2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)最新文献_第9页

mCluster: A Software Framework for Portable Device-Based Volunteer Computing mCluster:一个基于便携式设备的志愿计算软件框架

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-16 DOI: 10.1109/CCGrid.2016.65

D. Theodoropoulos, Grigorios Chrysos, Iosif Koidis, George Charitopoulos, Emmanouil Pissadakis, Antonis Varikos, D. Pnevmatikatos, Georgios Smaragdos, C. Strydis, Nikos Zervos

{"title":"mCluster: A Software Framework for Portable Device-Based Volunteer Computing","authors":"D. Theodoropoulos, Grigorios Chrysos, Iosif Koidis, George Charitopoulos, Emmanouil Pissadakis, Antonis Varikos, D. Pnevmatikatos, Georgios Smaragdos, C. Strydis, Nikos Zervos","doi":"10.1109/CCGrid.2016.65","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.65","url":null,"abstract":"Recent market forecasts predict that the portable computing trend will vastly spread, as by 2020 there will bemore than 3 billion LTE device users worldwide. Motivated by this fact, many companies and research institutes have already launched research projects that utilize portable devices, voluntarily provided by users, to perform the required computations. Many such projects employ Berkeley's BOINC middleware, since it can support a large variety of stationary and mobile devices. However, currently available BOINC high-level APIs, either do not support portable devices or lack advanced processing capabilities (such as inter-node task dependencies) and/or easiness of use. To resolve these issues, we propose the mCluster software framework for application execution powered by the BOINC middleware on portable devices. mCluster adopts a task-based programming model that requires simple, pragma-based annotations of the application software, in order to dynamically resolve task dependencies. To evaluate our framework, we have have mapped a scientific application from the neuroscience domain on an small-scaled network of portable devices. mCluster significantly reduces the required programming effort and complexity to efficiently map BOINC-powered applications with task dependencies on portable devices compared to previous approaches.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122726664","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

Say Hello Again: Privacy Preserving Matchmaking Using Cloud in Encounter Based Mobile Social Networks 再次打招呼:在基于相遇的移动社交网络中使用云来保护隐私

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-16 DOI: 10.1109/CCGrid.2016.39

Fizza Abbas, Ubaidullah Rajput, Jian Wang, Hasoo Eun, Heekuck Oh

{"title":"Say Hello Again: Privacy Preserving Matchmaking Using Cloud in Encounter Based Mobile Social Networks","authors":"Fizza Abbas, Ubaidullah Rajput, Jian Wang, Hasoo Eun, Heekuck Oh","doi":"10.1109/CCGrid.2016.39","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.39","url":null,"abstract":"Mobile social networks (MSNs) are getting increasingly popular day by day. With the help of MSNs people can connect with each other online as well as offline. One of the famous applications of MSNs is profile matchmaking in which users share their interests in order to find mutual friends. However, the user of such application can be a victim of various privacy related attacks due to the revelations of user's personal interests during profile matchmaking. More recent dimension of MSN is encounter-based social networks. In this scenario, the users make social contacts while sharing a common location and time. Mobile devices record the encounter information when two users are within physical proximity and at a later time, their encounter history should be matched when they try to find each other again. In this paper, we propose a privacy preserving matchmaking protocol in which users share the encounter information and later utilize a cloud server to post encounter information in order to privately match their profiles with unknowns to whom they shared the encounter. In our protocol, neither the users nor the cloud server is able to discover the interests of either participants during matchmaking. To the best of our knowledge, this approach is the first attempt that combines encounter based social networks and fine-grained profile matchmaking. Towards the end of the paper, we present security analysis as well as performance evaluation that shows the effectiveness and feasibility of our protocol.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132355816","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

enerGyPU and enerGyPhi Monitor for Power Consumption and Performance Evaluation on Nvidia Tesla GPU and Intel Xeon Phi enerGyPU和enerGyPhi监视器用于Nvidia Tesla GPU和Intel Xeon Phi的功耗和性能评估

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-16 DOI: 10.1109/CCGrid.2016.100

H. JohnA.Garcia, B. EstebanHernandez, C. E. Montenegro, P. Navaux, C. Hernández

{"title":"enerGyPU and enerGyPhi Monitor for Power Consumption and Performance Evaluation on Nvidia Tesla GPU and Intel Xeon Phi","authors":"H. JohnA.Garcia, B. EstebanHernandez, C. E. Montenegro, P. Navaux, C. Hernández","doi":"10.1109/CCGrid.2016.100","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.100","url":null,"abstract":"The evaluation of performance and power consumption is a key step in the design of applications for large computational systems as supercomputers and clusters (multicore and accelerator nodes, multicore and coprocessor nodes, manycore and accelerator nodes). In these systems the developers must design several experiments for workload characterization observing the architectural implications when using different combinations of computational resources such as number of GPU, number of cores for processing, number of cores for administration of GPU, number of MPI processes and thread affinity policy. It should also engage factors as the clock frequency and memory usage as well select the combination of computational resources that increases the performance and minimizes the power consumption. This research proposes an integrated energy-aware scheme called efficiently energetic acceleration (EEA) for large-scale scientific applications running on heterogeneous architectures. This paper shows the use of a monitoring tool with two components called enerGyPU and enerGyPhi to recording EEA control factors in runtime on two environments: one cluster with multicore and accelerator nodes (2-CPU/8-GPU) and one server with multiple cores and one coprocessor (2-CPU/1-MIC). These monitors allow to analyze multiple testing results under different parameter combinations to observe the EEA control factors that determine the energy efficiency.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126258186","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: 4

