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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Xia Xie Haiqing Zhu Wenzhi Cao Hai Jin Pingpeng Yuan Services Computing Technology and System Laboratory Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

With the development of virtualization technology, it can run more and more guest domains on one single physical machine. So the network I/O demand is also rapidly increasing, for these guest domains can supply more and more services or run more and more applications. This will lead to serious contention on network I/O of physical machine. Although we can use high performance NICs (network interface cards) to improve network I/O performance, one single NIC cannot get further performance improvement which depends on hardware technology. Linux bonding can achieve high bandwidth network by using multiple NICs, but it does not guarantee QoS among guest domains. Also it would terminate one guest domain's communication because of its response mechanism of ARP. Therefore, we present an approach named Virtual Bonding to achieve high bandwidth network by using multi-NICs. It aggregates multi-NICs to provide high bandwidth and high-quality network services. It also introduces load balancing mechanism between multi-NICs. So it can make full use of every NIC. Furthermore, it makes perfect support to virtualization environment.

关键词： Bonding Bridges Bandwidth Load management Servers Linux IP networks

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Optimization of Sparse Matrix-Vector Multiplication with Variant CSR on GPUs

Optimization of Sparse Matrix-Vector Multiplication with Var...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Xiaowen Feng Hai Jin Ran Zheng Kan Hu Jingxiang Zeng Zhiyuan Shao Services Computing Technology and System Laboratory Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Sparse Matrix-Vector multiplication (SpMV) is one of the most significant yet challenging issues in computational science area. It is a memory-bound application whose performance mostly depends on the input matrix and the underlying architecture. Many researchers have paid more attentions on exploring a variety of optimization techniques to SpMV. One of the most promising respects is how to adapt the storage format to satisfy the underlying architecture. Alterative storage formats can largely lessen memory pressure, however, the computational resources are often underutilized. Therefore, a new storage format, which is called Compressed Sparse Row with Segmented Interleave Combination (SIC), is proposed. Stemming from Compressed Sparse Row format (CSR), SIC format employs an interleave combination pattern that combines certain amount of CSR rows to form a new SIC row. In order to further improve performance, segmented processing is also brought in. According to the empirical data, we also develop an automatic SIC-based SpMV suitable for all the matrices. Experimental results show that our approach outperforms the NVIDIA CSR vector kernel, achieving up to 12.6 × speedup. It also demonstrates a comparable performance with the Hybrid format, even with the highest 2.89 × speedup.

关键词： Graphics processing unit Kernel Sparse matrices Silicon carbide Vectors Instruction sets Computer architecture

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EAPAC: An enhanced application placement framework for data centers

EAPAC: An enhanced application placement framework for data ...

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14th IEEE Int. Conf. on Computational Science and Engineering, CSE 2011, the 11th International Symposium on Pervasive systems, Algorithms, and Networks, I-SPAN 2011, and the 10th IEEE Int. Conf. on Ubiquitous computing and Communications, IUCC 2011

作者： Shi, Xuanhua Jiang, Hongbo He, Ligang Jin, Hai Wang, Chonggang Yu, Bo Wang, Fei Service Computing Technology and System Lab./Cluster and Grid Computing Lab. School of Computer Huazhong University of Science and Technology China Department of Electronics and Information Engineering Huazhong University of Science and Technology China Department of Computer Science University of Warwick United Kingdom InterDigital Communications Corp. United States

ISBN: (纸本)9780769544779

Emerging data centers may host a large number of applications that consume CPU power, memory, and I/O resources. Previous studies focus on the allocation of resources in order to perfectly satisfy the demands seen in the current cycle, and the existing application placement algorithms are all based on applications. The existing application placement algorithms in literature assume that the consumption of system resources is proportional to the level of workloads submitted to the system. In this paper, we revealed that it may not be the case in some circumstances. Based on this observation, we design and implement an application placement framework, called EAPAC, for data centers. The developed framework is able to judiciously allocate to application servers a proper mixture of different types of application requests as well as an appropriate number of requests in each type. Further, we investigate the issue of resource conflicts among different applications when there exist concurrent requests in the system. We have conducted extensive experiments to evaluate the performance of the developed framework. The experiment results show that compared with the existing studies, EAPAC can improve the performance by 30% in terms of the reply rate. Especially, when there are concurrent requests in the system, the performance can be improved by 100%. © 2011 IEEE.

