constrained many-objective optimization problem is formulated to minimize the cost of edge server deployment,operation,and maintenance,avoid the difference in the partition sizes,reduce the level of coupling between connected partitions,and maximize the inner cohesion of each partition.Capacities of edge server are constrained against underload and overload.To efficiently solve the problem,an improved non-dominated sorting genetic algorithm III(NSGA-III)is developed,with a specifically designed directed mutation operator based on topological characteristics of the partitions to accelerate convergence.Case study validates that the proposed formulations effectively characterize the practical concerns and reveal their trade-offs,and the improved algorithm outperforms existing representative ones for large-scale networks in converging to a near-optimal solution.The optimized result contributes significantly to real-time distributed state estimation.
基金Sponsored by the National Natural Science Foundation of China(Grant No.60973027)Science Projects of China National Ministry of Information Industry(Grant No.01XK230009)
文摘To determine CDN cache servers'placement reasonably,an idea that using graph partitioning to solve the problem was put forward through theoretical analysis and the specific algorithm of partitioning was researched. The concept of graph partitioning for CDN was defined. The conditions of graph partitioning for CDN were demonstrated: the sum of the weights of the nodes in each subarea is as close as possible; edge cut between the subareas is as large as possible; internal nodes in each subarea are connected as far as possible. By reference to light vertex matching algorithm of graph partitioning for network simulation,a multilevel k-way algorithm of graph partitioning for CDN was proposed. The maximized edge cut k-way KL refinement algorithm was discussed. Graph partitioning is a feasible way to solve the problem of CDN servers'placement. Multilevel k-way algorithm is a feasible algorithm for CDN graph partitioning.
文摘物联网和5G网络的快速发展产生了大量数据,通过将计算任务从移动设备卸载到具有足够计算资源的边缘服务器上,可有效减少网络拥塞和数据传播延迟等问题。边缘服务器放置是任务卸载的核心,高效的边缘服务器放置方法能有效满足移动用户访问低时延、高带宽等需求。为此,文中以最小化访问延迟和最小化负载差异为优化目标,建立边缘服务器放置优化模型;然后,提出了一种基于改进启发式算法的移动边缘服务器放置方法ESPHA(Edge Server Placement Based on Heuristic Algorithm),实现多目标优化。首先将K-means算法与蚁群算法相结合,通过效仿蚁群在觅食过程中共享信息素,将信息素反馈机制引入边缘服务器放置方法中,然后,通过设置禁忌表对蚁群算法进行改进,提高算法的收敛速度;最后,用改进的启发式算法求解模型的最优放置方案。使用上海电信真实数据集进行实验,结果表明提出的ESPHA方法在保证服务质量的前提下取得了低延迟和负载均衡之间的优化平衡,其效果优于现有的其他几种代表性的方法。
