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B. Thirumala Rao
K L University
Computer Science & IT Electrical & Electronics Engineering

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Migration of Virtual Machine to improve the Security of Cloud Computing N. Chandrakala; B. Thirumala Rao
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (478.467 KB) | DOI: 10.11591/ijece.v8i1.pp210-219

Abstract

Cloud services help individuals and organization to use data that are managed by third parties or another person at remote locations. With the increase in the development of cloud computing environment, the security has become the major concern that has been raised more consistently in order to move data and applications to the cloud as individuals do not trust the third party cloud computing providers with their private and most sensitive data and information. This paper presents, the migration of virtual machine to improve the security in cloud computing. Virtual machine (VM) is an emulation of a particular computer system. In cloud computing, virtual machine migration is a useful tool for migrating operating system instances across multiple physical machines. It is used to load balancing, fault management, low-level system maintenance and reduce energy consumption. Virtual machine (VM) migration is a powerful management technique that gives data center operators the ability to adapt the placement of VMs in order to better satisfy performance objectives, improve resource utilization and communication locality, achieve fault tolerance, reduce energy consumption, and facilitate system maintenance activities. In the migration based security approach, proposed the placement of VMs can make enormous difference in terms of security levels. On the bases of survivability analysis of VMs and Discrete Time Markov Chain (DTMC) analysis, we design an algorithm that generates a secure placement arrangement that the guest VMs can moves before succeeds the attack.
Novel Approach for Control Data Theft Attack in Cloud Computing K. Narasimha Sastry; B. Thirumala Rao; T Gunasekhar
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 6: December 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (500.057 KB) | DOI: 10.11591/ijece.v5i6.pp1545-1552

Abstract

Information security is a major problem faced by cloud computing around the world. Because of their adverse effects on organizational information systems, viruses, hackers, and attackers insiders can jeopardize organizations capabilities to pursue their undertaken effectively. Although technology based solutions help to mitigate some of the many problems of information security, even the preeminent technology can’t work successfully unless effective human computer communication occurs.IT experts, users and administrators all play crucial role to determine the behavior that occurs as people interact with information technology will support the maintenance of effective security or threaten it. In the present paper we try to apply behavioral science concepts and techniques to understanding problems of information security in organizations.
ERMO2 algorithm: an energy efficient mobility management in mobile cloud computing system for 5G heterogeneous networks L. Pallavi; A. Jagan; B. Thirumala Rao
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (495.783 KB) | DOI: 10.11591/ijece.v9i3.pp1957-1967

Abstract

Recently, mobile devices are becoming the primary platforms for every user who always roam around and access the cloud computing applications. Mobile cloud computing (MCC) combines the both mobile and cloud computing, which provides optimal services to the mobile users. In next-generation mobile environments, mainly due to the huge number of mobile users in conjunction with the small cell size and their portable information‟s, the influence of mobility on the network performance is strengthened. In this paper, we propose an energy efficient mobility management in mobile cloud computing (E2M2MC2) system for 5G heterogeneous networks. The proposed E2M2MC2 system use elective repeat multi-objective optimization (ERMO2) algorithm to determine the best clouds based on the selection metrics are delay, jitter, bit error rate (BER), packet loss, communication cost, response time, and network load. ERMO2 algorithm provides energy efficient management of user mobility as well as network resources. The simulation results shows that the proposed E2M2MC2 system helps in minimizing delay, packet loss rate and energy consumption in a heterogeneous network.
Co-Authors A. Jagan K. Narasimha Sastry L. Pallavi N. Chandrakala T Gunasekhar