Informatics Publishing Limited

A. Daison Raj ¹, M. BalaAnand ¹, C. Leena ¹

Affiliations
1 Department of CSE, V.R.S. College of Engineering and Technology, Arasur, Villupuram, IN

Abstract

IP lookup affects the speed of an incoming packet and the time required to determine which output port the packet should be sent to; hence, it plays an important role in the design of cluster-tables. In this paper, we propose a new data structure, called a BVLI – Binary Value Level based Index Data Structure for use in designing dynamic cluster-tables for reduce the time minimization process for searching the availability of next cluster head in the cluster table and retrieve the particular cluster network information quickly during the communication among the systems in the wireless networks. One key feature of our data structure is that each node can store only one Level in the cluster head table, which reduces the number of memory accesses. When performing lookup, the structure can search more prefixes in one node and may find the longest matching prefix in an internal node rather than on a leaf. Moreover, when updating the cluster head-table, it does not need to reconstruct the table. As a by-product, the proposed data structure minimizes the time required for dynamic cluster head table operations, including lookup, insertion, deletion, and also reduces the number of memory accesses. We report the results of experiments conducted to compare the proposed data structure with other structures using MATLAB.

Keywords

BVLI, Cluster, Lookup, Unique ID.

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M. Sabareesan ¹, A. Daison Raj ², C. Leena ¹, M. BalaAnand ²

Affiliations
1 Department of CSE, V.R.S. College of Engineering and Technology, Arasur, Villupuram, IN
2 Department of CSE, V.R.S. College of Engineering and Technology, Arasur, Villupuram, IN

Abstract

We propose system attributes regarding urban high resolution color remote sensing images, when I put forward the object oriented shadow detection in addition to removal method inside the method, shadow has are generally recognized into bank account through aesthetic segmentation, and then, according for the statistical provides of the images, suspected shadows are generally extracted. Furthermore, a series of dark objects that will can be mistaken regarding shadows are usually ruled out according to object properties as well s spatial relationship between objects. For shadow removal, inner–outer summarize report collection. (IOSRC) matching is used. First, your IOSRCs are consumed in respect to the boundary lines associated with shadows. Shadow removal is actually then performed according towards homogeneous sections attained in the course of IOSRC similarity matching. Experiments show which the new technique can accurately detect shadows via urban high-resolution remote sensing images and also can correctly restore shadows having a rate of over 85%.

Keywords

HSV, HCV, YIQ, Brightness, Saturation.

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R. Gayathri ¹, M. Balaanand ²

Affiliations
1 Computer Science and Engineering, University of Trichy, IN
2 V.R.S. College of Engineering and Technology, Arasur, Villupuram, IN

Abstract

Big Data is a term connected to information sets whose size is past the capacity of customary programming advancements to catch, store, oversee and prepare inside a passable slipped by time. The well known supposition around Huge Data examination is that it requires web scale adaptability: over many figure hubs with connected capacity. In this paper, we wrangle on the need of an enormously adaptable disseminated registering stage for Enormous Data examination in customary organizations. For associations which needn't bother with a flat, web request adaptability in their investigation stage, Big Data examination can be based on top of a customary POSIX Group File Systems utilizing a mutual stockpiling model. In this study, we looked at a broadly utilized bunched record framework: (SF-CFS) with Hadoop Distributed File System (HDFS) utilizing mainstream Guide diminish. In our investigations VxCFS couldn't just match the execution of HDFS, yet, additionally beat much of the time. Along these lines, endeavors can satisfy their Big Data examination need with a customary and existing shared stockpiling model without relocating to an alternate stockpiling model in their information focuses. This likewise incorporates different advantages like soundness and vigor, a rich arrangement of elements and similarity with customary examination application.

Keywords

BigData, Hadoop, Clustered File Systems, Investigation, Cloud.

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M. BalaAnand , S. Murugan , S. Sangeeta

Abstract

A man’s dream is process Big Data in cloud. But, nowadays this is achieved by using a new technology called cloud computing. Security is the major concern in Big Data. In cloud storage for Big Data are easily modified by the attackers. To overcome this data modification problem in cloud storage for Big Data, in this paper a novel Proxy Re-signature technique called Homomorphic Authenticable Proxy Iterative-signature is used for enhancing data security by using public key verifier. Public key Verifier will verify the integrity of shared data without accessing the entire big data from the cloud storage and also digital signature is attached to each block of message. With this digital signature, individual users can access the big data in the cloud storage. Whenever the attacker modifies the block of data in the cloud then signature is provided to user for modifying the particular block alone, these avoids the modification of data

Keywords

Big Data, Digital Signature, Homomorphic Authenticable Proxy Re-Signature, Group Manager, Public Key Verifier.

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