关键词： Computer programming

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Reference metadata extraction from scientific papers

Reference metadata extraction from scientific papers

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IEEE International Conference on Parallel and Distributed computing, Applications and Technologies (PDCAT)

作者： Zhixin Guo Hai Jin Cluster and Grid Computing Laboratory Services Computing Technology and System Laboratory Huazhong University of Science and Technology Wuhan China

Bibliographical information of scientific papers is of great value since the Science Citation Index is introduced to measure research impact. Most scientific documents available on the web are unstructured or semi-structured, and the automatic reference metadata extraction process becomes an important task. This paper describes a framework for automatic reference metadata extraction from scientific papers. Our system can extract title, author, journal, volume, year, and page from scientific papers in PDF. We utilize a document metadata knowledge base to guide the reference metadata extraction process. The experiment results show that our system achieves a high accuracy.

关键词： Data mining Portable document format Knowledge based systems Accuracy Libraries Semantics Hidden Markov models

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RAPn: Network Attack Prediction Using Ranking Access Petri Net

RAPn: Network Attack Prediction Using Ranking Access Petri N...

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Chinagrid Annual Conference (Chinagrid)

作者： Moussa Djiriba Traore Hai Jin Deqing Zou Weizhong Qiang Guofu Xiang Services Computing Technology and System Laboratory Cluster and Grid Computing Laboratory Huazhong University of Science and Technology Wuhan China

Exploits sequencing is a typical way by which an attacker breaks into a network. In such a scenario, each exploit lays as an atomic proposition for subsequent exploits. An attack path is seen as a succession of exploits which take an attacker right to his/her final goal. The set of all possible attack paths form an attack graph. Researchers have proposed a multitude of techniques to generate attack graph which grows exponentially in the size of the network. Hence it is preferable to optimize the choice of solutions which avoid the cost of scalability and cumbersome. In this paper, we propose a comprehensive approach to network vulnerability analysis by ranking access Petri net graph and utilizing a penetration tester's perspective of maximal level of access possible on a host. Our approach has the following benefits: it provides a simple model in which an analyst can work, its algorithmic complexity is polynomial in the size of the network, and has the ability of scaling well to large size networks. Nevertheless, it has some drawback as in place of all possible attack paths, we seek only good attack paths. An analyst may make suboptimal choices when repairing the network.

关键词： Mathematical model Analytical models Databases Finite element methods Automata Permission

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Towards pay-as-you-consume cloud computing

Towards pay-as-you-consume cloud computing

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International Conference on services computing

作者： Ibrahim, Shadi He, Bingsheng Jin, Hai Cluster and Grid Computing Lab. Huazhong University of Science and Technology Wuhan 430074 China School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)9780769544625

Cloud computing enables users to perform their computation tasks in the public virtualized cloud using a pay-as-you-go style. Current pay-as-you-go pricing schemes typically charge on the incurred virtual machine hours. Our case studies demonstrate significant variations in the user costs, indicating significant unfairness among different users from the micro-economic perspective. Further studies reveal the reason for such variations is interference among concurrent virtual machines. The amount of interference cost depends on various factors, including workload characteristics, the number of concurrent VMs, and scheduling in the cloud. In this paper, we adopt the concept of pricing fairness from micro economics, and quantitatively analyze the impact of interference on the pricing fairness. To solve the unfairness caused by interference, we propose a pay-as-you-consume pricing scheme, which charges users according to their effective resource consumption excluding interference. The key idea behind the pay-as-you-consume pricing scheme is a machine learning based prediction model of the relative cost of interference. Our preliminary results with Xen demonstrate the accuracy of the prediction model, and the fairness of the pay-as-you-consume pricing scheme. © 2011 IEEE.

关键词： Cloud computing

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Automatic power-aware reconfiguration of processor resource in virtualized clusters

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2011年第7期48卷 1123-1133页

作者： Jin, Hai Deng, Li Wu, Song Shi, Xuanhua Zhou, Like Key Laboratory of Services Computing Technology and System Huazhong University of Science and Technology Ministry of Education Wuhan 430074 China Key Laboratory of Cluster and Grid Computing of Hubei Province Huazhong University of Science and Technology Wuhan 430074 China

Virtualization provides significant benefits of system maintenance, load balancing, fault tolerance, and power-saving in clusters or data centers. It also enables dynamic reconfiguration of computing resource for application environment. However, current dynamic resource control approaches mainly focus on how to satisfy the application-level quality of service (QoS) when application workloads vary with time. They are driven by application performance, which is often specific to certain class of applications and also weakens the response capability of control systems. In this paper, a resource-use-status-driven resource reconfiguration scheme (RUSiC) is presented to automatically adapt to dynamic workload changes to meet the demands of application performance. According to the new characteristics introduced by system virtualization, the scheme is designed to be a two-layer resource reconfiguration model to exactly grasp the demands of applications. Based on real resource use status, the scheme adjusts proper resource configuration for applications in time. Furthermore, the scheme introduces power-saving into resource reconfiguration process and avoids considerable unnecessary power and cooling consumption by reducing the number of active physical nodes in a new resource configuration. Experiments demonstrate that the scheme can quickly detect and respond to shifting resource demands as application workloads change over time.