DieHard: Reliable Scheduling to Survive Correlated Failures in Cloud Data Centers 死忠:在云数据中心的相关故障中存活的可靠调度

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-16 DOI: 10.1109/CCGrid.2016.11

M. Sedaghat, E. Wadbro, J. Wilkes, S. S. Luna, O. Seleznjev, E. Elmroth

{"title":"DieHard: Reliable Scheduling to Survive Correlated Failures in Cloud Data Centers","authors":"M. Sedaghat, E. Wadbro, J. Wilkes, S. S. Luna, O. Seleznjev, E. Elmroth","doi":"10.1109/CCGrid.2016.11","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.11","url":null,"abstract":"In large scale data centers, a single fault can lead to correlated failures of several physical machines and the tasks running on them, simultaneously. Such correlated failures can severely damage the reliability of a service or a job. This paper models the impact of stochastic and correlated failures on job reliability in a data center. We focus on correlated failures caused by power outages or failures of network components, on jobs running multiple replicas of identical tasks. We present a statistical reliability model and an approximation technique for computing a job's reliability in the presence of correlated failures. In addition, we address the problem of scheduling a job with reliability constraints. We formulate the scheduling problem as an optimization problem, with the aim being to achieve the desired reliability with the minimum number of extra tasks. We present a scheduling algorithm that approximates the minimum number of required tasks and a placement to achieve a desired job reliability. We study the efficiency of our algorithm using an analytical approach and by simulating a cluster with different failure sources and reliabilities. The results show that the algorithm can effectively approximate the minimum number of extra tasks required to achieve the job's reliability.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126445310","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: 36

Usage Pattern-Driven Dynamic Data Layout Reorganization 使用模式驱动的动态数据布局重组

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-16 DOI: 10.1109/CCGrid.2016.15

Houjun Tang, S. Byna, Steve Harenberg, Xiaocheng Zou, Wenzhao Zhang, Kesheng Wu, Bin Dong, O. Rübel, K. Bouchard, S. Klasky, N. Samatova

{"title":"Usage Pattern-Driven Dynamic Data Layout Reorganization","authors":"Houjun Tang, S. Byna, Steve Harenberg, Xiaocheng Zou, Wenzhao Zhang, Kesheng Wu, Bin Dong, O. Rübel, K. Bouchard, S. Klasky, N. Samatova","doi":"10.1109/CCGrid.2016.15","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.15","url":null,"abstract":"As scientific simulations and experiments move toward extremely large scales and generate massive amounts of data, the data access performance of analytic applications becomes crucial. A mismatch often happens between write and read patterns of data accesses, typically resulting in poor read performance. Data layout reorganization has been used to improve the locality of data accesses. However, current data reorganizations are static and focus on generating a single (or set of) optimized layouts that rely on prior knowledge of exact future access patterns. We propose a framework that dynamically recognizes the data usage patterns, replicates the data of interest in multiple reorganized layouts that would benefit common read patterns, and makes runtime decisions on selecting a favorable layout for a given read pattern. This framework supports reading individual elements and chunks of a multi-dimensional array of variables. Our pattern-driven layout selection strategy achieves multi-fold speedups compared to reading from the original dataset.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126901394","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: 13

Proof of Violation for Trust and Accountability of Cloud Database Systems 云数据库系统信任与问责的违规证明

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-16 DOI: 10.1109/CCGrid.2016.27

Gwan-Hwan Hwang, Shi Fu

{"title":"Proof of Violation for Trust and Accountability of Cloud Database Systems","authors":"Gwan-Hwan Hwang, Shi Fu","doi":"10.1109/CCGrid.2016.27","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.27","url":null,"abstract":"A cloud database is a system that typically runs on a cloud computing platform which is not maintained by the user but a service provider. The service provider can leak confidential data, modify the data, or return inconsistent data to users due to bugs, crashes, operator errors, or even malicious security attacks. Some cloud database systems provide Web interface or application programming interface for clients to access logs of database transactions. However, these logs are not cryptographic proofs. Clients cannot use these logs to prove whether a cloud service provider has violated some required properties such as data integrity, write serializability, and read freshness. A proof of violation (POV) scheme enables a client or a service provider to produce a precise proof of either the occurrence of the violation of properties or the innocence of the service provider. In this paper, we develop POV schemes for cloud database systems. First, we show that previously proposed cryptographic accountability protocols (CAPs), cannot be applied to cloud database systems directly. A CAP defines a multi-step handshaking protocol for clients and the service provider to exchange signed messages during service request and response so as to generate cryptographic proofs for later auditing. In addition, previously proposed auditing schemes are inappropriate to obtain the auditing requirements of SQL database according to collected cryptographic proofs. We design a new auditing scheme for cloud database systems. Implementation and experimental results are presented that demonstrate the feasibility of the proposed schemes. Service providers can use the proposed schemes to provide a mutual nonrepudiation guarantee for database transactions in their service-level agreements.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128489561","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: 5

