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作者： Qiang, Weizhong Jiang, Changqing Ran, Longbo Zou, Deqing Jin, Hai Services Computing Technology and System Lab and Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Cloud provides users with a new model of utilizing the computing infrastructure with the ability to perform parallel and distributed computations using elastic virtual cluster. However, the multi-level and complex features make cloud computing system more prone to failure. In this paper, we present a multi-level fault-tolerant system for distributed applications in cloud named Distributed-application oriented Multi-level Checkpoint/Restart for Cloud (CDMCR). The CDMCR system backups the complete state of applications periodically with a snapshot-based distributed checkpointing protocol, including file system state. Thus, we cannot only recover processes but also rollback data. A multi-level recovery strategy is proposed, which includes process-level recovery, virtual machine recreation, and host rescheduling, enabling comprehensive and efficient fault tolerance for different components in cloud. We deploy CDMCR as PaaS, so that users can be liberated from node management and system configuration and get access to fault-tolerant service conveniently. We have implemented this system based on the Xen virtualization platform and the OpenNebula cloud platform. Experiments on the prototype demonstrate the correctness of the system. Analysis shows that CDMCR does not cause message loss or data loss, and the backup time remains nearly constant as the number of nodes increases on virtual cluster. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： Copyrights

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A survey of cloud resource management for complex engineering applications

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Frontiers of Computer Science 2016年第3期10卷 447-461页

作者： Haibao CHEN Song WU Hai JIN Wenguang CHEN Jidong ZHAI Yingwei LUO Xiaolin WANG Services Computing Technology and System Lab Cluster and Grid Computing LabSchool of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Institute of High Performance Computing Tsinghua University Beijing 100084 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China School of Computer and Information Engineering Chuzhou University Chuzhou 239000 China

Traditionally, complex engineering applications （CEAs）, which consist of numerous components （software） and require a large amount of computing resources, usu- ally run in dedicated clusters or high performance computing （HPC） centers. Nowadays, Cloud computing system with the ability of providing massive computing resources and cus- tomizable execution environment is becoming an attractive option for CEAs. As a new type on Cloud applications, CEA also brings the challenges of dealing with Cloud resources. In this paper, we provide a comprehensive survey of Cloud resource management research for CEAs. The survey puts forward two important questions： 1） what are the main chal- lenges for CEAs to run in Clouds？ and 2） what are the prior research topics addressing these challenges？ We summarize and highlight the main challenges and prior research topics. Our work can be probably helpful to those scientists and en- gineers who are interested in running CEAs in Cloud envi- ronment.

关键词： Cloud computing complex engineering application resource management virtualization

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Piggyback game: Efficient event stream dissemination in Online Social Network systems

Piggyback game: Efficient event stream dissemination in Onli...

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International Conference on Network Protocols

作者： Fan Zhang Hanhua Chen Hai Jin Services Computing Technology and System Lab Big Data Technology and System Lab and Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781509032822

Event stream dissemination dominates the workloads in large-scale Online Social Network (OSN) systems. Based on the de facto per-user view data storage, event stream dissemination raises a large amount of inter-server traffics due to the complex interconnection among OSN users. The state-of-the-art schemes mainly explore the structure features of social graphs to reduce the inter-server messages for event stream dissemination. Different sub-graph structures are exploited for achieving the approximated optimal assignment. However, such schemes incur high costs of computation or communication. In this work, we follow a different design philosophy by using a game theoretic approach, which decomposes the high complex graph computation problem into individuals' rational strategy selection of each node. Specifically, we propose a novel social piggyback game to achieve a more efficient solution. We mathematically prove the existing of the Nash Equilibrium of the social piggyback game. Moreover, we propose an efficient best response dynamic algorithm to achieve the Nash Equilibrium, which quickly converges in a small number of iterations for large-scale OSNs. We further show that the communication cost of this design achieves a 1.5-approximation of the theoretical social optimal. We conduct comprehensive experiments to evaluate the performance of this design using large-scale real-world traces from popular OSN systems. Results show that the social piggyback game achieves a significant 302× improvement in system efficiency compared to existing schemes.

