G. Pirrò, Paolo Trunfio, D. Talia, P. Missier, C. Goble
The increasing number of available online services demands distributed architectures to promote scalability as well as semantics to enable their precise and efficient retrieval. Two common approaches toward this goal are Semantic Overlay Networks (SONs) and Distributed Hash Tables (DHTs) with semantic extensions. This paper presents ERGOT, a system that combines DHTs and SONs to enable semantic-based service discovery in distributed infrastructures such as Grids and Clouds. ERGOT takes advantage of semantic annotations that enrich service specifications in two ways: (i) services are advertised in the DHT on the basis of their annotations, thus allowing to establish a SON among service providers, (ii) annotations enable semantic-based service matchmaking, using a novel similarity measure between service requests and descriptions. Experimental evaluations confirmed the efficiency of ERGOT in terms of accuracy of search and network traffic.
{"title":"ERGOT: A Semantic-Based System for Service Discovery in Distributed Infrastructures","authors":"G. Pirrò, Paolo Trunfio, D. Talia, P. Missier, C. Goble","doi":"10.1109/CCGRID.2010.24","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.24","url":null,"abstract":"The increasing number of available online services demands distributed architectures to promote scalability as well as semantics to enable their precise and efficient retrieval. Two common approaches toward this goal are Semantic Overlay Networks (SONs) and Distributed Hash Tables (DHTs) with semantic extensions. This paper presents ERGOT, a system that combines DHTs and SONs to enable semantic-based service discovery in distributed infrastructures such as Grids and Clouds. ERGOT takes advantage of semantic annotations that enrich service specifications in two ways: (i) services are advertised in the DHT on the basis of their annotations, thus allowing to establish a SON among service providers, (ii) annotations enable semantic-based service matchmaking, using a novel similarity measure between service requests and descriptions. Experimental evaluations confirmed the efficiency of ERGOT in terms of accuracy of search and network traffic.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124353488","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}
This paper discusses our experience in building SPIRE, an autonomic system for service provision. The architecture consists of a set of hosted Web Services subject to QoS constraints, and a certain number of servers used to run session-based traffic. Customers pay for having their jobs run, but require in turn certain quality guarantees: there are different SLAs specifying charges for running jobs and penalties for failing to meet promised performance metrics. The system is driven by an utility function, aiming at optimizing the average earned revenue per unit time. Demand and performance statistics are collected, while traffic parameters are estimated in order to make dynamic decisions concerning server allocation and admission control. Different utility functions are introduced and a number of experiments aiming at testing their performance are discussed. Results show that revenues can be dramatically improved by imposing suitable conditions for accepting incoming traffic, the proposed system performs well under different traffic settings, and it successfully adapts to changes in the operating environment.
{"title":"Towards Autonomic Service Provisioning Systems","authors":"M. Mazzucco","doi":"10.1109/CCGRID.2010.125","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.125","url":null,"abstract":"This paper discusses our experience in building SPIRE, an autonomic system for service provision. The architecture consists of a set of hosted Web Services subject to QoS constraints, and a certain number of servers used to run session-based traffic. Customers pay for having their jobs run, but require in turn certain quality guarantees: there are different SLAs specifying charges for running jobs and penalties for failing to meet promised performance metrics. The system is driven by an utility function, aiming at optimizing the average earned revenue per unit time. Demand and performance statistics are collected, while traffic parameters are estimated in order to make dynamic decisions concerning server allocation and admission control. Different utility functions are introduced and a number of experiments aiming at testing their performance are discussed. Results show that revenues can be dramatically improved by imposing suitable conditions for accepting incoming traffic, the proposed system performs well under different traffic settings, and it successfully adapts to changes in the operating environment.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115345016","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}
We propose a dynamic auction mechanism to solve the allocation problem of computation capacity in the environment of cloud computing. Truth-telling property holds when we apply a second-priced auction mechanism into the resource allocation problem. Thus, the cloud service provider (CSP) can assure reasonable profit and efficient allocation of its computation resources. In the cases that the number of users and resources are large enough, potential problems in second-priced auction mechanism, including the variation of revenue, will not be weighted seriously since the law of large number holds in this case.
{"title":"Dynamic Auction Mechanism for Cloud Resource Allocation","authors":"Wei-Yu Lin, Guan-Yu Lin, Hung-Yu Wei","doi":"10.1109/CCGRID.2010.92","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.92","url":null,"abstract":"We propose a dynamic auction mechanism to solve the allocation problem of computation capacity in the environment of cloud computing. Truth-telling property holds when we apply a second-priced auction mechanism into the resource allocation problem. Thus, the cloud service provider (CSP) can assure reasonable profit and efficient allocation of its computation resources. In the cases that the number of users and resources are large enough, potential problems in second-priced auction mechanism, including the variation of revenue, will not be weighted seriously since the law of large number holds in this case.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"251 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115638412","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}
We present a policy-centered QoS meta-model which can be used by service providers and consumers alike to express capabilities, requirements, constraints, and general management characteristics relevant for SLA establishment in service aggregations. We also provide a QoS assertion model which is generic, domain-independent and conforming to the WS-Policy syntax and semantics. Using these two models, assertions over acceptable and required values for QoS properties can be expressed across the different service layers and service roles.