Impact and Limitations of Point-to-Point Performance on Collective Algorithms 点对点性能对集合算法的影响和限制

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-16 DOI: 10.1109/CCGrid.2016.44

S. Jha, E. Gabriel

引用次数: 2

High Performance On-demand Video Transcoding Using Cloud Services 使用云服务的高性能点播视频转码

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-01 DOI: 10.1109/CCGrid.2016.50

Xiangbo Li, M. Salehi, M. Bayoumi

{"title":"High Performance On-demand Video Transcoding Using Cloud Services","authors":"Xiangbo Li, M. Salehi, M. Bayoumi","doi":"10.1109/CCGrid.2016.50","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.50","url":null,"abstract":"Video streams, either in form of on-demand streaming or live streaming, usually have to be converted (i.e., transcoded) based on the characteristics (e.g., spatial resolution) of clients' devices. Transcoding is a computationally expensive operation, therefore, streaming service providers currently store numerous transcoded versions of the same video to serve different types of client devices. However, recent studies show that accessing video streams have a long tail distribution. That is, there are few popular videos that are frequently accessed while the majority of them are accessed infrequently. The idea we propose in this research is to transcode the infrequently accessed videos in a on-demand (i.e., lazy) manner. Due to the cost of maintaining infrastructure, streaming service providers (e.g., Netflix) are commonly using cloud services. However, the challenge in utilizing cloud services for video transcoding is how to deploy cloud resources in a cost-efficient manner without any major impact on the quality of video streams. To address the challenge, in this research, we present an architecture for on-demand transcoding of video streams. The architecture provides a platform for streaming service providers to utilize cloud resources in a cost-efficient manner and with respect to the Quality of Service (QoS) requirements of video streams. In particular, the architecture includes a QoS-aware scheduling component to efficiently map video streams to cloud resources, and a cost-efficient dynamic (i.e., elastic) resource provisioning policy that adapts the resource acquisition with respect to the video streaming QoS requirements.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"11 suppl_1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117274557","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: 23

EDISON: A Web-Based HPC Simulation Execution Framework for Large-Scale Scientific Computing Software 基于web的大规模科学计算软件HPC仿真执行框架

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-01 DOI: 10.1109/CCGrid.2016.31

Young-Kyoon Suh, Hoon Ryu, Hangi Kim, Kumwon Cho

{"title":"EDISON: A Web-Based HPC Simulation Execution Framework for Large-Scale Scientific Computing Software","authors":"Young-Kyoon Suh, Hoon Ryu, Hangi Kim, Kumwon Cho","doi":"10.1109/CCGrid.2016.31","DOIUrl":"https://doi.org/10.1109/CCGrid.2016.31","url":null,"abstract":"Computational science and engineering (CSE) researchers usually develop their own technology computer-aided design (TCAD) programs, accompanying large-scale computation and I/O on high-performance computing (HPC) resources like clusters or supercomputers. The researchers typically use command-line interface (CLI) such as Terminal to access the HPC resources. But CLI may not be a useful tool to those who conduct research or get educated with the TCAD software, because of their unfamiliarity with executing a series of commands. Thus there has been a strong need on a platform that assists domain-specific scientists to easily share, access, and run TCAD services. To satisfy the need, in this poster we present a novel cyber-environment, called \"Education-research Integration through Simulation On the Net\" (EDISON), which has been designed and implemented to access and run various TCAD software tools developed in five selected CSE fields over the past four years. The EDISON platform comprises three layers: application portal to browse and run TCAD software, middleware to manage metadata associated with TCAD software and handle online simulation jobs, and infrastructure to support network, storage, and computing resources. In this demo a user will interact with the EDISON platform to perform two representative use-case scenarios: 1) browsing various TCAD tools, selecting one of the tools, controlling with its parameters, and running a simulation job from the tool, and 2) constructing a scientific workflow of selected TCAD tools and executing the workflow. At the end, the user will visualize the completed simulation results.","PeriodicalId":103641,"journal":{"name":"2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126991720","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: 23

Hubbub-Scale: Towards Reliable Elastic Scaling under Multi-tenancy hubbam - scale:实现多租户下可靠的弹性扩展

2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) Pub Date : 2016-05-01 DOI: 10.1109/CCGrid.2016.71

N. Rameshan, Y. Liu, Leandro Navarro-Moldes, Vladimir Vlassov

引用次数: 13