The time-critical online contest environment calls for an elegant and precise management system to start a contest online. The management system should simultaneously follow three rules of security that are confidenti...
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The time-critical online contest environment calls for an elegant and precise management system to start a contest online. The management system should simultaneously follow three rules of security that are confidentiality, anonymity and fairness. We present in this paper a novel system named Secure Synchronized Reading (SSR) system as well as its corresponding security model according to the three rules. SSR can evoke a synchronized start for all competitors in a contest at the intended time by employing a Randomness-reused Identity-Based Encryption (RIBE) scheme. It can avoid huge differences among delivery delays of heterogeneous competitors and any false start by an adverse competitor. Consequently when an online contest begins, the SSR system performs quasi real-time with ignorable communication delays in the security model. As a complement, the analysis on the provable security of SSR is given finally, as well as a further analysis on the achievement of synchronization.
With the rapid growth of data, near-duplicate documents bearing high similarity are abundant. Elimination of near-duplicates can reduce storage cost and improve the quality of search indexes in data mining. A challeng...
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ISBN:
(纸本)9781479957125
With the rapid growth of data, near-duplicate documents bearing high similarity are abundant. Elimination of near-duplicates can reduce storage cost and improve the quality of search indexes in data mining. A challenging problem is to find near-duplicate records in large-scale collections efficiently. There have already been several efforts on implementing near-duplicate detection on different architectures. In this paper, a new implementation, using a special hash function namely simhash, is proposed to identify near-duplicate documents on CUDA enabled devices. Two mechanisms are designed to achieve higher performance, including swapping and dynamic allocating. Experimental results show that our parallel implementation outperforms the serial CPU version, achieving up to 18 times.
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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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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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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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.
The prevalence of multicore processors and virtualization technology enables parallel soft real-time applications to run in virtualized environment. However, current hypervisors do not provide adequate support for the...
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With the rapid development of intelligent video surveillance system for transportation, traditional single-camera-based video analysis has become insufficient. Many researches have focused on the non-overlapping multi...
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With the rapid development of intelligent video surveillance system for transportation, traditional single-camera-based video analysis has become insufficient. Many researches have focused on the non-overlapping multi-camera target tracking. However, the tracking precision and the computing overhead are still big obstacles. This paper proposes a novel vehicle tracking approach for non-overlapping multi-camera targets with data fusion by using minimum cost and maximum flow method. Structured information of moving targets is extracted and associated with other information such as motion time, the topology of camera network to solve targeted vehicle tracks. Besides, to improve the performance of the process, a parallelization algorithm for camera network topology partitioning is presented, which makes it possible for each sub-graph to track target independently in parallel. The experiment results show that the presented approach is able to perform target vehicle tracking analysis with high efficiency and accuracy.
Virtualization has become a prominent tool in data centers and is extensively leveraged in cloud environments: it enables multiple virtual machines (VMs) - with multiple operating systems and applications - to run wit...
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Virtualization has become a prominent tool in data centers and is extensively leveraged in cloud environments: it enables multiple virtual machines (VMs) - with multiple operating systems and applications - to run within a physical server. However, virtualization introduces the challenging issue of preserving the high disk utilization (i.e., reducing the seek delay and rotation overhead) when allocating disk resources to VMs. Exploiting spatial locality, a key technique for improving disk utilization and performance, faces additional challenges in the virtualized cloud because of the transparency feature of virtualization (hyper visors do not have the information about the access patterns of applications running within each VM). To this end, this paper contributes a novel disk I/O scheduling framework, named Pregather, to improve disk I/O efficiency through exposure and exploitation of the special spatial locality in the virtualized environment (regional and sub-regional spatial locality corresponds to the virtual disk space and applications' access patterns, respectively), thereby improving the performance of disk-intensive applications without harming the transparency feature of virtualization (without a priori knowledge of the applications' access patterns). The key idea behind Pregather is to implement an intelligent model to predict the access regularity of sub-regional spatial locality for each VM. We implement the Pregather disk scheduling framework and perform extensive experiments that involve multiple simultaneous applications of both synthetic benchmarks and a MapReduce application on Xen-based platforms. Our experiments demonstrate the accuracy of our prediction model and indicate that Pregather results in the high disk spatial locality and a significant improvement in disk throughput and application performance.
Mobile video editing systems need efficient streaming transmission and interactive operations. Rather than using a specialized protocol and stream format, the video editing system makes use of a generic mechanism base...
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ISBN:
(纸本)9781479934300
Mobile video editing systems need efficient streaming transmission and interactive operations. Rather than using a specialized protocol and stream format, the video editing system makes use of a generic mechanism based on chunks in the cloud computing environment. Chunks are in fixed-size and contains a mixture of scalar data and references to other chunks. Chunks allow programmers to expose large, but fine-grained, data structures over the network. The video editing system organizes video clips with simple data types including linked lists and search trees, allowing a client to retrieve. The mobile video editing system supports resource adaptive play-back and "live" streaming of real-time video as well as fast, frame-accurate seeking, bandwidth-efficient high-speed play-back, and compilation of editing decisions from a set of clips. All the editing functions are completed in the cloud center and the editing results are showed on the mobile devices. Evaluations indicate that our system uses less bandwidth than HTTP Live Streaming while providing better support for editing primitives.
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