{"title":"Policy-Based Management of QoS in Service Aggregations","authors":"Mohan Baruwal Chhetri, Quoc Bao Vo, R. Kowalczyk","doi":"10.1109/CCGRID.2010.95","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.95","url":null,"abstract":"We present a policy-centered QoS meta-model which can be used by service providers and consumers alike to express capabilities, requirements, constraints, and general management characteristics relevant for SLA establishment in service aggregations. We also provide a QoS assertion model which is generic, domain-independent and conforming to the WS-Policy syntax and semantics. Using these two models, assertions over acceptable and required values for QoS properties can be expressed across the different service layers and service roles.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122635240","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}
Geo-sciences involve large-scale parallel models, high resolution real time data from highly asynchronous and heterogeneous sensor networks and instruments, and complex analysis and visualization tools. Scientific workflows are an accepted approach to executing sequences of tasks on scientists’ behalf during scientific investigation. Many geo-science workflows have the need to interact with sensors that produce large continuous streams of data, but programming models provided by scientific workflows are not equipped to handle continuous data streams. This paper proposes a framework that utilizes scientific workflow infrastructure and the benefits of complex event processing to compensate for the impedance mismatch between scientific workflows and continuous data streams. Further we propose and formalize new workflow semantics that would allow the users to not only incorporate stream in scientific workflow, but also make use of the functionalities provided by the complex event processing systems effective within the scientific workflows.
{"title":"Streamflow Programming Model for Data Streaming in Scientific Workflows","authors":"Chathura Herath, Beth Plale","doi":"10.1109/CCGRID.2010.116","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.116","url":null,"abstract":"Geo-sciences involve large-scale parallel models, high resolution real time data from highly asynchronous and heterogeneous sensor networks and instruments, and complex analysis and visualization tools. Scientific workflows are an accepted approach to executing sequences of tasks on scientists’ behalf during scientific investigation. Many geo-science workflows have the need to interact with sensors that produce large continuous streams of data, but programming models provided by scientific workflows are not equipped to handle continuous data streams. This paper proposes a framework that utilizes scientific workflow infrastructure and the benefits of complex event processing to compensate for the impedance mismatch between scientific workflows and continuous data streams. Further we propose and formalize new workflow semantics that would allow the users to not only incorporate stream in scientific workflow, but also make use of the functionalities provided by the complex event processing systems effective within the scientific workflows.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128749109","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}
Replicated distributed file systems are designed to store large file reliably across lots of machines, and it arouse the problem of selecting the nearest replica for clients. In this paper, we propose Rigel, a Network Coordinates (NC) based nearest replica selection service, which is an effective infrastructure to select the nearest replica for client in a scalable and lightweight way. Our simulation results have demonstrated that Rigel can at least reduce the read latency between clients and replicas by 20% when compared to the replica selection strategy in Hadoop Distributed File System.
{"title":"Rigel: A Scalable and Lightweight Replica Selection Service for Replicated Distributed File System","authors":"Yuan Lin, Yang Chen, Guodong Wang, Beixing Deng","doi":"10.1109/CCGRID.2010.51","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.51","url":null,"abstract":"Replicated distributed file systems are designed to store large file reliably across lots of machines, and it arouse the problem of selecting the nearest replica for clients. In this paper, we propose Rigel, a Network Coordinates (NC) based nearest replica selection service, which is an effective infrastructure to select the nearest replica for client in a scalable and lightweight way. Our simulation results have demonstrated that Rigel can at least reduce the read latency between clients and replicas by 20% when compared to the replica selection strategy in Hadoop Distributed File System.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133619245","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}
C. Teixeira, Ricardo Azevedo, J. S. Pinto, Tiago Batista
Web 2.0 started a paradigm shift concerning content generation. Users spend hours browsing and producing contents to share, most of the times, freely. During these activities, their laptops and home PCs are considerably underused. By combining the amount of idle processing capacity with increasingly fast internet accesses, every computer can be considered as a computational “nearby” resource. The question is: what to do with them? This paper explores how these resources can be used to give something back to the user in a secure and private way.
