{"title":"Modeling for Dynamic Cloud Scheduling Via Migration of Virtual Machines","authors":"Wubin Li, Johan Tordsson, E. Elmroth","doi":"10.1109/CloudCom.2011.31","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.31","url":null,"abstract":"Cloud brokerage mechanisms are fundamental to reduce the complexity of using multiple cloud infrastructures to achieve optimal placement of virtual machines and avoid the potential vendor lock-in problems. However, current approaches are restricted to static scenarios, where changes in characteristics such as pricing schemes, virtual machine types, and service performance throughout the service life-cycle are ignored. In this paper, we investigate dynamic cloud scheduling use cases where these parameters are continuously changed, and propose a linear integer programming model for dynamic cloud scheduling. Our model can be applied in various scenarios through selections of corresponding objectives and constraints, and offers the flexibility to express different levels of migration overhead when restructuring an existing infrastructure. Finally, our approach is evaluated using commercial clouds parameters in selected simulations for the studied scenarios. Experimental results demonstrate that, with proper parametrizations, our approach is feasible.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127045968","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":"Monitoring Intrusions and Security Breaches in Highly Distributed Cloud Environments","authors":"Aryan TaheriMonfared, M. Jaatun","doi":"10.1109/CloudCom.2011.119","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.119","url":null,"abstract":"Cloud computing is a new computing model, and security is ranked first among its challenges. This paper reviews existing security monitoring mechanisms compared with new challenges which are caused by this new model. We highlight possible weaknesses in existing monitoring mechanisms, and propose approaches to mitigate them.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123409289","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}
Cristina Alcaraz, Isaac Agudo, David Nuñez, Javier López
{"title":"Managing Incidents in Smart Grids à la Cloud","authors":"Cristina Alcaraz, Isaac Agudo, David Nuñez, Javier López","doi":"10.1109/CloudCom.2011.79","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.79","url":null,"abstract":"Over the last decade, the Cloud Computing paradigm has emerged as a panacea for many problems in traditional IT infrastructures. Much has been said about the potential of Cloud Computing in the context of the Smart Grid, but unfortunately it is still relegated to a second layer when it comes to critical systems. Although the advantages of outsourcing these kinds of applications to the cloud is clear, data confidentiality and operational privacy stand as mayor drawbacks. In this paper, we describe some security mechanisms, and specifically, some cryptographic schemes, that will help in a better integration of Smart Grids and Clouds. We propose the use of Virtual SCADA in the Cloud (VS-Cloud) as a means to improve reliability and efficiency whilst maintaining the same protection level as in traditional SCADA architectures.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131577669","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":"Scalable Service Containers","authors":"Sami Yangui, Mohamed Mohamed, S. Tata, S. Moalla","doi":"10.1109/CloudCom.2011.54","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.54","url":null,"abstract":"Cloud Computing is a new supplement, consumption, and delivery model for IT services based on Internet protocols. It typically involves provisioning of dynamically scalable and often virtualized resources. In this environment, there are several issues related to the inadequacies of hosting platforms and mechanisms to ensure the smooth running of service-based applications (communication protocols, ESB, Service containers, etc.). In particular, architectures and implementations of service containers are not adapted to Cloud environments. In this paper, we present a new service container dedicated to one deployed service that avoids the processing limits of classical services containers. Our approach addresses scalability by reducing memory consumption and response time. The proposed service container is evaluated in several situations against well known services containers within a real Cloud Computing network.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126456727","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 Semantic Interoperability Framework for Cloud Platform as a Service","authors":"Nikos Loutas, Eleni Kamateri, K. Tarabanis","doi":"10.1109/CloudCom.2011.45","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.45","url":null,"abstract":"Given the rapid uptake and the great diversity of PaaS offerings, understanding semantic interoperability at the PaaS level is essential for supporting inter-Cloud cooperation, seamless information exchange and application and data portability. In this vein, this paper introduces a PaaS semantic interoperability framework (PSIF). PSIF studies, models and tries to resolve semantic interoperability conflicts raised during the deployment or the migration of an application by defining the following dimensions: Fundamental PaaS Entities, Types of Semantics, and Levels of Semantic Conflicts. In the context of this paper, the development of common PaaS models and standardized management interfaces are raised as primary requirements in this context. PaaS architectures can then be augmented with a semantic layer that would host the common models and would be the link between heterogeneous PaaS offerings.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"311 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131677797","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":"Applications and Evaluation of In-memory MapReduce","authors":"Kim-Thomas Rehmann, M. Schöttner","doi":"10.1109/CloudCom.2011.19","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.19","url":null,"abstract":"In-memory storage techniques provide cloud applications with cheap, fast and large-scale RAM-based storage. By replicating data and providing adequate consistency control mechanisms, in-memory storage can simplify the design and implementation of highly scalable distributed applications. We argue that in-memory storage can increase the flexibility of the MapReduce parallel programming model without requiring additional communication facilities to propagate data updates. In this paper, we present several applications for our in-memory MapReduce framework from diverse problem domains including iterative and on-line data processing.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130789797","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}
