The mutual-interference phenomenon among multiple applications delivered as services through Cloud Services Delivery Network(CSDN)influences their QoS seriously.In order to deploy multiple applications dependably and ...The mutual-interference phenomenon among multiple applications delivered as services through Cloud Services Delivery Network(CSDN)influences their QoS seriously.In order to deploy multiple applications dependably and efficiently,we propose the Multiple Applications Co-Exist(MACE)method.MACE classifies multiple applications into different types and deploys them using isolation to some extent.Meanwhile,resource static allocation,dynamic supplement and resource reserved mechanism to minimize mutual-interference and maximize resource utilization are designed.After MACE is applied to a real large-scale CSDN and evaluated through 6-month measurement,we find that the CSDN load is more balanced,the bandwidth utilization increases by about 20%,the multiple applications'potential statistical multiplexing ratio decreases from 12% to 5%,and the number of complaint events affecting the dependability of CSDN services caused by multiple applications'mutual-interference has dropped to 0.Obviously,MACE offers a tradeoff and improvement for the dependability and efficiency goals of CSDN.展开更多
Calculating the most reliable maximum flow(MRMF)from the edge cache node to the requesting node can provide an important reference for selecting the best edge cache node in a content delivery network(CDN).However,SDBA...Calculating the most reliable maximum flow(MRMF)from the edge cache node to the requesting node can provide an important reference for selecting the best edge cache node in a content delivery network(CDN).However,SDBA,as the current state-of-the-art MRMF algorithm,is too complex to meet real-time computing needs.This paper proposes a set of MRMF algorithms:NWCD(Negative Weight Community Deletion),SCPDAT(Single-Cycle Preference Deletion Approximation algorithm with Time constraint)and SCPDAP(Single-Cycle Preference Deletion Approximation algorithm with Probability constraint).NWCD draws on the“flow-shifting”algorithm of minimum cost and maximum flow,and further defines the concept of negative weight community.This algorithm continuously deletes the negative weight communities,which can increase reliability while keeping the flow constant in the residual graph.It is proven that when all negative weight communities are deleted,the corresponding maximum flow is the MRMF.SCPDAT tries to approach the optimal solution to the greatest extent possible within the limited time,while SCPDAP tries to reach the probability threshold in the shortest amount of time.Both of these adopt the strategy of first deleting single-cycle communities(which contribute more to the reliability with lower time cost).Experiments show that,compared with SDBA,NWCD combined with the probabilistic pruning achieves an order of magnitude improvement in time cost,while SCPDAT and SCPDAP demonstrate better time performance and increased applicability.展开更多
In this paper, we present the virtual desktop that uses a novel methodology and related metrics to benchmark thin client based on Data Delivery Networks (DDN) in terms of scalability and reliability. Most studies of t...In this paper, we present the virtual desktop that uses a novel methodology and related metrics to benchmark thin client based on Data Delivery Networks (DDN) in terms of scalability and reliability. Most studies of the wireless networks mainly focus on system performance and power consumption circuit system;the main target has been separated in terms of Data operation and GUI operation by DDN. The communication protocol for wireless communication may play a major role in energy consumption and other important factors. The portable devices like Personal Digital Assistance (PDA) and others are mainly focusing on the efficient energy consumption (power control) in wireless networks. Here we focus on energy efficiency, algorithmic efficiency, virtualization and resource allocation;these are the main aims of the authors. The foremost research in the direction of wireless computing in saving energy and reducing carbon foot prints is also the challenging part. This is the study proof of brief account of wireless networks.展开更多
The emergence of smart edge-network content item hotspots, which are equipped with huge storage space (e.g., several GBs), opens up the opportunity to study the possibility of delivering videos at the edge network. ...The emergence of smart edge-network content item hotspots, which are equipped with huge storage space (e.g., several GBs), opens up the opportunity to study the possibility of delivering videos at the edge network. Different from both the conventional content item delivery network (CDN) and the peer-to-peer (P2P) scheme, this new delivery paradigm, namely edge video CDN, requires up to millions of edge hotspots located at users' homes/offices to be coordinately managed to serve mobile video content item. Specifically, two challenges are involved in building edge video CDN, including how edge content item hotspots should be organized to serve users, and how content items should be replicated to them at different locations to serve users. To address these challenges, we propose our data-driven design as follows. First, we formulate an edge region partition problem to jointly maximize the quality experienced by users and minimize the replication cost, which is NP-hard in nature, and we design a Voronoi-like partition algorithm to generate optimal service cells. Second, to replicate content items to edge-network content item hotspots, we propose an edge request prediction based replication strategy, which carries out the replication in a server peak offioading manner. We implement our design and use trace-driven experiments to verify its effectiveness. Compared with conventional centralized CDN and popularity-based replication, our design can significantly improve users' quality of experience, in terms of users' perceived bandwidth and latency, up to 40%.展开更多
