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共 344 条记录，以下是121-130 订阅

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AutoBench: Finding Workloads That You Need Using Pluggable Hybrid Analyses

AutoBench: Finding Workloads That You Need Using Pluggable H...

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IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Yudi Zheng Andrea Rosà Luca Salucci Yao Li Haiyang Sun Omar Javed Lubomír Bulej Lydia Y. Chen Zhengwei Qi Walter Binder Faculty of Informatics Università della Svizzera italiana (USI) Lugano Switzerland Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China Cloud Server Technologies Group IBM Research Lab Zurich Switzerland

Researchers often rely on benchmarks to demonstrate feasibility or efficiency of their contributions. However, finding the right benchmark suite can be a daunting task - existing benchmark suites may be outdated, known to be flawed, or simply irrelevant for the proposed approach. Creating a proper benchmark suite is challenging, extremely time consuming, and also - unless it becomes widely popular - a thankless endeavor. In this paper, we introduce a novel approach to help researchers find relevant workloads for their experimental evaluation needs. Our approach relies on the huge number of open-source projects available in public repositories, and on unit testing having become best practice in software development. Using a repository crawler employing pluggable static and dynamic analyses for filtering and workload characterization, we allow users to automatically find projects with relevant workloads. Preliminary results presented here show that unit tests can provide a viable source of workloads, and that the combination of static and dynamic analyses improves the ability to identify relevant workloads that can serve as the basis for custom benchmark suites.

关键词： Benchmark testing Open source software Java Libraries Context

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Selecting most informative contributors with unknown costs for budgeted crowdsensing

Selecting most informative contributors with unknown costs f...

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International Workshop on Quality of Service

作者： Shuo Yang Fan Wu Shaojie Tang Tie Luo Xiaofeng Gao Linghe Kong Guihai Chen Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China Shanghai Jiao Tong University Shanghai CN Department of Information Systems University of Texas at Dallas. USA A*STAR Institute for Infocomm Research Singapore

Mobile crowdsensing has become a novel and promising paradigm in collecting environmental data. A critical problem in improving the QoS of crowdsensing is to decide which users to select to perform sensing tasks, in order to obtain the most informative data, while maintaining the total sensing costs below a given budget. The key challenges lie in (i) finding an effective measure of the informativeness of users' data, (ii) learning users' sensing costs which are unknown a priori, and (iii) designing efficient user selection algorithms that achieve low-regret guarantees. In this paper, we build Gaussian Processes (GPs) to model spatial locations, and provide a mutual information-based criteria to characterize users' informativeness. To tackle the second and third challenges, we model the problem as a budgeted multi-armed bandit (MAB) problem based on stochastic assumptions, and propose an algorithm with theoretically proven low-regret guarantee. Our theoretical analysis and evaluation results both demonstrate that our algorithm can efficiently select most informative users under stringent constraints.

关键词： Sensors Random variables Algorithm design and analysis Mutual information Gaussian processes Monitoring Gaussian distribution

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SYNC or ASYNC: Time to fuse for distributed graph-parallel computation 2015

SYNC or ASYNC: Time to fuse for distributed graph-parallel c...

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20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015

作者： Xie, Chenning Chen, Rong Guan, Haibing Zang, Binyu Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450332057

Large-scale graph-structured computation usually exhibits iterative and convergence-oriented computing nature, where input data is computed iteratively until a convergence condition is reached. Such features have led to the development of two different computation modes for graph-structured programs, namely synchronous (Sync) and asynchronous (Async) modes. Unfortunately, there is currently no in-depth study on their execution properties and thus programmers have to manually choose a mode, either requiring a deep understanding of underlying graph engines, or suffering from suboptimal performance. This paper makes the first comprehensive characterization on the performance of the two modes on a set of typical graph-parallel applications. Our study shows that the performance of the two modes varies significantly with different graph algorithms, partitioning methods, execution stages, input graphs and cluster scales, and no single mode consistently outperforms the other. To this end, this paper proposes Hsync, a hybrid graph computation mode that adaptively switches a graph-parallel program between the two modes for optimal performance. Hsync constantly collects execution statistics on-the-fly and leverages a set of heuristics to predict future performance and determine when a mode switch could be profitable. We have built online sampling and offline profiling approaches combined with a set of heuristics to accurately predicting future performance in the two modes. A prototype called PowerSwitch has been built based on PowerGraph, a state-of-the-art distributed graph-parallel system, to support adaptive execution of graph algorithms. On a 48-node EC2-like cluster, PowerSwitch consistently outperforms the best of both modes, with a speedup ranging from 9% to 73% due to timely switch between two modes. Copyright 2015 ACM.

