423,491 research outputs found

    Reconsidering big data security and privacy in cloud and mobile cloud systems

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    Large scale distributed systems in particular cloud and mobile cloud deployments provide great services improving people\u27s quality of life and organizational efficiency. In order to match the performance needs, cloud computing engages with the perils of peer-to-peer (P2P) computing and brings up the P2P cloud systems as an extension for federated cloud. Having a decentralized architecture built on independent nodes and resources without any specific central control and monitoring, these cloud deployments are able to handle resource provisioning at a very low cost. Hence, we see a vast amount of mobile applications and services that are ready to scale to billions of mobile devices painlessly. Among these, data driven applications are the most successful ones in terms of popularity or monetization. However, data rich applications expose other problems to consider including storage, big data processing and also the crucial task of protecting private or sensitive information. In this work, first, we go through the existing layered cloud architectures and present a solution addressing the big data storage. Secondly, we explore the use of P2P Cloud System (P2PCS) for big data processing and analytics. Thirdly, we propose an efficient hybrid mobile cloud computing model based on cloudlets concept and we apply this model to health care systems as a case study. Then, the model is simulated using Mobile Cloud Computing Simulator (MCCSIM). According to the experimental power and delay results, the hybrid cloud model performs up to 75% better when compared to the traditional cloud models. Lastly, we enhance our proposals by presenting and analyzing security and privacy countermeasures against possible attacks

    CONVENIENCE STORE PRACTICES AND PROGRESS WITH EFFICIENT CONSUMER RESPONSE: THE MINNESOTA CASE

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    The adoption of Efficient Consumer Response (ECR) practices by Minnesota convenience store (C- store) is explained in this study. Data were collected through a mail survey distributed to more than 250 Minnesota C-stores ranging in size from single, independently owned stores to over 100 store chains. The survey instrument was developed to collect data on the following components important to C-store operations and the implementation of ECR: information systems, ordering, receiving, inventory management, and pricing practices. Findings are presented from three distinct perspectives: 1. Location: Rural C-stores, which often meet customer needs that were once met by small supermarkets, carried a wider range of products and offered more services than C-stores in urban and suburban locations. However, rural stores had the lowest adoption rate for practices related to the ECR initiative. Urban chains coordinated business practices with suppliers to a greater degree than suburban and rural chains. 2. Chain size: Larger chains were more likely to have implemented the more costly technological practices than were small chains. This was expected since large chains can spread the fixed costs of ECR adoption over a larger number of stores. Larger chains also cooperated and communicated more with their suppliers than small chains. Again, this was expected, since larger chains can economize on transaction costs involved in maintaining these business relationships. 3. ECR practices: ECR adoption and superior performance were positively related. Having adopted six to nine practices was positively correlated with higher inside and outside sales per square foot of selling area and higher annual inventory turns. However, it was not clear whether there was a causal relationship in either direction between ECR practices and store performance. The C-store industry is changing, as new information technologies, new business practices, and new retail strategies are developed. The results from this survey can serve as a baseline for future research monitoring the adoption of these innovations and assessing their impact on productivity and profitability. Minnesota C-Stores appear to be smaller but more productive than the national average. Overall, it appears ECR is just beginning to impact the Minnesota C-store industry. Nonetheless, regression analyses confirmed ECR practices are positively related to store sales performance and those stores adopting the most practices had higher productivity measures.Industrial Organization, Marketing,

    Performance prediction tools for low impact building design

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    IT systems are emerging that may be used to support decisions relating to the design of a built enviroment that has low impact in terms of energy use and environmental emissions. This paper summarises this prospect in relation to four complementary application areas: digital cities, rational planning, virtual design and Internet energy services

    Performance of Network and Service Monitoring Frameworks

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    The efficiency and the performance of anagement systems is becoming a hot research topic within the networks and services management community. This concern is due to the new challenges of large scale managed systems, where the management plane is integrated within the functional plane and where management activities have to carry accurate and up-to-date information. We defined a set of primary and secondary metrics to measure the performance of a management approach. Secondary metrics are derived from the primary ones and quantifies mainly the efficiency, the scalability and the impact of management activities. To validate our proposals, we have designed and developed a benchmarking platform dedicated to the measurement of the performance of a JMX manager-agent based management system. The second part of our work deals with the collection of measurement data sets from our JMX benchmarking platform. We mainly studied the effect of both load and the number of agents on the scalability, the impact of management activities on the user perceived performance of a managed server and the delays of JMX operations when carrying variables values. Our findings show that most of these delays follow a Weibull statistical distribution. We used this statistical model to study the behavior of a monitoring algorithm proposed in the literature, under heavy tail delays distribution. In this case, the view of the managed system on the manager side becomes noisy and out of date

    A study of publish/subscribe systems for real-time grid monitoring

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    Monitoring and controlling a large number of geographically distributed scientific instruments is a challenging task. Some operations on these instruments require real-time (or quasi real-time) response which make it even more difficult. In this paper, we describe the requirements of distributed monitoring for a possible future electrical power grid based on real-time extensions to grid computing. We examine several standards and publish/subscribe middleware candidates, some of which were specially designed and developed for grid monitoring. We analyze their architecture and functionality, and discuss the advantages and disadvantages. We report on a series of tests to measure their real-time performance and scalability

    Checkpointing as a Service in Heterogeneous Cloud Environments

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    A non-invasive, cloud-agnostic approach is demonstrated for extending existing cloud platforms to include checkpoint-restart capability. Most cloud platforms currently rely on each application to provide its own fault tolerance. A uniform mechanism within the cloud itself serves two purposes: (a) direct support for long-running jobs, which would otherwise require a custom fault-tolerant mechanism for each application; and (b) the administrative capability to manage an over-subscribed cloud by temporarily swapping out jobs when higher priority jobs arrive. An advantage of this uniform approach is that it also supports parallel and distributed computations, over both TCP and InfiniBand, thus allowing traditional HPC applications to take advantage of an existing cloud infrastructure. Additionally, an integrated health-monitoring mechanism detects when long-running jobs either fail or incur exceptionally low performance, perhaps due to resource starvation, and proactively suspends the job. The cloud-agnostic feature is demonstrated by applying the implementation to two very different cloud platforms: Snooze and OpenStack. The use of a cloud-agnostic architecture also enables, for the first time, migration of applications from one cloud platform to another.Comment: 20 pages, 11 figures, appears in CCGrid, 201
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