关键词： Virtualization

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Virtual machine VCPU scheduling in the multi-core environment: Issues and challenges

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2011年第7期48卷 1216-1224页

作者： Jin, Hai Zhong, Alin Wu, Song Shi, Xuanhua Key Laboratory of Services Computing Technology and System Huazhong University of Science and Technology Ministry of Education Wuhan 430074 China Key Laboratory of Cluster and Grid Computing of Hubei Province Huazhong University of Science and Technology Wuhan 430074 China

The policies and mechanisms of VCPU (virtual CPU) scheduling in a virtual machine system are key factors to determine the system performance. Because the architecture of the software stack in the virtual machine system is different from the traditional computer systems, when scheduling the VCPUs in virtual machines, simply adopting scheduling strategies and algorithms of existing operating systems without any modifications can lead to drastic degradation of the system performance. Moreover, with the multi-core technology being employed for physical processors, the complexity of the VCPU scheduling is increased. Firstly, the architecture of the virtual machine system and its two-stage scheduling framework are depicted and analyzed in detail in this paper. Because the deterministic mapping relationship between application threads and physical cores is difficult to establish in the two-stage framework, and part functions of operating systems move down to virtual machine monitor, VCPU scheduling will confront many problems and challenges that mainly embody four aspects: the semantic gap between guest operating systems and a virtual machine monitor, the synchronization mechanisms in a multiprocessor operating system, the structure of shared cache in multi-core processors and emerging asymmetric multi-core structure. And then advantages and limitations of the existing solutions for these problems are discussed and analyzed deeply, and suggestions for further researches are presented.

关键词： Virtual machine

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Adaptive disk I/O scheduling for MapReduce in virtualized environment

Adaptive disk I/O scheduling for MapReduce in virtualized en...

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40th International Conference on Parallel Processing, ICPP 2011

作者： Ibrahim, Shadi Jin, Hai Lu, Lu He, Bingsheng Wu, Song Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)9780769545103

Virtual machine (VM) interference has long been a challenging problem for performance predictability and system throughput for large-scale virtualized environments in the cloud. Such interferences are contributed by intertwined factors including the application's type, the number of concurrent VMs, and the VM scheduling algorithms used within the host. Since MapReduce has become an important data processing platform in the cloud, we investigate the impact of disk schedulers in Hadoop. Interestingly, our experimental results report a noticeable variation of the Hadoop performance between different applications when applying different disk pairs' schedulers in both the hypervisor and the virtual machines. Furthermore, a typical Hadoop application consists of different interleaving stages, each requiring different I/O workloads and patterns. As a result, the disk pairs' schedulers are not only sub-optimal for different MapReduce applications, but also sub-optimal for different sub-phases of the whole job. Accordingly, this paper presents a novel approach for adaptively tuning the disk pairs' schedulers in both the hypervisor and the virtual machines during the execution of a single MapReduce job. Our results show that MapReduce performance can be significantly improved;specifically, adaptive tuning of disk pairs' schedulers achieves a 25% performance improvement on a sort benchmark with Hadoop. © 2011 IEEE.

关键词： MapReduce

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A Cloud Service Cache system Based on Memory Template of Virtual Machine

A Cloud Service Cache System Based on Memory Template of Vir...

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Chinagrid Annual Conference (Chinagrid)

作者： Xuanhua Shi Chao Liu Song Wu Hai Jin Xiaoxin Wu Li Deng Services Computing Technology and System Laboratory Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Huawei Technologies Company Limited China

In data centers and cloud computing environments, the number of virtual machines (VMs) increases when the number of service requests increases. Since services are invoked on demand, the corresponding virtual machines will be created and shut down frequently. This makes the time of starting a virtual machine a crucial performance bottleneck for services in data centers. Besides, if virtual machines read image files from disks to start themselves, additional overhead to access disk will be generated. In this paper, we present a cloud service cache system based on memory template of virtual machines - VCache to improve the response time of cloud computing services, and to reduce the disk access overhead. This system can create and maintain service cache VMs through memory templates, which are snapshots of running virtual machines. By creating virtual machines from cached image files, the service running in these VMs can be deployed rapidly, which greatly reduces the launching time of the service and disk I/O load. We evaluate our system with experiments, and the experimental results show that the average time for creating a VM is reduced about 80% and the amount of data through disk access decreases more than 50%.

关键词： Virtual machining Random access memory IP networks Memory management Image restoration Cloud computing Cloning

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