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

作者： Jiang, Wenbin Lu, Zhiwei Jin, Hai Chi, Ye Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319271361

In order to ensure recognition accuracy, intelligent traffic video tracking system usually requires various types of information. Therefore, multi-features fusion becomes a good choice. In this paper, a new recognition approach for vehicle types based multi-feature fusion is proposed, which is used for vehicle tracking in a multi-camera traffic system. An improved Canny operator is presented for edge detection. SURF (Speeded Up Robust Features) is used for local feature extraction. To improve the performance of distance cal- culation between features, a refined method based on Hellinger kernel is put forward. A position constraint rule is applied to reduce unnecessary fake matchings. Finally, the information of vehicle types combined with LBP (Local Binary Pattern), HOG (Histogram of Oriented Gradients) is used for a multi-camera vehicle tracking platform, which adopts Hadoop to realize the parallel computing of the system. Experimental results show that the proposed approach has good performance for the platform. © Springer International Publishing Switzerland 2015.

关键词： Local binary pattern

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HRF: A resource allocation scheme for moldable jobs 15

HRF: A resource allocation scheme for moldable jobs

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12th ACM International Conference on computing Frontiers, CF 2015

作者： Wu, Song Tuo, Qiong Jin, Hai Yan, Chuxiong Weng, Qizheng Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450333580

Moldable jobs, which allow the number of allocated processors to be adjusted before running in clusters, have attracted increasing concern in parallel job scheduling research. Compared with traditional rigid jobs where the number of allocated processors is fixed, moldable jobs are more flexible and therefore have more potential for improving their average turnaround time (a crucial metric to describe performance of jobs in a cluster). Average turnaround time of moldable jobs depends greatly on resource allocation schemes. Unfortunately, existing schemes do not perform well in reducing average turnaround time, either because they only consider a single job's turnaround time instead of the average turnaround time of all jobs, or because they just aim at fairness between short and long jobs instead of their average turnaround time. In this paper, we investigate how resource allocation affects the average turnaround time of moldable jobs in clusters, and propose a scheme named HRF (highest revenue first), which allocates processors according to the highest revenue of shortening runtime. In our simulations, experimental results show that HRF can reduce average turnaround time up to 71% when compared with state-of-the-art schemes. © Copyright 2015 ACM.

关键词： Resource allocation

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A data-centric tool to improve the performance of multithreaded program on NUMA 15th

A data-centric tool to improve the performance of multithrea...

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

作者： Zeng, Dan Zhu, Liang Liao, Xiaofei Jin, Hai Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319271392

Non-uniform memory access (NUMA) is one of the main architectures of today’s high-performance server. The key feature of NUMA is the non-uniformity of access latency. Access from a processor to attached memory is faster, and it also reduces the possibility of causing contention on interconnect links and memory controller. Multithreaded programs may experience high memory latency without careful placement of data and thread. Thus, it is necessary to develop a tool to identify and help ameliorate NUMA problems. In this paper, we present a data-centric tool to analyze the performance of multithreaded programs on NUMA architectures and provide advices on how to improve the performance. This paper describes the design and implementation of the tool. The tool is evaluated on Linux using three benchmark applications, and the evaluation shows how this tool helps to identify costly variables and choose optimization methods. The result shows performance improvement of up to 51.92%. © 2015 Springer International Publishing Switzerland.

关键词： Benchmarking

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Robust image document authentication code with autonomous biometrie key generation, selection, and updating in cloud environment 11

Robust image document authentication code with autonomous bi...

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11th International Conference on Information Assurance and Security, IAS 2015

作者： Abduljabbar, Zaid Ameen Jin, Hai Hussien, Zaid Alaa Yassin, Ali A. Hussain, Mohammed Abdulridha Abbdal, Salah H. Zou, Deqing Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China University of Basrah Basrah Iraq Southern Technical University Basrah Iraq

ISBN: (纸本)9781467387156

Recently, security issues are obstructing the development and using of cloud computing services. Authentication and integrity play an important role in the cloud security, and numerous concerns have been raised to recognize any tampering with exchanges of the image document between two entities (sender and receiver) within the cloud environment. However, none of the existing solutions reduce the probability of known attacks by combining cryptographic hash function with a strong factor that should be periodically changed. For this reason, in this paper we propose a robust one-time image document authentication scheme based on combining non-interactive onetime biometric key and a robust wavelet-based cryptographic hashing scheme. The result of the combination is one-time image document authentication code (OMAC). OMAC is hidden in an image document as a cover image through reversible data embedding steganography. The proposed scheme has several important security attributes, such as key agreement, biometric key management, robust OMAC, invulnerability, and efficiency. In biometric key management, key generation, key selection, and key update algorithms are performed autonomously by the sender and the receiver;thus, no interaction between them is needed. © 2015 IEEE.

