Cloud has become one of the most demanding services for data storage. On another hand, the security of data is one of the challenging tasks for Cloud Service Provider (CSP). Cryptography is one of the ways for securing the storage data. Cryptography is not a new approach instead of the efficient utilization of cryptographical algorithms is greatly needed. In this work, we proposed a Secure Hidden Layer (SHL) and Application Programming Interface (API) for data encryption. The SHL is consisting of two major modules (i) Key Management Server (KMS) and (ii) Share Holder Server (SHS) which is used for storing and sharing of cryptographic key. For this purpose, we proposed a server-side encryption algorithm, which is based on the asymmetric algorithm (RSA and CRT) for providing end-to-end security of multimedia data. The experimental results of text and video are evidence that the size of file is not much affected after the encryption and effectively stored at Cloud Storage Server (CSS). The parameters like ciphertext size, encryption time and throughput are considered for performance evaluation of the proposed encryption technique.
Multiprocessor scheduling is one of the thrust areas in the field of computational science. There are various traditional scheduling techniques exist for the allocation and processing of jobs. But the performance of these techniques reduce in terms of makespan and waiting time when a large number of jobs are allocated to multiprocessors. In this paper, a new stochastic evolutionary technique is proposed based on the Genetic Algorithm and Pareto optimality. The new technique is implemented in a high-performance computing (HPC) environment using a Message passing interface (MPI) to resolve the permutation flow shop scheduling problem. Pareto optimality technique is used for sample distribution and the basis of the decision to select the lower bound of the makespan, instead of selecting the makespan directly for the best solution. The performance and quality evaluation of proposed techniques (GA_PO_MPI, GA) are compared with traditional techniques (FCFS, FCFS_MPI, TSAB, TSGP, TSGW) on the basis of Relative Percentage Deviation (RPD), Computational Time (CT) and Average Waiting Time and found satisfactory. INDEX TERMS Average relative percentage deviation (RPD), computational time (CT), flowshop, GA_PO_MPI, HPC, MPI, pareto optimal, scheduling.
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