2012 IEEE Ninth International Conference on Services Computing最新文献_第4页

A Scalable Accounting Solution for Prepaid Services in Cloud Systems 云系统中预付费服务的可扩展会计解决方案

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.40

Lei Xu, Ewnetu Bayuh Lakew, F. Hernández-Rodriguez, E. Elmroth

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引用次数: 5

A Multi-agent Reinforcement Learning Model for Service Composition 面向服务组合的多智能体强化学习模型

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.58

Hongbing Wang, Xiaojun Wang, Xuan Zhou

引用次数: 2

How to Assess and Customize Service Value for IT Cloud Services Clients 如何为IT云服务客户评估和定制服务价值

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.70

K. Ramaswami, A. Sailer

引用次数: 0

Towards an Automata-Based Semantic Web Services Composition Method in Context-Aware Environment 上下文感知环境下基于自动机的语义Web服务组合方法研究

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.27

Zhichao Zhang, Weiping Li, Zhonghai Wu, Wei Tan

引用次数: 12

Event-Driven Mashup Orchestration with Scala 使用Scala进行事件驱动的Mashup编排

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.41

Michele Stecca, Martino Fornasa, Nicholas DallArmellina, M. Maresca

引用次数: 2

A Service Binding Framework for Open Environment 面向开放环境的服务绑定框架

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.74

Masahiro Tanaka, Yohei Murakami, Donghui Lin, T. Ishida

引用次数: 3

Utilizing PCFGs for Modeling and Learning Service Compositions in Sensor Networks 利用pcfg建模和学习传感器网络中的服务组合

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.22

S. Geyik, E. Bulut, B. Szymanski

{"title":"Utilizing PCFGs for Modeling and Learning Service Compositions in Sensor Networks","authors":"S. Geyik, E. Bulut, B. Szymanski","doi":"10.1109/SCC.2012.22","DOIUrl":"https://doi.org/10.1109/SCC.2012.22","url":null,"abstract":"Service composition in sensor networks combines elementary services with a specific functionality to create a service with higher level functionality. The previous efforts in automating composition were sending full information about all services across the entire sensor network, creating a security risk and imposing significant communication overhead. Furthermore, learning based composition or error detection methods do not consider global information, leading to inefficiencies in the generated composition graphs. In this paper, we propose a probabilistic context-free grammar (PCFG) based modeling technique to construct service compositions. The successful compositions created for the given application are treated as statements belonging to an efficient composition PCFG of this application. The given set of such compositions is used to derive this PCFG automatically. Future composition could be then easily constructed with the help of such PCFG. We present our methodology for achieving such modeling and provide examples of its use to demonstrate its advantage over previous work. We also evaluate the resulting improvements in performance of compositions and in the costs of their creation.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124184755","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

Profit-Based Experimental Analysis of IaaS Cloud Performance: Impact of Software Resource Allocation 基于利润的IaaS云性能实验分析:软件资源分配的影响

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.85

Jack Li, Qingyang Wang, D. Jayasinghe, Simon Malkowski, Pengcheng Xiong, C. Pu, Yasuhiko Kanemasa, Motoyuki Kawaba

{"title":"Profit-Based Experimental Analysis of IaaS Cloud Performance: Impact of Software Resource Allocation","authors":"Jack Li, Qingyang Wang, D. Jayasinghe, Simon Malkowski, Pengcheng Xiong, C. Pu, Yasuhiko Kanemasa, Motoyuki Kawaba","doi":"10.1109/SCC.2012.85","DOIUrl":"https://doi.org/10.1109/SCC.2012.85","url":null,"abstract":"High resource utilization is an important goal in achieving high return on investment in cloud environments. Guaranteed quality of service (QoS) is an important goal for web-facing applications such as e-commerce. Achieving both high utilization and high QoS simultaneously is a significant challenge, since high utilization often implies more QoS failures such as long response times. In this paper, we adopt a profit model based on response time (i.e., decreasing or negative revenues for increasing query answer response time) to represent the QoS requirements. Our data shows that such a profit model often yields different analytical results compared to traditional performance metrics such as average throughput. Using extensive experimental measurements (on the same hardware platform and software stack) of the standard RUBBoS n-tier benchmark, we study the impact of different allocations of software resources such as the size of thread pools in various servers in an n-tier system. First, the profit model emphasizes the importance of appropriate allocations, showing a difference of up to 48.6% when system utilization is high (over 80%). Second, our experiments show that over-allocation of thread pool may lead to unnecessary consumption of critical resources (e.g., CPU) that reduce profits by up to 84.8%. Third, we found that under-allocation of thread pool in one server may lead to under-utilization of several servers downstream in an n-tier system, also reducing profits by up to 52.8%. Our data shows that the best allocation depends on several system parameters, including resource availability. We designed an adaptive algorithm to find the best allocations and show its effectiveness through our experiments and analyses.","PeriodicalId":178841,"journal":{"name":"2012 IEEE Ninth International Conference on Services Computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115650859","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: 29

Web Service andWorkflow Abstractions to Large Scale Nuclear Physics Calculations 大规模核物理计算的Web服务和工作流抽象

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.112

Chathura Herath, Fang Liu, S. Marru, Lahiru Gunathilake, M. Sosonkina, J. Vary, P. Maris, M. Pierce

引用次数: 2

Collective Intelligence Applications in IT Services Business 集体智慧在资讯科技服务业的应用

2012 IEEE Ninth International Conference on Services Computing Pub Date : 2012-06-24 DOI: 10.1109/SCC.2012.55

M. Vukovic, O. Stewart

引用次数: 7