关键词： Authentication

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AutoCSD: Automatic cloud system deployment in data centers 2nd

AutoCSD: Automatic cloud system deployment in data centers

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2nd International Conference on Cloud computing and Big Data, CloudCom-Asia 2015

作者： Xie, Tao Chen, Haibao Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China School of Computer and Information Engineering Chuzhou University Chuzhou239000 China

ISBN: (纸本)9783319284293

It is a huge challenge to deploy a cloud computing system in large-scale data centers. In order to help resolve this issue, we propose an automatic cloud system deployment approach with the characteristics of reliability, availab.lity, and load balance. Specifically, we use workflow to deal with the dependencies among the automatic deployment processes of a cloud system. We also design a failover mechanism to avoid the single point failure of the deployment server. Besides, we adopt a load balancing algorithm to solve the bottleneck problem of deploying a cloud system. We implement a prototype, and evaluate it with 16 physical nodes as well as a virtualized environment with 160 virtual machines. Experimental results show that the average deployment time under our approach is lower than that with traditional deployment methods. In addition, it achieves a cloud system deployment success ratio of up to 90%, even in the high-concurrency environment. © Springer International Publishing Switzerland 2015.

关键词： Cloud computing

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MR-COF: A genetic MapReduce configuration optimization framework 15th

MR-COF: A genetic MapReduce configuration optimization frame...

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

作者： Liu, Chao Zeng, Deze Yao, Hong Hu, Chengyu Yan, Xuesong Fan, Yuanyuan Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan430074 China China Services Computing Technology and System Lab and Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319271392

Hadoop/MapReduce has emerged as a de facto programming framework to explore cloud-computing resources. Hadoop has many configuration parameters, some of which are crucial to the performance of MapReduce jobs. In practice, these parameters are usually set to default or inappropriate values. This severely limits system performance (e.g., execution time). Therefore, it is essential but also challenging to investigate how to automatically tune these parameters to optimize MapReduce job performance. In this paper, we propose an automatic MapReduce configuration optimization framework named as MR-COF. By monitoring and analyzing the runtime behavior, the framework adopts a cost-based performance prediction model that predicts the MapReduce job performance. In addition, we design a genetic search algorithm which iteratively tunes parameters in order to find out the best one. Testbed-based experimental results show that the average MapReduce job performance is increased by 35% with MR-COF compared to the default configuration. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

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LS-AMS: An Adaptive Indexing Structure for Realtime Search on Microblogs

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IEEE Transactions on Big Data 2015年第4期1卷 125-137页

作者： Zhao, Feng Liu, Jun Zhou, Jingyu Jin, Hai Yang, Laurence T. Services Computing Technology and System Lab Big Data Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technolgoy Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computer Science St. Francis Xavier University Canada

Indexing microblogs for realtime search is challenging, because new microblogs are created at tremendous speed, and user query requests keep constantly changing. To guarantee user obtain complete query results, micro-blogging site maintains huge indices which leads to index fragmentation or extra merging overhead during realtime search. This paper proposes an efficient Log-Structured index structure with Adaptive Merging Strategy (LS-AMS) for realtime search on microblogs. LS-AMS structure consists of an inverted index buffer and a sequence of dynamically adjustable index packages with exponentially increasing sizes. These index packages manage their inverted indices using adaptive merging strategy, which can reduce the merging overhead to improve query performance and can adjust the index structure based on environmental factors, such as the arrival rate of query requests and new microblogs. Experimental results show that LS-AMS can greatly improve query performance without increasing the update cost and improve the self-adaptability in dynamic environment. © 2015 IEEE.

