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LSShare: an efficient multiple query optimization system in the cloud

Distributed and Parallel Databases 2014年第4期32卷 583-605页

作者： Xing Ge Bin Yao Minyi Guo Changliang Xu Jingyu Zhou Chentao Wu Guangtao Xue Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Alibaba Cloud Computing Company Hangzhou China

Multiple query optimization (MQO) in the cloud has become a promising research direction due to the popularity of cloud computing, which runs massive data analysis queries (jobs) routinely. These CPU/IO intensive analysis queries are complex and time-consuming but share common components. It is challenging to detect, share and reuse the common components among thousands of SQL-like queries. Previous solutions to MQO, heuristic or genetic based, are not appropriate for the large growing query set situation. In this paper, we develop a sharing system called LSShare using our proposed Lineage-Signature approach. By LSShare, we can efficiently solve the MQO problem in a recurring query set situation in the cloud. Our system has been prototyped in a distributed system built for massive data analysis based on Alibaba’s cloud computing platform ( http://***/ ). Experimental results on real data sets demonstrate the efficiency and effectiveness of the proposed approach.

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New tight upper bounds on the capacity for general deterministic dissemination in wireless ad hoc networks

New tight upper bounds on the capacity for general determini...

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IEEE International Conference on Performance, computing and Communications (IPCCC)

作者： Cheng Wang Jieren Zhou Tianci Liu Lu Shao Huiya Yan Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science Tongji University Shanghai China School of Software Tsinghua University Beijing China Mathematics Department University of Wisconsin-La Crosse La Crosse WI

In this paper, we study capacity scaling laws of the deterministic dissemination (DD) in random wireless networks under the generalized physical model (GphyM). This is truly not a new topic. Our motivation to readdress this issue is two-fold: Firstly, we aim to propose a more general result to unify the network capacity for general homogeneous random models by investigating the impacts of different parameters of the system on the network capacity. Secondly, we target to close the open gaps between the upper and the lower bounds on the network capacity in the literature. We derive the general upper bounds on the capacity for the arbitrary case of (λ, nd, ns) by introducing the Poisson Boolean model of continuum percolation, where λ, nd, and ns are the general node density, the number of destinations for each session, and the number of sessions, respectively. We prove that the derived upper bounds are tight according to the existing general lower bounds constructed in the literature.

关键词： Roads Mathematics Unicast Signal to noise ratio Interference

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Social welfare maximization in participatory smartphone sensing

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computer Networks 2014年 73卷 195-209页

作者： Tong Liu Yanmin Zhu Department of Computer Science and Engineering Shanghai Jiao Tong University China Shanghai Key Lab of Scalable Computing and Systems China

Participatory smartphone sensing has lately become more and more popular as a new paradigm for performing large-scale sensing, in which each smartphone contributes its sensed data for a collaborative sensing application. Most existing studies consider that smartphone users are strictly strategic and completely rational, which try to maximize their own payoffs. A number of incentive mechanisms are designed to encourage smartphone users to participate, which can achieve only suboptimal system performance. However, few existing studies can maximize a system-wide objective which takes both the platform and smartphone users into account. This paper focuses on the crucial problem of maximizing the system-wide performance or social welfare for a participatory smartphone sensing system. There are two great challenges. First , the social welfare maximization cannot be realized on the platform side because the cost of each user is private and unknown to the platform in reality. Second , the participatory sensing system is a large-scale real-time system due to the huge number of smartphone users who are geo-distributed in the whole world. A price-based decomposition framework is proposed in our previous work (Liu and Zhu, 2013), in which the platform provides a unit price for the sensing time spent by each user and the users return the sensing time via maximizing the monetary reward. This pricing framework is an effective incentive mechanism as users are motivated to participate for monetary rewards from the platform. In this paper, we propose two distributed solutions, which protect users’ privacy and achieve optimal social welfare. The first solution is designed based on the Lagrangian dual decomposition. A poplar iterative gradient algorithm is used to converge to the optimal value. Moreover, this distributed method is interpreted by our pricing framework. In the second solution, we first equivalently convert the original problem to an optimal pricing problem. Then, a distr

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DIARY: A Differentially Private and Approximately Revenue Maximizing Auction Mechanism for Secondary Spectrum Markets

DIARY: A Differentially Private and Approximately Revenue Ma...

