Showing 37–48 of 74 results
H2Hadoop: Improving Hadoop Performance using the Metadata of Related Jobs Abstract? Cloud Computing leverages Hadoop framework for processing BigData in parallel. Hadoop has certain limitation s that could be exploited to execute the job efficiently. These limitations are mostly because of data locality in the cluster, jobs and tasks scheduling, and resource allocations in Hadoop….
Hadoop MapReduce for Mobile Clouds Abstract-The new generations of mobile devices have high processing power and storage, but they lag behind in terms of software systems for big data storage and processing. Hadoop is a scalable platform that provides distributed storage and computational capabilities on clusters of commodity hardware. Building Hadoop on a mobile network…
Hadoop Multi Node Cluster Resource Analysis Abstract? In the Computer System we have basically three types of Resources; they are Software, Hardware and Data. Data is the most important resource of computer system, because whatever computing we are doing is just because of data. Data Science deals with large amount of data to infer knowledge…
HDM: A Composable Framewor k for Big Data Processing Abstract-Over the past years, frameworks such as MapReduce and Spark have been introduced to ease the task of developing bigdata programs and applications. However, the jobs in these frameworks are roughly defined and packaged as executable jars withoutany functionality being exposed or described. This means that…
Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data Abstract?Abstract The advances in information technology have witnessed great progress on healthcare technologies in various domains nowadays. However, these new technologies have also made healthcare data not only much bigger but also much more difficult to handle and process. Moreover, because the data are created…
High Performance Analytics of Bigdata with Dynamic and Optimized Hadoop Cluster Abstract? With enterprises collecting feedback down to every possible detail, data repositories are being over flooded with information. In-order to access valuable information, these data should be processed using sophisticated statistical analysis. Traditional analytical tools, existing statistical software and data management systems find it…
Improve the Prediction Accuracy of Naive Bayes Classifier with Association Rule Mining Abstract?Companies begin to analyze their data to predict their potential customers and business decisions using Na?ve Bayes Classifier, Association Rule Mining, Decision Tree and other famous algorithms. < final year projects > [numbers_sections number=”1″ title=”Including =Packages=” last=”no” ] Complete Source Code Complete Documentation…
Improving the efficiency of Map Reduce scheduling algorithm in Hadoop Abstract-It is cost-efficient for a tenant with a limited budget to establish a virtual Map Reduce cluster by renting multiple virtual private servers (VPSs) from a VPS provider. To provide an appropriate scheduling scheme for this type of computing environment, we propose in this paper…
Incentivizing Device-to-Device Load Balancing for Cellular Networks: An Online Auction Design Abstract? The device-to-device load balancing (D2D-LB) paradigm has been advocated in recent small-cell architecture design for cellular networks. The idea is to exploit inter-cell D2D communication and dynamically relay traffic of a busy cell to adjacent under-utilized cells to improve spectrum temporal efficiency, addressing…
Increasing User Perceived Quality by Selective Load Balancing of Video Traffic in Wireless Networks Abstract? Increasing User Perceived Quality by Selective Load Balancing of Video Traffic in Wireless Networks. Wireless mesh networks < Final Year Projects 2016 > are becoming increasingly popular mostly due to their deployment ?exibility. The main drawback of these networks is…
CVSS: IoT-based Big Data Storage Systems in Cloud Computing: Perspectives and Challenges Abstract? IoT related applications have emerged as an important field for both engineers and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations especially in cloud computing. This paper first provides a functional framework that identifies…
iShuffle: Improving Hadoop Performance with Shuffle-on-Write Abstract– Hadoop is a popular implementation of the MapReduce framework for running data-intensive jobs on clusters of commodity servers. Shuffle, the all-to-all input data fetching phase between the map and reduce phase can significantly affect job performance. However, the shuffle phase and reduce phase are coupled together in Hadoop…
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