2015 IEEE International Conference on Autonomic Computing最新文献_第7页

Revenue Driven Resource Allocation for Virtualized Data Centers 虚拟化数据中心的收益驱动资源分配

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.40

Sajib Kundu, R. Rangaswami, Ming Zhao, Ajay Gulati, K. Dutta

引用次数: 13

iKaaS Data Modeling: A Data Model for Community Services and Environment Monitoring in Smart City iKaaS数据建模:智慧城市社区服务与环境监测的数据模型

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.64

Kazuo Hashimoto, Keiji Yamada, K. Tabata, Michio Oda, T. Suganuma, A. Biswas, P. Vlacheas, V. Stavroulaki, Dimitris Kelaidonis, A. Georgakopoulos

{"title":"iKaaS Data Modeling: A Data Model for Community Services and Environment Monitoring in Smart City","authors":"Kazuo Hashimoto, Keiji Yamada, K. Tabata, Michio Oda, T. Suganuma, A. Biswas, P. Vlacheas, V. Stavroulaki, Dimitris Kelaidonis, A. Georgakopoulos","doi":"10.1109/ICAC.2015.64","DOIUrl":"https://doi.org/10.1109/ICAC.2015.64","url":null,"abstract":"Intelligent Knowledge as a Service (iKaaS) is an ambitious project aiming at integrating sensor management using Internet of Things (IoT) and cloud services by employing sensor data. The platform design covers self-healing functions based on self-awareness as well as basic functions such as inter-cloud, security/privacy management, and devices and data management. From the viewpoint of application development, ontology sharing is the most important to integrate services. This paper, the first step towards ontology sharing, defines the iKaaS data model as one that integrates data models used in all applications in the project. The data defined in the iKaaS data model is converted into RDF format and stored in the RDF database. The reasoning mechanism in semantic web allows the semantic integration of data and applications. The iKaaS project is developing a prototype community service, town management and healthcare, in Tagonishi's Smart City. Presenting the iKaaS data model for these said services, this paper emphasizes the necessity of higher contextual awareness to achieve the goal of a better-fitted personalization for the individual.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"7 1","pages":"301-306"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73446086","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

Framework for Intelligent Message Routing Policy Adaptation 智能消息路由策略适配框架

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.35

N. Guizani, J. Fayn

{"title":"Framework for Intelligent Message Routing Policy Adaptation","authors":"N. Guizani, J. Fayn","doi":"10.1109/ICAC.2015.35","DOIUrl":"https://doi.org/10.1109/ICAC.2015.35","url":null,"abstract":"Monitoring message workflow transmission is a very challenging problem, especially in pervasive environments, mainly because of the wide range of unexpected events (e.g. Human and material resources unavailability) and context changes (e.g. Source and target localizations) that may occur at run-time. In this paper, we propose an information system and services orchestration framework enabling intelligent message routing policy adaptation. Our objective is to build a reliable routing strategy that can autonomously and intelligently adapt its own behavior and decisions according to source and target context changes as well as to controlled message status (e.g. Exceeded deadlines for message reception). We present a solution that emphasizes some cutting-edge characteristics that we believe are crucial for enhancing the quality of message communication, such as intelligence, controllability, scalability, adaptivity and personalization. The routing decisions can be adapted at different levels of decision-making such as message itinerary, delay for message treatment, etc., by means of advanced AI methods that we detail for some of the most sensitive self-adaptive services.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"43 1","pages":"235-238"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86473965","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

Automated Adaptive Restart for Accelerating Task Completion in Cloud Offloading Systems 加速云卸载系统任务完成的自动自适应重启

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.11

Qiushi Wang, K. Wolter

引用次数: 4

Social Trove: A Self-Summarizing Storage Service for Social Sensing 社会宝藏:一种面向社会感知的自总结存储服务

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.47

Md. Tanvir Al Amin, Shen Li, Muntasir Raihan Rahman, P. Seetharamu, Shiguang Wang, T. Abdelzaher, Indranil Gupta, M. Srivatsa, R. Ganti, Reaz Ahmed, H. Le