Web 2.0开始了关于内容生成的范式转变。用户花费数小时浏览和制作内容来分享，大多数时候是免费的。在这些活动中，他们的笔记本电脑和家用个人电脑没有得到充分利用。通过将大量的空闲处理能力与日益快速的互联网访问相结合，每台计算机都可以被视为计算性的“附近”资源。问题是:如何处理它们?本文探讨了如何使用这些资源以安全和私密的方式将某些内容返回给用户。
{"title":"User Provided Cloud Computing","authors":"C. Teixeira, Ricardo Azevedo, J. S. Pinto, Tiago Batista","doi":"10.1109/CCGRID.2010.37","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.37","url":null,"abstract":"Web 2.0 started a paradigm shift concerning content generation. Users spend hours browsing and producing contents to share, most of the times, freely. During these activities, their laptops and home PCs are considerably underused. By combining the amount of idle processing capacity with increasingly fast internet accesses, every computer can be considered as a computational “nearby” resource. The question is: what to do with them? This paper explores how these resources can be used to give something back to the user in a secure and private way.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134474177","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}
There is growing interest in large-scale systems where globally distributed and commoditized resources can be shared and traded, such as peer-to-peer networks, grids, and cloud computing. Users of these systems are rational and maximize their own interest when consuming and contributing shared resources, even if by doing so they affect the overall efficiency of the system. To manage rational users, resource pricing and allocation can provide the necessary incentives for users to behave such that the overall efficiency can be maximized. In this paper, we propose a dynamic pricing mechanism for the allocation of shared resources, and evaluate its performance. In contrast with several existing trading models, our scheme is designed to allocate a request with multiple resource types, such that the user does not have to aggregate different resource types manually. We formally prove the economic properties of our pricing scheme using the mechanism design framework. We perform both theoretical and simulation analysis to evaluate the economic and computational efficiency of the allocation and the scalability of the mechanism. Our simulations are validated against a prototype implementation on PlanetLab.
{"title":"On Economic and Computational-Efficient Resource Pricing in Large Distributed Systems","authors":"Marian Mihailescu, Y. M. Teo","doi":"10.1109/CCGRID.2010.124","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.124","url":null,"abstract":"There is growing interest in large-scale systems where globally distributed and commoditized resources can be shared and traded, such as peer-to-peer networks, grids, and cloud computing. Users of these systems are rational and maximize their own interest when consuming and contributing shared resources, even if by doing so they affect the overall efficiency of the system. To manage rational users, resource pricing and allocation can provide the necessary incentives for users to behave such that the overall efficiency can be maximized. In this paper, we propose a dynamic pricing mechanism for the allocation of shared resources, and evaluate its performance. In contrast with several existing trading models, our scheme is designed to allocate a request with multiple resource types, such that the user does not have to aggregate different resource types manually. We formally prove the economic properties of our pricing scheme using the mechanism design framework. We perform both theoretical and simulation analysis to evaluate the economic and computational efficiency of the allocation and the scalability of the mechanism. Our simulations are validated against a prototype implementation on PlanetLab.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134595350","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}
Applications structured as parallel task graphs exhibit both data and task parallelism, and arise in many domains. Scheduling these applications on parallel platforms has been a long-standing challenge. In the case of a single homogeneous cluster, most of the existing algorithms focus on the reduction of the application completion time (make span). But in presence of resource managers such as batch schedulers and due to accentuated pressure on energy concerns, the produced schedules also have to be efficient in terms of resource usage. In this paper we propose a novel bi-criteria algorithm, called biCPA, able to optimize these two performance metrics either simultaneously or separately. Using simulation over a wide range of experimental scenarios, we find that biCPA leads to better results than previously published algorithms.
{"title":"A Bi-criteria Algorithm for Scheduling Parallel Task Graphs on Clusters","authors":"F. Desprez, F. Suter","doi":"10.1109/CCGRID.2010.43","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.43","url":null,"abstract":"Applications structured as parallel task graphs exhibit both data and task parallelism, and arise in many domains. Scheduling these applications on parallel platforms has been a long-standing challenge. In the case of a single homogeneous cluster, most of the existing algorithms focus on the reduction of the application completion time (make span). But in presence of resource managers such as batch schedulers and due to accentuated pressure on energy concerns, the produced schedules also have to be efficient in terms of resource usage. In this paper we propose a novel bi-criteria algorithm, called biCPA, able to optimize these two performance metrics either simultaneously or separately. Using simulation over a wide range of experimental scenarios, we find that biCPA leads to better results than previously published algorithms.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132930614","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}
To date, the literature on software architecture for cloud computing is focussed largely on the service provider, and inadequately reflects the fact that cloud computing is a form of client-server relationship. Architectures must also encompass the software and devices that users utilise in order to invoke functions in the cloud, and intermediary functions. A further problem with analyses to date is inadequate reflection of the risks that users are subject to when they use cloud services. This paper proposes a comprehensive model that reflects user needs, and identifies implications of the model for computer scientists working in the area.
{"title":"User Requirements for Cloud Computing Architecture","authors":"R. Clarke","doi":"10.1109/CCGRID.2010.20","DOIUrl":"https://doi.org/10.1109/CCGRID.2010.20","url":null,"abstract":"To date, the literature on software architecture for cloud computing is focussed largely on the service provider, and inadequately reflects the fact that cloud computing is a form of client-server relationship. Architectures must also encompass the software and devices that users utilise in order to invoke functions in the cloud, and intermediary functions. A further problem with analyses to date is inadequate reflection of the risks that users are subject to when they use cloud services. This paper proposes a comprehensive model that reflects user needs, and identifies implications of the model for computer scientists working in the area.","PeriodicalId":444485,"journal":{"name":"2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133984749","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}
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