关键词： Graphic methods

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DaSS: Dynamic time slice scheduler for virtual machine monitor 1

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： Ma, Ruhui Li, Jian Lin, Liwei Guan, Haibing Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

I/O performance is an important factor in virtualization technology. However, the hypervisor and the scheduler brings impact on the I/O performance, since the scheduler considers I/O-intensive Virtual Machine (VM) and CPU-intensive VM as the same VM which results in scheduling latency. Most researches address this I/O problem but they do not take dynamic workload into consideration, leaving the facts that their solutions do not work well when the workload is volatile. In this paper, we present a Dynamic time Slice Scheduler (DaSS) as a software solution which brings a significant improvement on the I/O performance. In order to maintain good flexibility and availability, DaSS requires no modification on the Guest OS but only a few changes on the VMM. We implement the prototype on Xen 4. 3. 0 and conduct detailed evaluations on network benchmarks. Our experimental results show that DaSS increases I/O throughput by nearly 40%. © Springer International Publishing Switzerland 2015.

关键词： Virtual machine

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Practical private shortest path computation based on Oblivious Storage

Practical private shortest path computation based on Oblivio...

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International Conference on Data Engineering

作者： Dong Xie Guanru Li Bin Yao Xuan Wei Xiaokui Xiao Yunjun Gao Minyi Guo Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China School of Computer Engineering Nanyang Technological University Singapore College of Computer Science Zhejiang University China

ISBN: (纸本)9781509020218

As location-based services (LBSs) become popular, location-dependent queries have raised serious privacy concerns since they may disclose sensitive information in query processing. Among typical queries supported by LBSs, shortest path queries may reveal information about not only current locations of the clients, but also their potential destinations and travel plans. Unfortunately, existing methods for private shortest path computation suffer from issues of weak privacy property, low performance or poor scalability. In this paper, we aim at a strong privacy guarantee, where the adversary cannot infer almost any information about the queries, with better performance and scalability. To achieve this goal, we introduce a general system model based on the concept of Oblivious Storage (OS), which can deal with queries requiring strong privacy properties. Furthermore, we propose a new oblivious shuffle algorithm to optimize an existing OS scheme. By making trade-offs between query performance, scalability and privacy properties, we design different schemes for private shortest path computation. Eventually, we comprehensively evaluate our schemes upon real road networks in a practical environment and show their efficiency.

关键词： Privacy Roads Servers Outsourcing Scalability Protocols Computational modeling

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Crowdsourcing sensing to smartphones: A randomized auction approach 23

Crowdsourcing sensing to smartphones: A randomized auction a...

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23rd IEEE International Symposium on Quality of Service, IWQoS 2015

作者： Li, Juan Zhu, Yanmin Hua, Yiqun Yu, Jiadi Shanghai Key Lab of Scalable Computing and Systems Shanghai China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781467371131

Mobile crowdsourcing to smartphones has emerged as a compelling paradigm for collecting sensing data over a vast area for various monitoring applications. It is of paramount importance for mobile crowdsourcing to provide incentive mechanisms. State-of-the-art auction mechanisms for mobile crowdsourcing are deterministic in the sense that given the real costs of the smartphone users, a fixed set of smartphone users are recruited for performing sensing tasks. This leads to serious issues including reduced diversity of sensing devices and starvation of some users. In this paper, we propose an approximate-truthful randomized combinatorial auction mechanism for the social cost minimization problem, which is NP-hard. We design an approximate task allocation algorithm that is near optimal with polynomial-time complexity and use it as a block to construct the whole randomized auction mechanism. We carry out numerical studies and show that our randomized auction mechanism achieves approximate truthfulness, individual rationality, and high computation efficiency. Moreover, the proposed mechanism increases diversity of devices and prevents starvation of some smartphones. © 2015 IEEE.

关键词： Smartphones

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NUMA-aware graph-structured analytics 2015

NUMA-aware graph-structured analytics

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20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015

作者： Zhang, Kaiyuan Chen, Rong Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China

ISBN: (纸本)9781450332057

Graph-structured analytics has been widely adopted in a number of big data applications such as social computation, web-search and recommendation systems. Though much prior research focuses on scaling graph-analytics on distributed environments, the strong desire on performance per core, dollar and joule has generated considerable interests of processing large-scale graphs on a single server-class machine, which may have several terabytes of RAM and 80 or more cores. However, prior graph-analytics systems are largely neutral to NUMA characteristics and thus have suboptimal performance. This paper presents a detailed study of NUMA characteristics and their impact on the efficiency of graph-analytics. Our study uncovers two insights: 1) either random or interleaved allocation of graph data will significantly hamper data locality and parallelism;2) sequential inter-node (i.e., remote) memory accesses have much higher bandwidth than both intra- and inter-node random ones. Based on them, this paper describes Polymer, a NUMA-aware graph-analytics system on multicore with two key design decisions. First, Polymer differentially allocates and places topology data, application-defined data and mutable runtime states of a graph system according to their access patterns to minimize remote accesses. Second, for some remaining random accesses, Polymer carefully converts random remote accesses into sequential remote accesses, by using lightweight replication of vertices across NUMA nodes. To improve load balance and vertex convergence, Polymer is further built with a hierarchical barrier to boost parallelism and locality, an edge-oriented balanced partitioning for skewed graphs, and adaptive data structures according to the proportion of active vertices. A detailed evaluation on an 80-core machine shows that Polymer often outperforms the state-of-the-art single-machine graph-analytics systems, including Ligra, X-Stream and Galois, for a set of popular real-world and synthetic grap

关键词： Random access storage

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Powerlyra: Differentiated graph computation and partitioning on skewed graphs 15

Powerlyra: Differentiated graph computation and partitioning...

