With the development of desktop virtualization technology, more and more companies begins to deploy virtual desktop. Traditional NAS and SAN storages can only support small-scale users due to network bandwidth limit a...
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In virtualized systems, allocation and scheduling of resources shared among multiple virtual machines faces challenges such as autonomy, isolation and high workload dynamics. The multiplexing and consolidation nature ...
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In virtualized systems, allocation and scheduling of resources shared among multiple virtual machines faces challenges such as autonomy, isolation and high workload dynamics. The multiplexing and consolidation nature of virtualized systems also raise issues such as interference and conflicts among various virtual machine instances. Therefore traditional resource allocation strategy can't achieve good performance without modifications according to these particular characteristics in virtualized systems. In this paper we use a stochastic model to characterize the resources (especially CPU) and workload dynamics. Then we use a weighted priority based service differentiation strategy to allocate resources in contending conditions to provide performance guarantees as well as load balance and fairness. In the proposed algorithms user behavior and workloads are characterized through the historical and real time performance profiling and estimation from hosted agents within individual Virtual Machines. The resources are allocated according to the demand as well as the performance of the targeted Virtual Machines based on the Sufferage aggregation and performance feedback. Experiments on a real Xen based virtualization environment with 20 Virtual Machines are conducted and evaluated for accuracy, efficiency, sensitivity, and overhead. The results show that the performance feedback based allocation can achieve a higher SLA satisfaction rate as 97.1%, a lower load imbalance index as 18.7%. The performance feedback based allocator uses 14.06% less CPU time for CPU-intensive applications and reduces 45.59% I/O wait time in disk contention environments. The results also show that the feedback based algorithm is valid, effective and scalable for implementation in real virtualized environments.
Peer-to-Peer (P2P) networks have been shown to be a promising approach to provide instant voice services over the Internet for its potential high scalability. However, for one paired peers, how to efficiently transmit...
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Hybrid memory systems composed of dynamic random access memory(DRAM)and Non-volatile memory(NVM)often exploit page migration technologies to fully take the advantages of different memory *** previous proposals usually...
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Hybrid memory systems composed of dynamic random access memory(DRAM)and Non-volatile memory(NVM)often exploit page migration technologies to fully take the advantages of different memory *** previous proposals usually migrate data at a granularity of 4 KB pages,and thus waste memory bandwidth and DRAM *** this paper,we propose Mocha,a non-hierarchical architecture that organizes DRAM and NVM in a flat address space physically,but manages them in a cache/memory *** the commercial NVM device-Intel Optane DC Persistent Memory Modules(DCPMM)actually access the physical media at a granularity of 256 bytes(an Optane block),we manage the DRAM cache at the 256-byte size to adapt to this feature of *** design not only enables fine-grained data migration and management for the DRAM cache,but also avoids write amplification for Intel Optane *** also create an Indirect Address Cache(IAC)in Hybrid Memory Controller(HMC)and propose a reverse address mapping table in the DRAM to speed up address translation and cache ***,we exploit a utility-based caching mechanism to filter cold blocks in the NVM,and further improve the efficiency of the DRAM *** implement Mocha in an architectural *** results show that Mocha can improve application performance by 8.2%on average(up to 24.6%),reduce 6.9%energy consumption and 25.9%data migration traffic on average,compared with a typical hybrid memory architecture-HSCC.
Replica management has become a hot research topic in storage systems. This paper presents a dynamic replica management strategy based on response time, named RTRM. RTRM strategy consists of replica creation, replica ...
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MapReduce programming model is emerging as an efficient tool for data-intensive applications. Hadoop, an open-source implementation of MapReduce, has been widely adopted and experienced by both academia and enterprise...
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ISBN:
(纸本)9781605589428
MapReduce programming model is emerging as an efficient tool for data-intensive applications. Hadoop, an open-source implementation of MapReduce, has been widely adopted and experienced by both academia and enterprise. Recently, lots of efforts have been done on improving the performance of MapReduce system and on analyzing the MapReduce process based on the log files generated during the Hadoop execution. Visualizing log files seems to be a very useful tool to understand the behavior of the Hadoop process. In this paper, we present MRScope, a real-time MapReduce tracing tool. MR-Scope provides a real-time insight of the MapReduce process, including the ongoing progress of every task hosted in Task Tracker. In addition, it displays the health of the Hadoop cluster data nodes, the distribution of the file system's blocks and their replicas and the content of the different block splits of the file system. We implement MR-Scope in native Hadoop 0.1. Experimental results demonstrat that MR-Scope's overhead is less than 4% when running wordcount benchmark. Copyright 2010 ACM.
CS (Conflict Serializability) is a recently proposed relaxer correctness criterion that can increase transactional memory's parallelism. DDA (Distributed Dependency-Aware) model is currently proposed to implement ...
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Agent-based grid data loading method aims at integrating heterogeneous hospitals' information systems into a medical information exchange platform based on grid middleware. It collects distributed data sets for de...
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Current grid information service is centralized or hierarchical and proves inefficient as grid scale rapidly increases. The introduction of P2P techniques into grids breaks an encouraging path. However, frequent join ...
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ISBN:
(纸本)9781605580777
Current grid information service is centralized or hierarchical and proves inefficient as grid scale rapidly increases. The introduction of P2P techniques into grids breaks an encouraging path. However, frequent join and departure of resource nodes require strong self-organization capacity of system to maintain their rigid structure. Moreover, arranging identifier space for P2P nodes is knotty and has great impact on system performance. If the identifier space is too large, some nodes will be overloaded. On the contraiy, small identifier space will bring the same problem as millennium bug. To address the issues, this paper proposes a scalable DHT-based (Distributed Hash Table) Information Service (DIS) for grid system, which organizes grid resources into a DHT ring based on VO (Virtual Organization). To save the identifier space while retaining the scalability and system performance, only stable VOs can join DIS via a new DHT node, whereas volatile VOs join DIS through being the sub-domain of other VO. Experimental results show that DIS provides rapid resource query, strong scalability and high throughput, meanwhile avoiding the key node failure as well as the bottleneck problem. Copyright 2008 ACM.
A large-scale image retrieval system for the WWW, named VAST (VisuAl & SemanTic image search), is presented in this paper. Based on the existing inverted file and visual feature clusters, we form a semantic networ...
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ISBN:
(纸本)9788955191356
A large-scale image retrieval system for the WWW, named VAST (VisuAl & SemanTic image search), is presented in this paper. Based on the existing inverted file and visual feature clusters, we form a semantic network on top of the keyword association on the visual feature clusters. The system is able to automatically combine keyword and visual features for retrieval by the semantic network The combination is automatic, simple, and very fast, which is suitable for large-scale web dataset Meanwhile, the retrieval takes advantage of the semantic contents of the images in addition to the low-level features, which remarkably improves the retrieval precision. The experimental results demonstrate the superiority of the system.
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