By analyzing the problems and challenges of virtual machine image store system in cloud computing environment, we present a cooperative persistent cache (CoCache) for virtual disks. CoCache takes advantage of the serv...
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By analyzing the problems and challenges of virtual machine image store system in cloud computing environment, we present a cooperative persistent cache (CoCache) for virtual disks. CoCache takes advantage of the service ability of the cached nodes by providing virtual image data service for other nodes. CoCache can transfer data between nodes in a P2P pattern, for extending data service ability of the system. CoCache is realized in the kernel space of Linux, can support any kind of VMM. Experiments show that CoCache can effectively reduce the cost during virtual machines read data, and promote the service ability of virtual machine storage system. Layer-aware cache policy is proposed specially for improving cache hit rate in the multi-layer and multipath environment.
Pervasive software should be able to adapt itself to the changing environments and user ***,it will bring great challenges to the software engineering *** paper proposes AUModel,a conceptual model for adaptive softwar...
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Pervasive software should be able to adapt itself to the changing environments and user ***,it will bring great challenges to the software engineering *** paper proposes AUModel,a conceptual model for adaptive software,which takes adaptability as an inherent feature and can act as the foundation of the engineering *** introducing AUModel,the reuse of software adaptation infrastructure as well as the separation of adaptation concerns are enabled,which can facilitate both the development and maintenance of adaptive *** paper also presents our initial attempts to realize this model,including a middleware prototype to support this model and an application to validate its effectiveness.
Traditional wireless relay networks have large endto-end time delay and low throughput because of the limit that it can't receive and forward at the same *** this paper,we proposed IWFR:Immediate Wireless Full-Dup...
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Traditional wireless relay networks have large endto-end time delay and low throughput because of the limit that it can't receive and forward at the same *** this paper,we proposed IWFR:Immediate Wireless Full-Duplex Relay which exploits the advantages of full-duplex to shorten the end-to-end time delay and improve the *** the same time,we designed a new implicit acknowledgement mechanism,which can eliminate the ACK overheads and evidently improve the throughput of the *** implement IWFR,we also modified the full-duplex node architecture to make it support for immediate *** shows that IWFR shortens the end-to-end time delay by 60%on average and improves the throughput to 240%of the original relay.
Traditional wireless relay networks have large end-to-end time delay and low throughput because of the limit that it can't receive and forward at the same time. In this paper, we proposed IWFR: Immediate Wireless ...
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Traditional wireless relay networks have large end-to-end time delay and low throughput because of the limit that it can't receive and forward at the same time. In this paper, we proposed IWFR: Immediate Wireless Full-Duplex Relay which exploits the advantages of full-duplex to shorten the end-to-end time delay and improve the throughput. At the same time, we designed a new implicit acknowledgement mechanism, which can eliminate the ACK overheads and evidently improve the throughput of the relay. To implement IWFR, we also modified the full-duplex node architecture to make it support for immediate relay. Simulation shows that IWFR shortens the end-to-end time delay by 60% on average and improves the throughput to 240% of the original relay.
As a key technique in cloud computing, live virtual machine (VM) migration makes cloud computing elastic and renders more efficient resource scheduling. In many cases, live storage migration is also desirable. Compare...
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As a key technique in cloud computing, live virtual machine (VM) migration makes cloud computing elastic and renders more efficient resource scheduling. In many cases, live storage migration is also desirable. Compared to live VM migration, however, live storage migration is relatively slow. The speed gap between live VM migration and live storage migration may lead to poor Quality of Service (QoS) for cloud users. In this paper, we present a new resource migration scheme, called Decoupled Live Storage Migration (DLSM), which decouples the live storage migration from the live VM migration. DLSM can migrate the VM immediately, while data blocks actually required by the VM are moved on demand at later times. It achieves the on-demand data migration at the storage level without the need of modifying the hypervisor. The key contribution of DLSM is that it reduces the network traffic and speeds up the live storage migration, by completely eliminating iterative copy of dirty data over the network. This good property is achieved without relying on any tracking mechanism for dirty data blocks. Experimental evaluation demonstrates the efficiency and effectiveness of DLSM.
