Securing and Self recovery of Virtual Machines in cloud with an Autonomic Approach using Snapshots

Joseph, Linda; Mukesh, Rajeswari

doi:10.1007/s11036-019-01261-3

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…The paper [12] introduces an autonomic prediction model for auto recovery of attacked VM instances in a cloud. The proposed approach to auto recovery and self-healing in the VM's by an intelligent hypervisor offers a continuous progression of any process in the schedule without any job disruption.…”

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confidence: 99%

Editorial: Mobile Networks in the Era of Big Data

Varadarajan

Neelanarayanan

Doyle³

et al. 2019

Mobile Netw Appl

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There is an exceptional rupture of research activities in big data, which illustrate enormous potential in making decisions, optimizing operations, mitigating security threats and also in a variety of fields, such as retail, advertisement, manufacturing, healthcare and insurance. Data from Mobile devices and networks like smart phones, cellular networks, Sensor networks, Vehicular Networks is an important source of big data. Thus, Mobile networks play a critical role in big data generation, delivery, and processing. Big Data will have profound impacts on the design and operation of Mobile networks. We received 46 paper submissions, from which 7 submissions have been transferred and 8 papers withdrawn. After a rigorous single blinded peer review process only 14 papers have been accepted and 17 papers have been rejected, i.e., our acceptance rate is about 45% not considering the transferred and withdrawn submissions. Hence, this special issue features 14 high quality research papers that can demonstrate proofs-of-concept, services, solutions for research challenges, case studies, analytics, real world examples and successful deliveries of Big Data and Mobile Networks.

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confidence: 99%