关键词： Merging

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Pricing bilateral electricity trade between smart grids and hybrid green datacenters

Pricing bilateral electricity trade between smart grids and ...

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ACM SIGMETRICS International Conference on Measurement and Modeling of Computer systems, SIGMETRICS 2015

作者： Zhou, Zhi Liu, Fangming Li, Zongpeng Services Computing Technology and System Lab. School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computer Science University of Calgary Canada

ISBN: (纸本)9781450334860

Datacenter demand response is envisioned as a promising approach for mitigating operational instability faced by smart grids. It enables significant potentials in peak load shedding and facilitates the incorporation of distributed generation and intermittent energy sources. This work considers two key aspects towards realtime electricity pricing for eliciting demand response: (i) Two-way electricity flow between smart grids and large datacenters with hybrid green generation capabilities. (ii) The geo-distributed nature of large cloud systems, and hence the potential competition among smart grids that serve different datacenters of the cloud. We propose a pricing scheme tailored for geo-distributed green datacenters, from a multi-leader single-follower game point of view. At the cloud side, in quest for performance, scalab.lity and robustness, the energy cost is minimized in a distributed manner, based on the technique of alternating direction of multipliers (ADMM). At the smart grid side, a practical equilibrium of the pricing game is desired. To this end, we employ mathematical programming with equilibrium constraints (MPEC), equilibrium problem with equilibrium constraints (EPEC) and exact linearization, to transform the multi-leader single-follower pricing game into a mixed integer linear program (MILP) that can be readily solved. The effectiveness of the proposed solutions is evaluated based on trace-driven simulations. © Copyright 2015 ACM.

关键词： Distributed cloud

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Multi-version Execution for the Dynamic Updating of Cloud Applications

Multi-version Execution for the Dynamic Updating of Cloud Ap...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Feng Chen Weizhong Qiang Hai Jin Deqing Zou Duoqiang Wang Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan China

Softwares usually need to be updated to fix bugs or add new features. On the other hand, some critical softwares, such as cloud applications, need to provide service continuously, thus should be updated without downtime. Conventional Dynamic Software Updating (DSU) systems try to update programs while running, but they hardly consider the communication of the program to be updated with other programs, which may lead to some inconsistency problems. We handle the problem with an improved DSU system by using multi-version execution. When a new update arrives, instead of updating the application to the new version, we fork a new process of the old version and dynamically update it to the new version, then make these two versions run concurrently until the update finishes. We implement a prototype system called MUC (Multi-vesion for Updating of Cloud) on Linux. To verify our prototype, we apply MUC to cloud applications Redis and Ice cast, and evaluate the overhead of MUC at runtime.

关键词： Servers Software Synchronization Prototypes Linux Analytical models Process control

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Evaluating Latency-Sensitive Applications' Performance Degradation in Datacenters with Restricted Power Budget

Evaluating Latency-Sensitive Applications' Performance Degra...

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International Conference on Parallel Processing

作者： Song Wu Chuxiong Yan Haibao Chen Hai Jin Wei Guo Zhen Wang Deqing Zou Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Tencent Inc

ISBN: (纸本)9781467375887

For datacenters with limited power supply, restricting the servers' power budget (i.e., the maximal power provided to servers) is an efficient approach to increase the server density (the server quantity per rack), which can effectively improve the cost-effectiveness of the datacenters. However, this approach may also affect the performance of applications in servers. Hence, the prerequisite of adopting the approach in datacenters is to precisely evaluate the application performance degradation caused by restricting the servers' power budget. Unfortunately, existing evaluation methods are inaccurate because they are either improper or coarse-grained, especially for the latency-sensitive applications widely deployed in datacenters. In this paper, we analyze the reasons why state-of-the-art methods are not appropriate for evaluating the performance degradation of latency-sensitive applications in case of power restriction, and we propose a new evaluation method which can provide a fine-grained way to precisely describe and evaluate such degradation. We verify our proposed method by a real-world application and the traces from Tencent's datecenter with 25328 servers. The experimental results show that our method is much more accurate compared with the state of the art, and we can significantly increase datacenter efficiency by saving servers' power budget while maintaining the applications' performance degradation within controllab.e and acceptable range.

关键词： Servers degradation of performance power budget evaluation method state of the art Budgets

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