To reduce the access latencies of end hosts,latency-sensitive applications need to choose suitably close service machines to answer the access requests from end *** K nearest neighbor search locates K service machines...
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To reduce the access latencies of end hosts,latency-sensitive applications need to choose suitably close service machines to answer the access requests from end *** K nearest neighbor search locates K service machines closest to end hosts,which can efficiently optimize the access latencies for end *** work has weakness in terms of the accuracy and *** to the scalable and accurate K nearest neighbor search problem,we propose a distributed K nearest neighbor search method called DKNNS in this *** machines are organized into a locality-aware multilevel *** first locates a service machine that starts the search process based on a farthest neighbor search scheme,then discovers K nearest service machines based on a backtracking approach within the proximity region containing the target in the latency *** analysis,simulation results and deployment experiments on the PlanetLab show that,DKNNS can determine K approximately optimal service machines,with modest completion time and query ***,DKNNS is also quite stable that can be used for reducing frequent searches by caching found nearest neighbors.
Hyperlink Induced Topic Search (HITS) is the most authoritative and most widely used personalized ranking algorithm on networks. The HITS algorithm ranks nodes on networks according to power iteration, and has high co...
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Virtualization is the foundation for cloud computing, and the virtualization can not be achieved without software defined, elastic, flexible and scalable virtual layers. Unfortunately, if multiple virtual storage devi...
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Virtualization is the foundation for cloud computing, and the virtualization can not be achieved without software defined, elastic, flexible and scalable virtual layers. Unfortunately, if multiple virtual storage devices are chained together, the system may be subject to severe performance degradation. While the read-ahead (RA) mechanism in storage devices plays a very important role to improve I/O performance, RA may not be effective as expected for multiple virtualization layers, since it is originally designed for one layer only. When I/O requests are passed through a long I/O path, they may trigger a chain reaction and lead to unnecessary data transmission and thus bandwidth waste. In this paper, we study the dynamic behavior of RA through multiple I/O layers and demonstrate that if controlled well, RA can greatly accelerate I/O speed. We present RAFlow, a RA control mechanism, to effectively improve I/O performance by strategically expanding RA window at each layer. Our real-world experiments show that it can achieve 20% to 50% performance improvement in I/O paths with up to 8 virtualized storage devices.
The concerns of data-intensiveness and energy awareness are actively reshaping the design of high-performance computing (HPC) systems nowadays. The Graph500 is a widely adopted benchmark for evaluating the performance...
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ISBN:
(纸本)9781479947638
The concerns of data-intensiveness and energy awareness are actively reshaping the design of high-performance computing (HPC) systems nowadays. The Graph500 is a widely adopted benchmark for evaluating the performance of computing systems for data-intensive workloads. In this paper, we introduce a data-parallel implementation of Graph500 on the Intel Single-chip Cloud Computer (SCC). The SCC features a non-coherent many-core architecture and multi-domain on-chip DVFS support for dynamic power management. With our custom-made shared virtual memory programming library, memory sharing among threads is done efficiently via the shared physical memory (SPM) while the library has taken care of the coherence. We conduct an in-depth study on the power and performance characteristics of the Graph500 workloads running on this system with varying system scales and power states. Our experimental results are insightful for the design of energy-efficient many-core systems for data-intensive applications.
Regarding the non-negativity property of the magnitude spectrogram of speech signals, nonnegative matrix factorization (NMF) has obtained promising performance for speech separation by independently learning a diction...
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ISBN:
(纸本)9781479928941
Regarding the non-negativity property of the magnitude spectrogram of speech signals, nonnegative matrix factorization (NMF) has obtained promising performance for speech separation by independently learning a dictionary on the speech signals of each known speaker. However, traditional NM-F fails to represent the mixture signals accurately because the dictionaries for speakers are learned in the absence of mixture signals. In this paper, we propose a new transductive NMF algorithm (TNMF) to jointly learn a dictionary on both speech signals of each speaker and the mixture signals to be separated. Since TNMF learns a more descriptive dictionary by encoding the mixture signals than that learned by NMF, it significantly boosts the separation performance. Experiments results on a popular TIMIT dataset show that the proposed TNMF-based methods outperform traditional NMF-based methods for separating the monophonic mixtures of speech signals of known speakers.
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