关键词： Games Schedules Heuristic algorithms Algorithm design and analysis Nash equilibrium Social network services Servers

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Sponge:An Oversubscription Strategy Supporting Performance Interference Management in Cloud

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China Communications 2015年第11期12卷 196-209页

作者： LIU Ying Services Computing Technology and System Lab Cluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and Technology

Resource oversubscription optimizes the utilization of the computing resources. Many well-known virtual machine monitors(VMMs)such as Xen and KVM,adopt this approach to help maximize the yield of the cloud datacenters That is,with proper resource oversubscription strategies,more virtual machines(VMs) can be supported by limited resources. However performance interference among VMs hosting in the same physical machines(PMs) exists in cloud environment,and probably aggravated by resource oversubscription strategies,which aims to put more VMs into the same PM. In this paper,we present a resource oversubscription strategy called Sponge targeting cloud platforms Sponge mitigates the issue of performance interference among the oversubscribed co-hosting VMs. Sponge also provides a VM association strategy for each PM to handle with its besteffort. We performed our evaluation on a virtua datacenter simulated by Xen. Our evaluation results show that Sponge improves the resources utilization and manages to make each VM mee its performance requirement even hosting with other VMs in the same PM.

关键词： resources oversubscription performance interference cloud computing resource management

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A Novel Metadata Extraction Method for Surveillance Video

A Novel Metadata Extraction Method for Surveillance Video

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International Conference on computing, Networking and Communications

作者： Ran Zheng Long Chen Hai Jin Lei Zhu Qin Zhang Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology

ISBN: (纸本)9781467385800

Surveillance videos are increasing massively with monitoring cameras widely deployed in cities. Metadata of moving objects in videos can reduce video storage and be utilized in many video analysis applications. The whole metadata extraction is too time-consuming to be fulfilled quickly. Therefore, it is urgent to parallelize and accelerate the extraction process. However, iterative execution of traditional metadata extraction methods makes the parallelization quite challenging. In this paper, we propose a novel Parallel Metadata Extraction (PME) method for surveillance video. A novel video segmentation algorithm is designed to segment whole video into independent video segments. The metadata of each video segment is extracted independently and simultaneously on computer nodes, which will be integrated later to guarantee the completeness of the metadata. Performance evaluations demonstrate that PME can accelerate extraction process greatly almost without metadata loss.

关键词： Surveillance Videos Video Segmentation Metadata Extraction Iterative Execution MapReduce

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Conch: A Cyclic MapReduce Model for Iterative Applications

Conch: A Cyclic MapReduce Model for Iterative Applications

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Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Ran Zheng Genmao Yu Hai Jin Xuanhua Shi Qin Zhang Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

MapReduce programming model is a popular model to simplify but speed up data parallel applications. However, it is not efficient for iterative applications because of its repeated data transmission with HDFS (Hadoop Distributed File system). Conch, a cyclic MapReduce model, is designed for efficient processing of iterative applications. In order to minimize network overhead, shared data is cached locally and a "map-shuffle" phase is presented with a combined transmission mechanism. Meanwhile, a prediction scheduler for iterative applications is brought out to achieve better data locality in terms of runtime information. The experiments show that Conch can support iterative applications transparently and efficiently. Compared with Hadoop and HaLoop in single-job environment, Conch can achieve 13%-17% improvements on K-Means and fuzzy C-Means. Especially in multi-job environment, 63.6% and 28.6% improvements can be obtained compared with Hadoop and HaLoop.

关键词： Delays Iterative methods Computational modeling Prediction algorithms Heart beat Data transfer Data models

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Communication Cost Efficient Virtualized Network Function Placement for Big Data Processing

Communication Cost Efficient Virtualized Network Function Pl...

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IEEE Conference on Computer Communications Workshops

作者： Lin Gu Sheng Tao Deze Zeng Hai Jin Services Computing Technology and System Lab Cluster and Grid Computing Lab Big Data Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Computer Science China University of Geosciences Wuhan Hubei China

ISBN: (纸本)9781467399562

The data explosion in the emerging big data era imposes a big burden on the network infrastructure. This vision has urged the evolution of computer networks. By softwarizing traditional dedicated hardware based functions to virtualized network function (VNF) that can run on standard commodity servers, network function virtualization (NFV) technology promises increased networking efficiency, flexibility and scalab.lity. From the perspective of network service providers, with the consideration of big data traffic volume, one primary concern is on the communication cost, which is highly influenced by the VNF placement strategy. In this paper, we are motivated to investigate the issue on communication cost efficient VNF placement problem for big data processing, with joint consideration of network flow balancing and the predetermined network service semantics. We formulate this problem into a mixed-integer linear programming (MILP) form and then propose a low-complexity relaxation-based heuristic algorithm accordingly. The high efficiency of our proposal is validated by extensive simulation studies.

