2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing最新文献_第4页

Optimize Parallel Data Access in Big Data Processing 优化大数据处理中的并行数据访问

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.168

Jiangling Yin, Jun Wang

{"title":"Optimize Parallel Data Access in Big Data Processing","authors":"Jiangling Yin, Jun Wang","doi":"10.1109/CCGrid.2015.168","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.168","url":null,"abstract":"Recent years the Hadoop Distributed File System(HDFS) has been deployed as the bedrock for many parallel big data processing systems, such as graph processing systems, MPI-based parallel programs and scala/java-based Spark frameworks, which can efficiently support iterative and interactive data analysis in memory. The first part of my dissertation mainly focuses on studying parallel data accession distributed file systems, e.g, HDFS. Since the distributed I/O resources and global data distribution are often not taken into consideration, the data requests from parallel processes/executors will unfortunately be served in a remoter imbalanced fashion on the storage servers. In order to address these problems, we develop I/O middleware systems and matching-based algorithms to map parallel data requests to storage servers such that local and balanced data access can be achieved. The last part of my dissertation presents our plans to improve the performance of interactive data access in big data analysis. Specifically, most interactive analysis programs will scan through the entire data set regardless of which data is actually required. We plan to develop a content-aware method to quickly access required data without this laborious scanning process.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"258 1","pages":"721-724"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74937324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Experience Based Sink Placement in Mobile Wireless Sensor Network 移动无线传感器网络中基于经验的Sink放置

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.57

Subhra Banerjee, S. Bhunia, N. Mukherjee

{"title":"Experience Based Sink Placement in Mobile Wireless Sensor Network","authors":"Subhra Banerjee, S. Bhunia, N. Mukherjee","doi":"10.1109/CCGrid.2015.57","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.57","url":null,"abstract":"In some applications of wireless sensor networks (WSN), sensor nodes are mobile while the sinks are static. In such dynamic environment, situations may arise where many sensor nodes are forwarding data through the same sink node resulting in sink overloading. One of the obvious effects of sink overloading is packet loss. It also indirectly affects the network lifetime in loss-sensitive WSN applications. Therefore, proper placement of sinks in such dynamic environment has a great impact on the performance of WSN applications. Multiple sink placement may not also work in some situations as node density may not be uniform. This paper introduces a sink placement scheme that aims at gathering experiences about sensor node density in region at different times and based on these observations, the scheme proposes candidate sink locations in order to reduce sink overloading. Next, based upon current sensor node density pattern, sinks at these locations are scheduled to active mode, while sinks at remaining candidate locations are scheduled to sleep mode. The second phase is repeated periodically. The scheme is implemented in a simulation environment and compared with another well-known strategy, namely Geographic Sink Placement (GSP). It has been observed that the proposed scheme exhibits better performance with respect to sink overloading and packet loss in comparison with GSP.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"2 1","pages":"898-907"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75585177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Network-Constrained Packing of Brokered Workloads in Virtualized Environments 虚拟化环境中代理工作负载的网络约束包装

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGRID.2015.110

Christine Bassem, Azer Bestavros

{"title":"Network-Constrained Packing of Brokered Workloads in Virtualized Environments","authors":"Christine Bassem, Azer Bestavros","doi":"10.1109/CCGRID.2015.110","DOIUrl":"https://doi.org/10.1109/CCGRID.2015.110","url":null,"abstract":"Providing resource allocation with performance predictability guarantees is increasingly important in cloud platforms, especially for data-intensive applications, for which performance depends greatly on the available rates of data transfer between the various computing/storage hosts underlying the virtualized resources assigned to the application. Existing resource allocation solutions either assume that applications manage their data transfer between their virtualized resources, or that cloud providers manage their internal networking resources. With the increased prevalence of brokerage services in cloud platforms, there is a need for resource allocation solutions that provide predictability guarantees in such settings, in which neither application scheduling nor cloud provider resources cane managed/controlled by the broker. This paper addresses this problem, as we define the Network-Constrained Packing (NCP)problem of finding the optimal mapping of brokered resources to applications with guaranteed performance predictability. We prove that NCP is NP-hard, and we define two special instances of the problem, for which exact solutions can be found efficiently. We develop a greedy heuristic to solve the general instance of thence problem, and we evaluate its efficiency using simulations on various application workloads, and network models.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"42 1","pages":"149-158"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79315699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

A Scheduler-Level Incentive Mechanism for Energy Efficiency in HPC 高性能计算中能效的调度级激励机制