Many production peer-to-peer (P2P) streaming systems use content delivery networks (CDN) to protect the user's quality of experiences. Thus, how to efficiently utilize the capacity of CDN (e.g., which peers rece...Many production peer-to-peer (P2P) streaming systems use content delivery networks (CDN) to protect the user's quality of experiences. Thus, how to efficiently utilize the capacity of CDN (e.g., which peers receive services from the CDN nodes) is a problem of practical significance. Existing solutions adopt a passive, on-demand approach, which is inefficient in utilizing CDN resources. In this paper, we propose PROSE, a simple, novel scheme to achieve proactive, selective CDN participation for P2P streaming. PROSE introduces novel concepts such as choke point expansion nodes/super nodes and leads to efficient, light-weighted, and distributed algorithms to identify and serve these nodes using CDN. Our experimental results show that PROSE achieves at least 10%~25% performance improvement and 2~4 times overhead reduction compared with existing general CDN-P2P-hybrid schemes.展开更多
Thanks to the emerging 3D integration technology, The multiprocessor system on chips (MPSoCs) can now integrate more IP cores on chip with improved energy efficiency. However, several severe challenges also rise up ...Thanks to the emerging 3D integration technology, The multiprocessor system on chips (MPSoCs) can now integrate more IP cores on chip with improved energy efficiency. However, several severe challenges also rise up for 3D ICs due to the die-stacking architecture. Among them, power supply noise becomes a big concern. In the paper, we investigate power supply noise (PSN) interactions among different cores and tiers and show that PSN variations largely depend on task assignments. On the other hand, high integration density incurs a severe thermal issue on 3D ICs. In the paper, we propose a novel task scheduling framework considering both the PSN and the thermal issue. It mainly consists of three parts. First, we extract current stimuli of running tasks by analyzing their power traces derived from architecture level simulations. Second, we develop an efficient power delivery network (PDN) solver to evaluate PSN magnitudes efficiently. Third, we propose a heuristic algorithm to solve the formulated task scheduling problem. Compared with the state-of-the-art task assignment algorithm, the proposed method can reduce PSN by 12% on a 2 × 2 × 2 3D MPSoCs and by 14% on a 3 × 3 × 3 3D MPSoCs. The end-to-end task execution time also improves as much as 5.5% and 7.8% respectively due to the suppressed PSN.展开更多
基金National Basic Research Program of China under Grant No. 2011CB302600National Natural Science Foundation of China under Grant No. 90818028,No. 61003226National Science Fund for Distinguished Young Scholars under Grant No. 60625203
文摘The mutual-interference phenomenon among multiple applications delivered as services through Cloud Services Delivery Network(CSDN)influences their QoS seriously.In order to deploy multiple applications dependably and efficiently,we propose the Multiple Applications Co-Exist(MACE)method.MACE classifies multiple applications into different types and deploys them using isolation to some extent.Meanwhile,resource static allocation,dynamic supplement and resource reserved mechanism to minimize mutual-interference and maximize resource utilization are designed.After MACE is applied to a real large-scale CSDN and evaluated through 6-month measurement,we find that the CSDN load is more balanced,the bandwidth utilization increases by about 20%,the multiple applications'potential statistical multiplexing ratio decreases from 12% to 5%,and the number of complaint events affecting the dependability of CSDN services caused by multiple applications'mutual-interference has dropped to 0.Obviously,MACE offers a tradeoff and improvement for the dependability and efficiency goals of CSDN.
基金partly supported by Open Research Fund from State Key Laboratory of Smart Grid Protection and Control,China(Zhang B,www.byqsc.net/com/nrjt/),Rapid Support Project(61406190120,Zhang B)the Fundamental Research Funds for the Central Universities(2242021k10011,Zhang B,www.seu.edu.cn)the National Key R&D Program of China(2018YFC0830200,Zhang B,www.most.gov.cn).
文摘Calculating the most reliable maximum flow(MRMF)from the edge cache node to the requesting node can provide an important reference for selecting the best edge cache node in a content delivery network(CDN).However,SDBA,as the current state-of-the-art MRMF algorithm,is too complex to meet real-time computing needs.This paper proposes a set of MRMF algorithms:NWCD(Negative Weight Community Deletion),SCPDAT(Single-Cycle Preference Deletion Approximation algorithm with Time constraint)and SCPDAP(Single-Cycle Preference Deletion Approximation algorithm with Probability constraint).NWCD draws on the“flow-shifting”algorithm of minimum cost and maximum flow,and further defines the concept of negative weight community.This algorithm continuously deletes the negative weight communities,which can increase reliability while keeping the flow constant in the residual graph.It is proven that when all negative weight communities are deleted,the corresponding maximum flow is the MRMF.SCPDAT tries to approach the optimal solution to the greatest extent possible within the limited time,while SCPDAP tries to reach the probability threshold in the shortest amount of time.Both of these adopt the strategy of first deleting single-cycle communities(which contribute more to the reliability with lower time cost).Experiments show that,compared with SDBA,NWCD combined with the probabilistic pruning achieves an order of magnitude improvement in time cost,while SCPDAT and SCPDAP demonstrate better time performance and increased applicability.