{"title":"Social Trove: A Self-Summarizing Storage Service for Social Sensing","authors":"Md. Tanvir Al Amin, Shen Li, Muntasir Raihan Rahman, P. Seetharamu, Shiguang Wang, T. Abdelzaher, Indranil Gupta, M. Srivatsa, R. Ganti, Reaz Ahmed, H. Le","doi":"10.1109/ICAC.2015.47","DOIUrl":"https://doi.org/10.1109/ICAC.2015.47","url":null,"abstract":"The increasing availability of smartphones, cameras, and wearables with instant data sharing capabilities, and the exploitation of social networks for information broadcast, heralds a future of real-time information overload. With the growing excess of worldwide streaming data, such as images, geotags, text annotations, and sensory measurements, an increasingly common service will become one of data summarization. The objective of such a service will be to obtain a representative sampling of large data streams at a configurable granularity, in real-time, for subsequent consumption by a range of data-centric applications. This paper describes a general-purpose self-summarizing storage service, called Social Trove, for social sensing applications. The service summarizes data streams from human sources, or sensors in their possession, by hierarchically clustering received information in accordance with an application-specific distance metric. It then serves a sampling of produced clusters at a configurable granularity in response to application queries. While Social Trove is a general service, we illustrate its functionality and evaluate it in the specific context of workloads collected from Twitter. Results show that Social Trove supports a high query throughput, while maintaining a low access latency to the produced real-time application-specific data summaries. As a specific application case-study, we implement a fact-finding service on top of Social Trove.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"12 1","pages":"41-50"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89920700","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: 19

A Symbiotic Cognitive Computing Perspective on Autonomic Computing 自主计算的共生认知计算视角

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.16

J. Kephart, J. Lenchner

{"title":"A Symbiotic Cognitive Computing Perspective on Autonomic Computing","authors":"J. Kephart, J. Lenchner","doi":"10.1109/ICAC.2015.16","DOIUrl":"https://doi.org/10.1109/ICAC.2015.16","url":null,"abstract":"Symbiotic Cognitive Systems (SCS) are multi-agent systems comprising both human and software agents that are designed to collectively perform cognitive tasks such as decision-making better than humans or software agents can unaided. Autonomic Computing Systems (ACS) are multi-agent systems that manage applications as well as software and hardware resources in accordance with goals specified by human administrators and users. SCS and ACS share some key characteristics. First, both are designed to extend human intellectual capabilities, and as such they require effective means by which humans can communicate their objectives to the computing system. Second, their natural architecture is a multi-agent system in which dozens, hundreds or even more semi-autonomous entities interact. In both SCS and ACS, issues of inter-agent communication and coordination come to the fore. We report our experience with a moderate-scale SCS prototype that helps human experts make decisions with financial impacts ranging from millions to even billions of US: corporate mergers and acquisitions. Taking advantage of the commonalities, we translate this experience into insights that may benefit future research on ACS, and recommend a stronger focus on agent-human communication and building realistic system prototypes.","PeriodicalId":6643,"journal":{"name":"2015 IEEE International Conference on Autonomic Computing","volume":"6 1","pages":"109-114"},"PeriodicalIF":0.0,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73232297","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: 25

Distributed Rendering in an Open Self-Organised Trusted Desktop Grid 开放自组织可信桌面网格中的分布式渲染

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.66

Jan Kantert, H. Spiegelberg, Sven Tomforde, J. Hähner, C. Müller-Schloer

引用次数: 13

Optimized Storage and Fast Retrieval of Large Monitoring Datasets without Compromising Granularity 不影响粒度的大型监测数据集的优化存储和快速检索

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.53

Sebastien Cabaniols, Nathalie Viollet, Clement Poulain

引用次数: 0

Runtime Evolution of the Adaptation Logic in Self-Adaptive Systems 自适应系统中自适应逻辑的运行演化

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.20

F. Roth, Christian Krupitzer, C. Becker

引用次数: 9

Responsible Objects: Towards Self-Healing Internet of Things Applications 负责任的对象:走向自我修复的物联网应用

2015 IEEE International Conference on Autonomic Computing Pub Date : 2015-07-07 DOI: 10.1109/ICAC.2015.60

Rafael Angarita

引用次数: 21