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.101

Yiannis Georgiou, David Glesser, K. Rządca, D. Trystram

{"title":"A Scheduler-Level Incentive Mechanism for Energy Efficiency in HPC","authors":"Yiannis Georgiou, David Glesser, K. Rządca, D. Trystram","doi":"10.1109/CCGrid.2015.101","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.101","url":null,"abstract":"Energy consumption has become one of the most important factors in High Performance Computing platforms. However, while there are various algorithmic and programming techniques to save energy, a user has currently no incentive to employ them, as they might result in worse performance. We propose to manage the energy budget of a supercomputer through EnergyFairShare (EFS), a FairShare-like scheduling algorithm. FairShare is a classic scheduling rule that prioritizes jobs belonging to users who were assigned small amount of CPU-second in the past. Similarly, EFS keeps track of users 'consumption of Watt-seconds and prioritizes those whom jobs consumed less energy. Therefore, EFS incentives users to optimize their code for energy efficiency. Having higher priority, jobs have smaller queuing times and, thus, smaller turn-around time. To validate this principle, we implemented EFS in a scheduling simulator and processed workloads from various HPC centers. The results show that, by reducing it energy consumption, auser will reduce it stretch (slowdown), compared to increasing it energy consumption. To validate the general feasibility odour approach, we also implemented EFS as an extension forSLURM, a popular HPC resource and job management system.We validated our plugin both by emulating a large scale platform, and by experiments upon a real cluster with monitored energy consumption. We observed smaller waiting times for energy efficient users.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"56 3 1","pages":"617-626"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79799329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Cross-Layer SLA Management for Cloud-hosted Big Data Analytics Applications 云托管大数据分析应用的跨层SLA管理

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.175

Xuezhi Zeng, R. Ranjan, P. Strazdins, S. Garg, Lizhe Wang

{"title":"Cross-Layer SLA Management for Cloud-hosted Big Data Analytics Applications","authors":"Xuezhi Zeng, R. Ranjan, P. Strazdins, S. Garg, Lizhe Wang","doi":"10.1109/CCGrid.2015.175","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.175","url":null,"abstract":"As we come to terms with various big data challenges, one vital issue remains largely untouched. That is service level agreement (SLA) management to deliver strong Quality of Service (QoS) guarantees for big data analytics applications (BDAA) sharing the same underlying infrastructure, for example, a public cloud platform. Although SLA and QoS are not new concepts as they originated much before the cloud computing and big data era, its importance is amplified and complexity is aggravated by the emergence of time-sensitive BDAAs such as social network-based stock recommendation and environmental monitoring. These applications require strong QoS guarantees and dependability from the underlying cloud computing platform to accommodate real-time responses while handling ever-increasing complexities and uncertainties. Hence, the over-reaching goal of this PhD research is to develop novel simulation, modelling and benchmarking tools and techniques that can aid researchers and practitioners in studying the impact of uncertainties (contention, failures, anomalies, etc.) on the final SLA and QoS of a cloud-hosted BDAA.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"1 1","pages":"765-768"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81474843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Towards Provenance-Based Anomaly Detection in MapReduce MapReduce中基于来源的异常检测

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.16

C. Liao, A. Squicciarini

引用次数: 24

mAMBER: Accelerating Explicit Solvent Molecular Dynamic with Intel Xeon Phi Many-Integrated Core Coprocessors 成员:加速显式溶剂分子动力学与英特尔至强Phi多集成核心协处理器

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.66

Xin Liu, Shaoliang Peng, Canqun Yang, Chengkun Wu, Haiqiang Wang, Qian Cheng, Weiliang Zhu, Jinan Wang

{"title":"mAMBER: Accelerating Explicit Solvent Molecular Dynamic with Intel Xeon Phi Many-Integrated Core Coprocessors","authors":"Xin Liu, Shaoliang Peng, Canqun Yang, Chengkun Wu, Haiqiang Wang, Qian Cheng, Weiliang Zhu, Jinan Wang","doi":"10.1109/CCGrid.2015.66","DOIUrl":"https://doi.org/10.1109/CCGrid.2015.66","url":null,"abstract":"Molecular dynamics (MD) is a computer simulation of physical movements of atoms and molecules, which is a very important research technique for the study of biological and chemical systems at micro-scale. Assisted Model Building with Energy Refinement (AMBER) is one of the most commonly used software for MD. However, the microsecond MD simulation of large-scale atom system requires a lot of computation power. In this paper, we propose mAMBER: an Intel Xeon Phi Many-Integrated Core (MIC) Coprocessors accelerated implementation of explicit solvent all-atom classical molecular dynamics (MD) within the AMBER program package. We mAMBER also includes new parallel algorithm using CPUs and MIC coprocessors on Tianhe-2 supercomputer. With several optimizing techniques including CPU/MIC collaborated parallelization, factorization and asynchronous data transfer framework, we can accelerate the sander program of AMBER (version 12) in 'offload' mode, and achieves a 4.17-fold overall speedup compared with the CPU-only sander program.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"19 1","pages":"729-732"},"PeriodicalIF":0.0,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85921094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Quantitative Musings on the Feasibility of Smartphone Clouds 智能手机云可行性的定量思考

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.115

Cheng Chen, M. Ehsan, R. Sion

引用次数: 1

Locality-Aware Stencil Computations Using Flash SSDs as Main Memory Extension 基于Flash ssd的位置感知模板计算

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.126

H. Midorikawa, Hideyuki Tan

引用次数: 8

A Structured Light 3D Measurement System Based on Heterogeneous Parallel Computation Model 基于异构并行计算模型的结构光三维测量系统

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing Pub Date : 2015-05-04 DOI: 10.1109/CCGrid.2015.69

Xiaoyu Liu, Hao Sheng, Yang Zhang, Z. Xiong

引用次数: 2