Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Privacy and trust in cloud database using threshold-based secret sharing(2013) Dutta, R.; Annappa, B.In today's cloud computing scenario, privacy of data and trust on the service provider have become a major issue and concern. Achieving trust and preserving the privacy of data stored in third-party cloud databases has emerged as a key research area. To achieve this, several different techniques have been proposed based on cryptography, auditing by a third party, etc. Secret sharing schemes have also been considered to address these issues of trust and privacy in databases by various researchers. In this paper, we propose a technique of using a well-known threshold-based visual secret sharing scheme to address the issue of privacy and trust in cloud databases and database-as-a-service offerings. We consider data records with at least one prime attribute and propose an indexing technique for the secret shares of records in a large database based on some properties of the secret sharing technique. Our technique is aimed at minimizing storage overhead of secret shares as well as high speed upload and retrieval of data. We discuss the results obtained from our implementation. Our implementation using Hadoop Distributed File System (HDFS) with Matlab shows that this technique minimizes storage overhead due to secret shares and ensures high speed data upload and retrieval. © 2013 IEEE.Item Load balancing strategy for optimal peak hour performance in cloud datacenters(Institute of Electrical and Electronics Engineers Inc., 2015) Kulkarni, A.K.; Annappa, B.Cloud computing is a growing computing model that is influencing every other entity in the global business industry. Efficient load balancing techniques plays a major role in cloud computing by allocating requests to computing resources efficiently to prevent under/over-allocation of Virtual Machines (VMs) and improve the response time to clients. It is observed that during peak hours when request frequency is high, active VM load balancer (packaged in cloudAnalyst) over-allocates initial VMs and under-allocates later ones creating load imbalance. In this paper we propose a novel VM load balancing algorithm that ensures uniform allocation of requests to virtual machines even during peak hours when frequency of requests received in data center is very high to ensure faster response times to users. The simulations results suggest that our algorithm allocates requests to VM uniformly even during peak traffic situations. © 2015 IEEE.