关键词： Noise measurement Big data Distributed databases Algorithm design and analysis Servers Heuristic algorithms Semantics

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Short: CICC: A fine-grained, semantic-aware, and transparent approach to preventing permission leaks for android permission managers 8

Short: CICC: A fine-grained, semantic-aware, and transparent...

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8th ACM Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2015

作者： Wang, Daibin Yao, Haixia Li, Yingjiu Jin, Hai Zou, Deqing Deng, Robert H. Services Computing Technology and System Lab. Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China School of Information Systems Singapore Management University Singapore

ISBN: (纸本)9781450336239

Android's permission system offers an all-or-nothing installation choice for users. To make it more flexible, users may choose a popular app tool, called permission manager, to selectively grant or revoke an app's permissions at runtime. A fundamental requirement for such permission manager is that the granted or revoked permissions should be enforced faithfully. However, we discover that none of existing permission managers meet this requirement due to permission leaks. To address this problem, we propose CICC, a finegrained, semantic-aware, and transparent approach for any permission managers to defend against the permission leaks. Compared to existing solutions, CICC is fine-grained because it detects the permission leaks using call-chain information at the component instance level, instead of at the app level or component level. The fine-grained feature enables it to generate a minimal impact on the usability of running apps. CICC is semantic-aware in a sense that it manages call-chains in the whole lifecycle of each component instance. CICC is transparent to users and app developers, and it requires minor modification to permission managers. Our evaluation shows that CICC incurs relatively low performance overhead and power consumption. Copyright 2015 ACM.

关键词： Android Call-chain Permission leaks Permission manager

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Optimization of asynchronous graph processing on GPU with hybrid coloring model 2015

Optimization of asynchronous graph processing on GPU with hy...

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

作者： Shi, Xuanhua Liang, Junling Di, Sheng He, Bingsheng Jin, Hai Lu, Lu Wang, Zhixiang Luo, Xuan Zhong, Jianlong Services Computing Technology and System Lab. Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology China Argonne National Laboratory United States School of Computer Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781450332057

Modern GPUs have been widely used to accelerate the graph processing for complicated computational problems regarding graph theory. Many parallel graph algorithms adopt the asynchronous computing model to accelerate the iterative convergence. Unfortunately, the consistent asynchronous computing requires locking or the atomic operations, leading to significant penalties/overheads when implemented on GPUs. To this end, coloring algorithm is adopted to separate the vertices with potential updating conflicts, guaranteeing the consistency/correctness of the parallel processing. We propose a light-weight asynchronous processing framework called Frog with a hybrid coloring model. We find that majority of vertices (about 80%) are colored with only a few colors, such that they can be read and updated in a very high degree of parallelism without violating the sequential consistency. Accordingly, our solution will separate the processing of the vertices based on the distribution of colors.

关键词： Graphics processing unit

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Parallel bloom filter on xeon phi many-core processors 15th

Parallel bloom filter on xeon phi many-core processors

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

作者： Ni, Sheng Guo, Rentong 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)9783319271217

Bloom filters are widely used in databases and network areas. These filters facilitate efficient membership checking with a low false positive ratio. It is a way to improve the throughput of bloom filter by parallel processing. Common many-core processors such as Xeon Phi can provide high parallelism. Thus, we build an iterative model to analyze memory access performance. This performance suggests that the bottleneck in the traditional design is mainly caused by synchronization cost and memory latency on many-core platforms. Therefore, we propose a parallel bloom filter (PBF), which is a lockless method involving input data preprocessing. This method reduces synchronization overhead and improves cache locality. We also implement and evaluate PBF on a Xeon Phi processor. Results show that the memory access performance is three times better than that of the counting bloom filter. PBF provides improved scalab.lity, and the speedup ratio can reach a maximum of 80.7x. © Springer International Publishing Switzerland 2015.

关键词： Scalab.lity

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