Theses and Dissertations

Permanent URI for this collectionhttp://ir.daiict.ac.in/handle/123456789/1

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    Prepare a roadmap for RKK Prerna and Rallis advisory centre development
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2011) Uthup, Ryan; Chaudhary, Sanjay; Reddy, P.V.
    Rallis has introduced a concept called “Rallis Kisan Kutumba (RKK)”, wherein farmers are enrolled with Rallis and they are supported to achieve better yields from their farmland. RKK also leverages the advancement in information and other technologies. Many activities have been initiated or in the process to enhance farm level yield through proper education and training to farmers. Some of the activities under the RKK concept are “Prerna visits” and “Rallis Advisory Centre”. RKK Prerna Farmers will only believe, if they see the results with their own eyes or hear about it from some friends or some progressive farmer he knows. So Rallis have come up with a concept in which there will be a combination of both “Seeing is believing” and the “Word of mouth”. We call this “RKK PRERNA – A FARMER EXPERIENCE SHARING PROGRAMME.” RKK-Prerna is basically taking a few important farmers of one specific crop segment from an area where potential exists for a particular product to another area of same crop segment where the product benefits are already experienced. This experience sharing can be organized between two groups of farmers within Region/ Zone or across Zones. Rallis Advisory centre Lack of information and knowledge is a major barrier in improving the productivity of crops. Rallis advisory Centre is a medium through which this information barriers could be reduced and the farming community could be served through proper knowledge dissemination and services.
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    Service level agreement parameter matching in cloud computing
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2011) Chauhan, Tejas; Chaudhary, Sanjay; Bise, Minal
    Cloud is a large pool of easily usable and accessible virtualized resources (such as hardware, development platforms and/or software services). It provides an on-demand, pay-asyo-ugo computing resources and had become an alternative to traditional IT infrastructure. As more and more consumers delegate their task to cloud providers, Service Level Agreement (SLA) between consumer and provider becomes an important aspect. Due to the dynamic nature of cloud the matching of service level agreement need to be dynamic and continuous monitoring of Quality of Service (QoS) is necessary to enforce SLAs. This complex nature of cloud warrants a sophisticated means of managing SLAs. SLA contains many parameters like cloud’s types of services, resources (physical memory, main memory, processor speed, ethernet speed etc.) and properties (availability, response time, server reboot time etc.). At present, actual Cloud SLAs are typically plain-text documents, and sometimes an informative document published online. Consumer needs to manually match application requirements with each and every cloud provider to identify compatible cloud provider. This work addresses the issue of matching SLA parameters to find best suitable cloud provider. Proposed algorithm identifies the compatible cloud provider by matching parameters of application requirements and cloud SLAs. It gives suggestion to a consumer in terms of number of matched parameters.