R. Nanduri, N. Maheshwari, A. Reddyraja, Vasudeva Varma
{"title":"Job Aware Scheduling Algorithm for MapReduce Framework","authors":"R. Nanduri, N. Maheshwari, A. Reddyraja, Vasudeva Varma","doi":"10.1109/CloudCom.2011.112","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.112","url":null,"abstract":"MapReduce framework has received a wide acclaim over the past few years for large scale computing. It has become a standard paradigm for batch oriented workloads. As the adoption of this paradigm has increased rapidly, scheduling of these MapReduce jobs has become a problem of great interest in research community. We propose an approach which tries to maintain harmony among the jobs running on the cluster, and in turn decrease their runtime. In our model, the scheduler is made aware of different types of jobs running on the cluster. The scheduler tries to allocate a task on a node if the incoming task does not affect the tasks already running on that node. From the list of available pending tasks, our algorithm selects the one that is most compatible with the tasks already running on that node. We bring up heuristic and machine learning based solutions to our approach and try to maintain a resource balance on the cluster by not overloading any of the nodes, thereby reducing the overall runtime of the jobs. The results show a saving of runtime of around 21% in the case of heuristic based approach and around 27% in the case of machine learning based approach when compared to Yahoo's Capacity scheduler.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132689628","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":"Investigating the Impact of Deployment Configuration and User Demand on a Social Network Application in the Amazon EC2 Cloud","authors":"Matheus Cunha, N. Mendonça, Américo Sampaio","doi":"10.1109/CloudCom.2011.115","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.115","url":null,"abstract":"One of the main challenges faced by current users of infrastructure-as-a-service (IaaS) clouds are the difficulties to estimate cloud resources according to their application needs. Even though cloud platforms are elastic and provide fast means to acquire or release resources it is important to understand the best ways to do that considering a diversity of providers with many different resource types and prices. This work reports on an experimental investigation conducted on a popular cloud benchmark based on a social network application running on top of the Amazon EC2 cloud. Our experiments aim at finding cost-effective ways to select the different EC2 resource types and deployment configurations based on the demand imposed to the application (measured in number of simultaneous users) and identify the configuration that gives the best return in terms of its cost per user.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132757432","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":"Information Stewardship in Cloud Ecosystems: Towards Models, Economics, and Delivery","authors":"A. Baldwin, D. Pym, M. Sadler, S. Shiu","doi":"10.1109/CloudCom.2011.121","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.121","url":null,"abstract":"We discuss the concept of information stewardship in cloud-based business ecosystems. The constituent concepts of stewardship -- which we believe will be crucial to the successful development of cloud-based business of all kinds -- extend those of security to encompass concepts of objectives, ethics/values, sustainability, and resilience: all familiar from the stewardship of natural resources. Our view is based on rigorous approaches from mathematical systems modelling and economics, and is informed by concepts from natural resource management and information assurance.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132098899","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}
S. Lynden, Y. Tanimura, I. Kojima, Akiyoshi Matono
{"title":"Dynamic Data Redistribution for MapReduce Joins","authors":"S. Lynden, Y. Tanimura, I. Kojima, Akiyoshi Matono","doi":"10.1109/CloudCom.2011.111","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.111","url":null,"abstract":"MapReduce has become a popular method for data processing, in particular for large scale datasets, due to its accessibility as a scalable yet convenient programming paradigm. Data processing tasks often involve joins, and the repartition and fragment-replicate joins are two widely-used join algorithms utilised within the MapReduce framework. This paper presents a multi-join supporting tuple redistribution, building on both the repartition and fragment-replicate joins. Hadoop is used to demonstrate how reduce tasks may improve performance by passing intermediate results to other reduce tasks that are better able to process them using Apache ZooKeeper as a means of communication and data transfer. A performance analysis is presented showing the technique has the potential to reduce response times when processing multiple joins in single MapReduce jobs.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114871342","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}