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10th European Conference on Computer systems, EuroSys 2015

作者： Chen, Rong Shi, Jiaxin Chen, Yanzhe Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China

ISBN: (纸本)9781450332385

Natural graphs with skewed distribution raise unique challenges to graph computation and partitioning. Existing graph-parallel systems usually use a "one size fits all" design that uniformly processes all vertices, which either suffer from notable load imbalance and high contention for high-degree vertices (e.g., Pregel and Graphlab), or incur high communication cost and memory consumption even for low-degree vertices (e.g., PowerGraph and GraphX). In this paper, we argue that skewed distribution in natural graphs also calls for differentiated processing on highdegree and low-degree vertices. We then introduce Power-Lyra, a new graph computation engine that embraces the best of both worlds of existing graph-parallel systems, by dynamically applying different computation and partitioning strategies for different vertices. PowerLyra further provides an efficient hybrid graph partitioning algorithm (hybrid-cut) that combines edge-cut and vertex-cut with heuristics. Based on PowerLyra, we design locality-conscious data layout optimization to improve cache locality of graph accesses during communication. PowerLyra is implemented as a separate computation engine of PowerGraph, and can seamlessly support various graph algorithms. A detailed evaluation on two clusters using graph-analytics and MLDM (machine learning and data mining) applications show that PowerLyra outperforms PowerGraph by up to 5.53X (from 1.24X) and 3.26X (from 1.49X) for real-world and synthetic graphs accordingly, and is much faster than other systems like GraphX and Giraph, yet with much less memory consumption. A porting of hybrid-cut to GraphX further confirms the efficiency and generality of PowerLyra. Copyright © 2015 ACM 978-1-4503-3238-5/15/04 $15.00.

关键词： Data mining

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Omnidirectional chargability with directional antennas

Omnidirectional chargability with directional antennas

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International Conference on Network Protocols

作者： Haipeng Dai Xiaoyu Wang Alex X. Liu Fengmin Zhang Yang Zhao Guihai Chen State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu CHINA Department of Computer Science and Engineering Michigan State University East Lansing MI USA Shanghai key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai CHINA

ISBN: (纸本)9781509032822

Wireless Power Transfer (WPT) has received more and more attentions because of its convenience and reliability. In this paper, we first propose the notion of omnidirectional charging by which an area is omnidirectionally charged if a device with directional antennas at any position in the area with any orientation can be charged by directional chargers with power being no smaller than a given threshold. We present our empirical charging model based on field experimental results using off-the-shelf WPT products. Next, we consider the problem of detecting whether the target area achieves omnidirectional charging given a deterministic deployment of chargers. We develop piecewise constant approximation and area discretization techniques to partition the target area into subareas and approximate powers from chargers as constants. Then we propose the Minimum Coverage Set extraction technique which reduces the continuous search space to a discrete one and thereby allows a fast detection algorithm. Moreover, we consider the problem of determining the probability that the target area achieves omnidirectional charging given a random deployment of chargers. We first replace the target area by grid points on triangular lattices to reduce the search space from infinite to finite, then approximate chargers' power with reasonable relaxation, and derive an upper bound of the omnidirectional charging probability. Finally, we conduct both simulation and field experiments, and the results show that our algorithm outperforms comparison algorithms by at least 120%, and the consistency degree of our theoretical results and field experimental results is larger than 93.6%.

关键词： Wireless sensor networks Wireless communication Directional antennas Adaptation models Joining processes Conferences Protocols

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Indexing multi-dimensional data in modular data centers 26th

Indexing multi-dimensional data in modular data centers

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26th International Conference on Database and Expert systems Applications, DEXA 2015

作者： Gao, Libo Zhang, Yatao Gao, Xiaofeng Chen, Guihai Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9783319228518

Providing efficient multi-dimensional indexing is critically important to improve the overall performance of the cloud storage system. To achieve efficient querying service, the indexing scheme should guarantee lower routing cost and less false positive. In this paper, we propose RB-Index, a distributed multi-dimensional indexing scheme in modular data centers with Bcube topology. RB-Index is a two-layer indexing scheme, which integrates Bcube-based routing protocol and R-tree-based indexing technology. In its lower layer, each server in the network indexes the local data with R-tree, while in the upper layer the global index is distributed across different servers in the network. Based on the characteristics of Bcube, we build several indexing spaces and propose the way to map servers into the indexing spaces. The dimension of these indexing spaces are dynamically selected according to both the data distribution and the query habit. Index construction and query algorithms are also introduced. We simulate a three-level Bcube to evaluate the efficiency of our indexing scheme and compare the performance of RB-Index with RT-CAN, a similar design in P2P network. © Springer International Publishing Switzerland 2015.

关键词： Digital storage

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