On covert channels between virtual machines

P. Ranjith; Chandran Priya; Kaleeswaran Shalini

doi:10.1007/s11416-012-0168-x

On covert channels between virtual machines

Journal in Computer Virology ◽

10.1007/s11416-012-0168-x ◽

2012 ◽

Vol 8 (3) ◽

pp. 85-97 ◽

Cited By ~ 14

Author(s):

P. Ranjith ◽

Chandran Priya ◽

Kaleeswaran Shalini

Keyword(s):

Virtual Machines ◽

Covert Channels

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Load-based covert channels between Xen virtual machines

Proceedings of the 2010 ACM Symposium on Applied Computing - SAC '10 ◽

10.1145/1774088.1774125 ◽

2010 ◽

Cited By ~ 51

Author(s):

Keisuke Okamura ◽

Yoshihiro Oyama

Keyword(s):

Virtual Machines ◽

Covert Channels

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Survey on covert channels in virtual machines and cloud computing

Transactions on Emerging Telecommunications Technologies ◽

10.1002/ett.3134 ◽

2016 ◽

Vol 28 (6) ◽

pp. e3134 ◽

Cited By ~ 8

Author(s):

Johann Betz ◽

Dirk Westhoff ◽

Günter Müller

Keyword(s):

Cloud Computing ◽

Virtual Machines ◽

Covert Channels

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Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset21841125 ◽

2018 ◽

pp. 96-101

Author(s):

Shailendra Raghuvanshi ◽

Priyanka Dubey

Keyword(s):

Load Balancing ◽

Task Scheduling ◽

Waiting Time ◽

Virtual Machines ◽

Scheduling Algorithm ◽

Cloud Environment ◽

Task Scheduling Algorithm ◽

Machine Utilization ◽

Independent Tasks ◽

Optimal Machine

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

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