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IEEE Global Communications Conference

作者： Chunchun Wu Zuying Wei Fan Wu Guihai Chen Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781479935130

It is urgent to solve the contradiction between limited spectrum resources and the increasing demand from the ever-growing wireless networks. Spectrum redistribution is a powerful way to mitigate the situation of spectrum scarcity. In contrast to existing truthful mechanisms for spectrum redistribution which aim to maximize the spectrum utilization and social welfare, we propose DIARY in this paper, which not only achieves approximate revenue maximization, but also guarantees bid privacy via differential privacy. Extensive simulations show that DIARY has substantial competitive advantages over existing mechanisms.

关键词： Privacy Vectors Resource management Information systems Security Interference Cost accounting

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A Self-Learning Clustering Algorithm Based on Clustering Coefficient

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8786卷 79-94页

作者： Zhong, Mingjie Ding, Zhijun Sun, Haichun Wang, Pengwei The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai200092 China Department of Computer Science University of Pisa Pisa56127 Italy

This paper presents a novel clustering algorithm based on clustering coefficient. It includes two steps: First, k-nearest-neighbor method and correlation convergence are employed for a preliminary clustering. Then, the results are further split and merged according to intra-class and inter-class concentration degree based on clustering coefficient. The proposed method takes correlation between each other in a cluster into account, thereby improving the weakness existed in previous methods that consider only the correlation with center or core data element. Experiments show that our algorithm performs better in clustering compact data elements as well as forming some irregular shape clusters. It is more suitable for applications with little prior knowledge, e.g. hotspots discovery. © Springer International Publishing Switzerland 2014.

关键词： Clustering algorithms

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Geographic routing based on predictive locations in vehicular ad hoc networks

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EURASIP Journal on Wireless Communications and Networking 2014年第1期2014卷 1-9页

作者： Yanmin Zhu Ruobing Jiang Jiadi Yu Zhi Li Minglu Li Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Lab of Scalable Computing and Systems Shanghai China

Many geographic routing algorithms have been proposed for vehicular ad hoc networks (VANETs), which have the strength of not maintaining any routing structures. However, most of which rely on the availability of accurate real-time location information. It is well known that vehicles can be intermittently connected with other vehicles. Thus, in such networks, it is difficult or may incur considerable cost to retrieve accurate locations of moving vehicles. Furthermore, the location information of a moving vehicle available to other vehicles is usually time-lagged since it is constantly moving over time. Fortunately, we observe that the short-term future locations of vehicles can be predicted. Based on the important observation, we propose a novel approach for geographic routing which exploits the predictive locations of vehicles. Thus, we have developed a prediction technique based on the current speed and heading direction of a vehicle. As a result, the request frequency of location updates can be reduced. In addition, we propose two forwarding strategies and three buffer management strategies. We have performed extensive simulations based on real vehicular GPS traces collected from around 4,000 taxis in shanghai, China. Simulation results clearly show that geographic routing based on predictive locations is viable and can significantly reduce the cost of location updates.

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Pinso: Precise Isolation of Concurrency Bugs via Delta Triaging

Pinso: Precise Isolation of Concurrency Bugs via Delta Triag...

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International Conference on Software Maintenance (ICSM)

作者： Bo Liu Zhengwei Qi Bin Wang Ruhui Ma Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai CN

Concurrent programs are known to be difficult to test and maintain. These programs often fail because of concurrency bugs caused by non-deterministic interleavings among shared memory accesses. Even though a concurrency bug can be detected, it is still hard to isolate the root cause of the bug, due to the challenge in understanding the complex thread interleavings or schedules. In this paper, we propose a practical and precise isolation technique for concurrent bugs called Pinso that seeks to exploit the non-deterministic nature of concurrency bugs and accurately find the root causes of program error, to further help developers maintain concurrent programs. Pinso profiles runtime inter-thread interleavings based on a set of summarized memory access patterns, and then, isolates suspicious interleaving patterns in the triaging phase. Using a filtration-oriented scheduler, Pinso effectively eliminates false positives that are irrelevant to the bug. We evaluate Pinso with 11 real-world concurrency bugs, including single- and multi-variable violation, from sever/desktop concurrent applications (MySQL, Apache, and several others). Experiments indicate that our tool accurately isolates the root causes of all the bugs.