文摘In this paper, we present the virtual desktop that uses a novel methodology and related metrics to benchmark thin client based on Data Delivery Networks (DDN) in terms of scalability and reliability. Most studies of the wireless networks mainly focus on system performance and power consumption circuit system;the main target has been separated in terms of Data operation and GUI operation by DDN. The communication protocol for wireless communication may play a major role in energy consumption and other important factors. The portable devices like Personal Digital Assistance (PDA) and others are mainly focusing on the efficient energy consumption (power control) in wireless networks. Here we focus on energy efficiency, algorithmic efficiency, virtualization and resource allocation;these are the main aims of the authors. The foremost research in the direction of wireless computing in saving energy and reducing carbon foot prints is also the challenging part. This is the study proof of brief account of wireless networks.
基金This work was supported by the National Basic Research 973 Program of China under Grant No. 2015CB352300, the National Natural Science Foundation of China under Grant Nos. 61402247, 61272231, and 61133008, and the Beijing Key Laboratory of Net- worked Multimedia.
文摘The emergence of smart edge-network content item hotspots, which are equipped with huge storage space (e.g., several GBs), opens up the opportunity to study the possibility of delivering videos at the edge network. Different from both the conventional content item delivery network (CDN) and the peer-to-peer (P2P) scheme, this new delivery paradigm, namely edge video CDN, requires up to millions of edge hotspots located at users' homes/offices to be coordinately managed to serve mobile video content item. Specifically, two challenges are involved in building edge video CDN, including how edge content item hotspots should be organized to serve users, and how content items should be replicated to them at different locations to serve users. To address these challenges, we propose our data-driven design as follows. First, we formulate an edge region partition problem to jointly maximize the quality experienced by users and minimize the replication cost, which is NP-hard in nature, and we design a Voronoi-like partition algorithm to generate optimal service cells. Second, to replicate content items to edge-network content item hotspots, we propose an edge request prediction based replication strategy, which carries out the replication in a server peak offioading manner. We implement our design and use trace-driven experiments to verify its effectiveness. Compared with conventional centralized CDN and popularity-based replication, our design can significantly improve users' quality of experience, in terms of users' perceived bandwidth and latency, up to 40%.
基金Supported by the National Natural Science Foundation of China under Grant No. 60903164
文摘Many production peer-to-peer (P2P) streaming systems use content delivery networks (CDN) to protect the user's quality of experiences. Thus, how to efficiently utilize the capacity of CDN (e.g., which peers receive services from the CDN nodes) is a problem of practical significance. Existing solutions adopt a passive, on-demand approach, which is inefficient in utilizing CDN resources. In this paper, we propose PROSE, a simple, novel scheme to achieve proactive, selective CDN participation for P2P streaming. PROSE introduces novel concepts such as choke point expansion nodes/super nodes and leads to efficient, light-weighted, and distributed algorithms to identify and serve these nodes using CDN. Our experimental results show that PROSE achieves at least 10%~25% performance improvement and 2~4 times overhead reduction compared with existing general CDN-P2P-hybrid schemes.
基金This work was supported by the National Natural Science Foundation of China under Grant Nos. 61401008 and 61602022, and the State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, under Grant No. CARCH201602.
文摘Thanks to the emerging 3D integration technology, The multiprocessor system on chips (MPSoCs) can now integrate more IP cores on chip with improved energy efficiency. However, several severe challenges also rise up for 3D ICs due to the die-stacking architecture. Among them, power supply noise becomes a big concern. In the paper, we investigate power supply noise (PSN) interactions among different cores and tiers and show that PSN variations largely depend on task assignments. On the other hand, high integration density incurs a severe thermal issue on 3D ICs. In the paper, we propose a novel task scheduling framework considering both the PSN and the thermal issue. It mainly consists of three parts. First, we extract current stimuli of running tasks by analyzing their power traces derived from architecture level simulations. Second, we develop an efficient power delivery network (PDN) solver to evaluate PSN magnitudes efficiently. Third, we propose a heuristic algorithm to solve the formulated task scheduling problem. Compared with the state-of-the-art task assignment algorithm, the proposed method can reduce PSN by 12% on a 2 × 2 × 2 3D MPSoCs and by 14% on a 3 × 3 × 3 3D MPSoCs. The end-to-end task execution time also improves as much as 5.5% and 7.8% respectively due to the suppressed PSN.