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IEEE International Conference on cluster computing

作者： Ming Li Xuanhua Shi Wei Liu Hai Jin Yong Chen Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China Department of Computer Science Texas Tech University Lubbock Texas USA

ISBN: (纸本)9781509036547

High performance computing (HPC) applications are becoming more data-intensive and produce increasingly large I/O demands on storage systems. New storage devices such as SSD which has nearly no seek latency and high throughput have been widely used together with HDD to serve as a hybrid storage system. To solve the I/O bottleneck problem, existing hybrid storage solutions such as Burst Buffer have been proposed as intermediate layer between clients and disks to absorb burst I/O requests and improve write performance. However Burst Buffer needs sufficient SSD space to meet the maximum burst I/O requests which is still a costly solution. In this paper, we propose a hybrid architecture called SSDUP (an SSD write buffer Using Pipeline) for HPC storage systems, which uses NAND flash based SSD as a write-back buffer for HDD. With our efforts, SSDUP can achieve a good performance by using limited SSD space.

关键词： Pipelines Buffer storage Throughput Prototypes Metadata Computer architecture Benchmark testing

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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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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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Public auditing for secure data storage in cloud through a third party auditor using modern ciphertext 11

Public auditing for secure data storage in cloud through a t...

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

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

ISBN: (纸本)9781467387156

Outsourced data in cloud and computation results are not always trustworthy because data owners lack physical possession and control over the data as a result of virtualization, replication, and migration techniques. Protecting outsourced data from security threats has become a challenging and potentially formidable task in cloud computing;hence, many schemes have focused on ameliorating this problem and on enabling public auditability for cloud data storage security. These schemes drop into two categories: total computation cost and burden on client side. Researchers have used bilinear map technology with public key cryptography. Although this technology is highly efficient, computation time is long and overhead cost is high. The client needs to perform numerous computations to ensure the integrity of data storage. To reduce auditing cost, we propose an efficient and robust scheme to maintain data integrity in cases that involve public auditing. Our scheme adopts modern cipher cryptography with a cryptographic hash function. We consider allowing a third party auditor to preprocess data on behalf of cloud users before uploading them to cloud service providers and then verifying data integrity afterward. Our proposed scheme has important security characteristics, such as privacy, key management, low cost computation, key exchange, low overhead cost, no burden on client side, inability of cloud service providers to create correct verifier respond without data, and one-time key. Finally, efficiency analysis shows that our scheme is faster and more cost-efficient than the bilinear map-based scheme. © 2015 IEEE.

关键词： Public key cryptography

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Towards Efficient Authentication Scheme with Biometric Key Management in Cloud Environment

Towards Efficient Authentication Scheme with Biometric Key M...

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IEEE International Conference on Big Data Security on Cloud (BigDataSecurity), High Performance and Smart computing (HPSC) and Intelligent Data and Security (IDS)

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

Recently, security issues are obstructing the development and using of cloud computing services. Authentication plays an important role in the cloud security, and numerous concerns have been raised to prevent an unauthorized users to access the entities' resources (sender and receiver) within the cloud environment. Existing solutions are based on one-time authentication scheme, in which a user's password is applicable only for one login session. However, none of the proposed schemes are sufficiently secure to prevent known forms of attack. In addition, these schemes often suffer from significant overhead in the key management. For this reason, we propose a robust one-time authentication scheme based on a non-interactive one-time biometric key to generate one-time login request message. The key used in our scheme has two strong building blocks, that is, it is biometrically based on the extraction of features from the entities' irises, and cryptographically based on the strong key-based message authentication code MAC-SHA-512 and Rivest Cipher 4. The proposed scheme exhibits several important security attributes, such as key agreement, biometric key management, a single authentication request for each user's login, mutual authentication, invulnerability, and efficiency.

关键词： Authentication Elliptic curve cryptography Receivers Robustness Feature extraction Cloud computing

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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 controllable and acceptable range.

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

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SKVM: Scaling In-Memory Key-Value Store on Multicore

SKVM: Scaling In-Memory Key-Value Store on Multicore

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IEEE Symposium on Computers and Communication

作者： Ran Zheng Wenjin Wang Hai Jin 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)9781467371957

SKVM is a high performance in-memory Key-Value (KV) store for multicore, which is designed for high concurrent data access. There are some problems of existing systems dealing with high concurrent data processing on multicore: lock competition, cache coherency overhead, and large numbers of concurrent network connections. To solve the problems and make the in-memory KV store scale well on multicore, high concurrent data access is divided into two steps: high concurrent connection processing and high concurrent data processing. Half sync/half async model (HSHA) is adopted to eliminate network bottle-neck, which can support high concurrent network connection. Through data partition, lock competition is eliminated and cache movement is reduced. Furthermore, consistent hash is adopted as data distribution strategy which can improve the scalability of system on multicore. Though some of these ideas appear elsewhere, SKVM is the first to combine them together. The experimental results show that SKVM can reach at most 2.4× higher throughput than Memcached, and scales near linearly with the number of cores under any workload.

关键词： In-Memory KV store Multicore Scalability Concurrent data access

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Cost Minimization for Code Offloading with Cellular Traffic Aggregation

Cost Minimization for Code Offloading with Cellular Traffic ...

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IEEE Symposium on Computers and Communication

作者： Jiao Song Feng Lu Hai Jin Zaiyang Tang Peng Li Xiaofei Liao Xia Xie Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China

ISBN: (纸本)9781467371957

Code offloading has been proposed to improve the performance and energy-efficiency of mobile devices by sending heavy computation tasks to resourceful cloud, instead of executing all tasks on local mobile devices. Unfortunately, current code offloading techniques are not efficient enough because of high communication cost. In this paper, we propose a novel code offloading strategy with cellular traffic aggregation that aggregates offloaded codes to several mobile devices before sending them to cloud, which can significantly reduce tail energy effect. With the objective of minimizing the total cost of computation and communication, we propose an optimization framework by jointly considering code partition and traffic aggregation. Due to the hardness of this problem, we design an efficient heuristic algorithm and evaluate its performance via extensive simulations. Simulation results demonstrate that the proposed algorithm significantly outperforms existing schemes.

关键词： Code Offloading Cellular Network Traffic Aggregation Energy Efficiency

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