关键词： Concurrent computing computer bugs Instruction sets Schedules Testing History Synchronization

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Distributed compressive data gathering in low duty cycled wireless sensor networks

Distributed compressive data gathering in low duty cycled wi...

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IEEE International Conference on Performance, computing and Communications (IPCCC)

作者： Yimao Wang Yanmin Zhu Ruobing Jiang Juan Li Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai Key Lab of Scalable Computing and Systems

ISBN: (纸本)9781479975761

Wireless sensor networks (WSNs) are gaining popularity in practical monitoring and surveillance applications. Because of the limited energy of sensor nodes, many WSNs work in a low duty cycle mode to effectively extend their network lifetime. However, low duty cycling also decreases transmission efficiency and makes data gathering more challenging. By exploiting the redundancy of in real sensing data, we propose a novel and distributed approach for data gathering in wireless sensor networks, employing the compressed sensing theory. Instead of selecting a fixed sink, all data can be retrieved from an arbitrary node within the network. Moreover, we use sequential observations to dynamically fit the sparsity of various data sets. With extensive simulations, we show that our approach is efficient with tunable accuracy in different node duty cycles.

关键词： Wireless sensor networks Compressed sensing Sensors Estimation Monitoring Accuracy Entropy

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A distributed spectrum sharing algorithm in cognitive radio networks

A distributed spectrum sharing algorithm in cognitive radio ...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Wei Sun Jiadi Yu Tong Liu Shanghai Key Lab of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University

In this paper we study a social welfare maximization problem for spectrum sharing in cognitive radio networks. To fully use the spectrum resource, the spectrum owned by the licensed primary user (PU) can be leased to secondary users (SUs) for transmitting data. We first formulate the social welfare of a cognitive radio network, considering the cost for the primary user sharing spectrum and the utility gained for secondary users transmitting data. The social welfare maximization is a convex optimization, which can be solved by standard methods in a centralized manner. However, the utility function of each secondary user always contains the private information, which leads to the centralized methods disabled. To overcome this challenge, we propose an iterative distributed algorithm based on a pricing-based decomposition framework. It is theoretically proved that our proposed algorithm converges to the optimal solution. Numerical simulation results are presented to show that our proposed algorithm achieves optimal social welfare and fast convergence speed.

关键词： Cognitive radio Distributed algorithms Bandwidth Pricing Resource management Cost function Convergence

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An efficient privacy-preserving compressive data gathering scheme in WSNs 1

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

作者： Xie, Kun Ning, Xueping Wang, Xin Wen, Jigang Liu, Xiaoxiao He, Shiming Zhang, Daqiang College of Computer Science and Electronics Engineering Hunan University Changsha410082 China The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommmunications Beijing100876 China Department of Electrical and Computer Engineering State University of New York at Stony Brook New York11790 United States Institute of Computing Technology Chinese Academy of Sciences Beijing100080 China State Grid HuNan Electric Power Company Research Insitute Changsha410000 China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China School of Software Engineering Tongji University Shanghai201804 China

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

Due to the strict energy limitation and the common vulnerability of WSNs, providing efficient and security data gathering in WSNs becomes an essential problem. Compressive data gathering, which is based on the recent breakthroughs in compressive sensing theory, has been proposed as a viable approach for data gathering in WSNs at low communication overhead. Nevertheless, compressive data gathering is susceptible to various attacks due to the open wireless medium. To thwart traffic analysis/flow tracing and realize privacy preservation, this paper proposes a novel Efficient Privacy-Preserving Compressive Data Gathering Scheme which exploits homomorphic encryption functions in compressive data gathering. With homomorphic encryption on the compressive sensing encoded sensory reading messages, the proposed scheme offers two significant privacy-preserving features, message flow untraceability and message content confidentiality, for efficiently thwarting the traffic analysis attacks. Extensive performance evaluations and security analysis demonstrate the validity and efficiency of the proposed scheme. © Springer International Publishing Switzerland 2015.

关键词： Compressed sensing

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