D. I. George Amalarethinam ¹, J. Sai Geetha ², K. Mani ²

Affiliations
1 MCA, Jamal Mohamed College, Trichy - 620020, Tamilnadu, IN
2 Computer Science, Nehru Memorial College, Trichy, Tamilnadu, IN

Abstract

In the world of internet, Cryptography places a vital role as an effective measure to maintain information security. Whenever the security of public key cryptography algorithm increases, the execution speed decreases since both are inversely proportionate. It is mandatory to improve the security without affecting the speed. The main objective of this paper focuses on speed enhancement. Generally the encryption and decryption process is done on each characters of the plain text separately. It is a time consuming process. In this paper, the plain text is being decomposed into blocks to achieve better performance. The characters are to be grouped (Block Cipher mode) into blocks. For grouping of blocks, the plain text is replaced by the binary form of ASCII code. The binary plain text is divided into blocks with fixed size. If the size of block increases, then the execution speed is also increased. The crucial factor is to fix the block size. In some instance, the process of obtaining the plain text (decryption) is affected due to inappropriate block size. To overcome this issue, precise block size is fixed by using the proposed methodology namely Message Encoding Algorithm (MsgEncA). This algorithm is implemented in Java. As a result of proposed algorithm, the appropriate block size is fixed as double of the key size and less than modulus value. The execution speed is also analyzed with different key sizes and file sizes using RSA algorithm. The speed is compared with the existing algorithm namely Short Range of Natural Numbers (SRNN). Even when applied with different key size, the MsgEncA produces better performance with same level of security. An experimental analysis and comparison proves that the execution speed of MsgEncA is better than the existing method. In the aspect of speed, the proposed algorithm can be applied in any public key algorithms.

Keywords

Block Cipher, Decryption, Encryption, Message Encoding, Public Key Cryptography

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D. I. George Amalarethinam ¹, T. Lucia Agnes Beena ²

Affiliations
1 Department of Computer Science, Jamal Mohamed College, Trichy – 620020, Tamil Nadu, IN
2 Deptartment of Information Technology, St. Joseph’s College, Trichy - 620002, Tamil Nadu, IN

Abstract

Cloud computing is aimed at delivering computing services as a utility. One of the Cloud computing services is Workflow as a Service (WFaaS). Workflow scheduling is a vital area in WFaaS. The objective of this paper is to propose a scheduling algorithm that meets the Quality of Service constraints such as Makespan and Cost. The proposed algorithm Level Based Task Prioritization (LBTP) follows the list scheduling strategy. The LBTP algorithm alters task prioritization phase and the resource selection phase, where three different algorithms like Earliest Finish Time, Parent Resource Allocation and Round Robin are applied. The LBTP algorithm is tested for small workflows. The performance analysis is done by varying the Communication to Computation Ratio and number of tasks. The scheduling metrics, Makespan and Cost of the proposed algorithm are compared with the Customer Facilitated Cost based Scheduling (CFCSC) algorithm. The experimental results show that Earliest Finish Time resource selection procedure outperforms CFCSC algorithm with respect to Makespan for communication intensive graphs. For computation intensive graphs, the parent resource allocation procedure produces better Makespan. With respect to Cost parameter, irrespective of total number of tasks in the Direct Acyclic Graph, all the resource selection procedures have incurred minimum cost. The proposed algorithm helps the Cloud Provider to select the scheduling algorithm in accordance with the Quality of Service parameters. Further, the LBTP algorithm can be tested with Regular Scientific workflows like Montage and Cybershake.

Keywords

Cloud Computing, Cost, Makespan, Resource Allocation, Tasks Scheduling, Workflow Scheduling

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V. Jude Nirmal ¹, D. I. George Amalarethinam ²

Affiliations
1 Department of IT, St. Joseph’s College (Autonomous), College Road, Tiruchirappalli - 620002, Tamil Nadu, IN
2 Jamal Mohamed College, 7, Race Course Road, Khajanagar, Tiruchirappalli – 620020, Tamil Nadu, IN

Abstract

Objectives: The major objective of this approach is to provide a sentiment analysis architecture that can operate on streaming big data to provide effective results at tolerable time limits. Method/Analysis: An effective mechanism for analyzing the social networking messages to identify the sentiment levels has been proposed. This is a generic model that can be used for product or organization specific analysis. Further, this method also considers emoticons, which form the integral part of any expressed emotion. The entire process is carried out in Hadoop Architecture using the MapReduce paradigm. Findings: Experiments have been conducted on a Hadoop cluster. Inputs were passed from a client node connected to the cluster. Map Reduce programs were executed in six phases, each phase performing a single task in map and reduce phases. The ROC plot exhibits excellect accuracies with most of the points being clustered in the top left region, some even approaching 100% effectiveness. Even the PR plots exihibits similar efficiency scenario with high positive retrieval rates. Incorporating the emoticons plays a major role in increasing the efficiency of this approach. Novelty/Improvement: This approach uses Hadoop based implementations, involving Map and Reduce operations. Using this approach provides data scalability and improves the efficiency of the results in acceptable time limits.

Keywords

Emoticons, Hadoop, Map Reduce, Polarity Identification, Sentiment Analysis, Social Networking Data Processing.

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