Companion Proceedings of the10th International Conference on Utility and Cloud Computing最新文献

{"title":"Chair's Welcome SCCTSA Workshop","authors":"Z. Khan","doi":"10.1145/3147234.3148605","DOIUrl":"https://doi.org/10.1145/3147234.3148605","url":null,"abstract":"Welcome note for the 4th International workshop - Smart City Clouds: Technologies Systems and Applications co-located with 10 IEEE/ACM Utility and Cloud Computing Conference, Austin, Texas, USA, 5-8 December 2017.","PeriodicalId":128267,"journal":{"name":"Companion Proceedings of the10th International Conference on Utility and Cloud Computing","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126286282","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}

{"title":"A Big Data Architecture for Near Real-time Traffic Analytics","authors":"Yikai Gong, Paul Rimba, R. Sinnott","doi":"10.1145/3147234.3151010","DOIUrl":"https://doi.org/10.1145/3147234.3151010","url":null,"abstract":"Big data is a popular research topic that has brought about a range of new IT challenges and opportunities. The transport domain is one area that has much to benefit from big data platforms. It requires capabilities for processing voluminous amounts of heterogeneous data that is often created in near real time and at high velocity from a multitude of distributed sensors. It can also require the application of performance-oriented spatial data processing of such data. In this paper, we present a platform (SMASH) that tackles many of the specific challenges raised by the transport domain. We present a range of case studies applying SMASH to transport and other data used to understand traffic phenomenon across the State of Victoria, Australia. The novelty of this work is that this Cloud-based platform is not designed for a specific type of data or for a specific form of data processing. Rather it supports a range of data flavours with a range of data processing possibilities. In particular we show how the platform can be used for analyzing social media data used for traffic jam identification through spatial and temporal clustering tweets on the road network and compare the results with official real-time traffic data based on the Sydney Coordinated Adaptive Traffic System (SCATS - www.scats.com.au) that has been rolled out across Victoria.","PeriodicalId":128267,"journal":{"name":"Companion Proceedings of the10th International Conference on Utility and Cloud Computing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126476113","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}

{"title":"Companion Proceedings of the10th International Conference on Utility and Cloud Computing","authors":"A. Anjum, A. Sill, G. Fox, Yong Chen","doi":"10.1145/3147234","DOIUrl":"https://doi.org/10.1145/3147234","url":null,"abstract":"On behalf of the UCC 2017 program committee, it is our great pleasure to welcome you to the 10th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2017), held in Austin, TX, USA. \u0000 \u0000UCC is a premier IEEE/ACM conference covering all areas related to cloud and utility computing and provides an international forum for leading researchers and practitioners in this important and growing field. We are delighted to see UCC 2017 travels to Austin, Texas, and with the previous successful instances of this conference series, UCC 2017 brings academics and industrial researchers together to discuss leading innovations in cloud computing, utility computing, and other forms of advanced distributed computing, as well as numerous multidisciplinary research areas. \u0000 \u0000UCC 2017 received a total of 63 complete submissions. Each paper was reviewed by at least three reviewers, and many papers received four or five reviews. Overall we have 270 reviews, with 4.3 reviews per paper on average. The paper selection and decision were made with considering both reviews and online discussions. We accepted 17 out of the 63 total submissions into the main conference program, with an acceptance rate of 27%. In addition to these 17 submissions accepted as conference papers, we recommended 13 submissions as a workshop paper or a conference poster. Out of these 13 papers, the authors of 7 papers accepted our recommendation and will present their studies at a workshop of their choice, and one paper chose to present as a poster. We also recommended another 12 submissions directly as conference poster presentation, and several authors accepted this offer. \u0000 \u0000UCC 2017 truly represents an international forum for leading researchers and practitioners. The authors of submissions are from 31 countries, with United States (51 authors), Brazil (19 authors), United Kingdom (14 authors), and Canada (14 authors) rank among top four countries in terms of the number of authors. The program committee well represents an international community too, with a total of 72 members from 24 countries. We have an additional 37 external reviewers who contributed 48 reviews.","PeriodicalId":128267,"journal":{"name":"Companion Proceedings of the10th International Conference on Utility and Cloud Computing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126738916","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}

{"title":"Exploring Cross-Domain Data Dependencies for Smart Homes to Improve Energy Efficiency","authors":"S. Iram, T. Fernando, May Bassanino","doi":"10.1145/3147234.3148096","DOIUrl":"https://doi.org/10.1145/3147234.3148096","url":null,"abstract":"Over the past decade, the idea of smart homes has been conceived as a potential solution to counter energy crises or to at least mitigate its intensive destructive consequences in the residential building sector. Smart homes have emerged as one of the applications of Internet of Things (IoT) that enabled the use of technology to automate and customize home services with reference to users' preferences. However, the concept of smart homes is still not fully matured due to the weak handling of diverse datasets that can be exploited to promote more adaptive, personalised, and context aware capabilities. Furthermore, instead of just deploying integrated automated services in the homes, the focus should be to bring the concerns of potential stakeholders into consideration. In this paper, we have exploited the concepts of ontologies to capture all sorts of data (classes and their subclasses) that belong to one domain based on stakeholders' requirements analysis. We have also explored their significant associations with other datasets from another domain. In addition, this research work provides an insight about what sorts of interdependencies exist between different datasets across different ontological models such as Smart homes ontology model and ICT ontology model.","PeriodicalId":128267,"journal":{"name":"Companion Proceedings of the10th International Conference on Utility and Cloud Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125193053","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}

{"title":"Microservices: Granularity vs. Performance","authors":"Dharmendra Shadija, Mo Rezai, Richard Hill","doi":"10.1145/3147234.3148093","DOIUrl":"https://doi.org/10.1145/3147234.3148093","url":null,"abstract":"Microservice Architectures (MA) have the potential to increase the agility of software development. In an era where businesses require software applications to evolve to support emerging software requirements, particularly for Internet of Things (IoT) applications, we examine the issue of microservice granularity and explore its effect upon application latency. Two approaches to microservice deployment are simulated; the first with microservices in a single container, and the second with microservices partitioned across separate containers. We observed a negligible increase in service latency for the multiple container deployment over a single container.","PeriodicalId":128267,"journal":{"name":"Companion Proceedings of the10th International Conference on Utility and Cloud Computing","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131876386","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}