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Power and Time aware VM Migration for Multi-tier Applications over Geo-distributed Clouds

Sourav Kanti Addya, Anurag Satpathy, Bishakh Chandra Ghosh and Sandip Chakraborty, Soumya K. Ghosh
2019 IEEE International Conference on Cloud Computing (IEEE CLOUD 2019) - Short Paper, Milan, Italy, July 08-13 2019 (Acceptance Rate: 20.8%)
Publication year: 2019-07-08

Towards a Democratic Federation for Infrastructure Service Provisioning

Bishakh Chandra Ghosh, Sourav Kanti Addya, Anurag Satpathy, Soumya K. Ghosh and Sandip Chakraborty
2019 IEEE International Conference on Services Computing (IEEE SCC 2019) - Short Paper, Milan, Italy, July 08-13 2019 (Acceptance Rate: 17%)
Publication year: 2019-07-08

A Stable Cloud-Alliance to Provide Uninterruptable Service

Sourav Kanti Addya, Ashok Kumar Turuk, Bibhudatta Sahoo and Anurag Satpathy,
File No. 201931006455
Publication year: 2019-02-19


To overcome certain limitations of the federated cloud architecture an alliance is proposed. A cloud-alliance, which is a more relaxed structure as the service providers can lend their resources to the alliance according to their convenience and availability. There are no strict rules that mandate for their contribution towards the alliance.

To view go to page 69 in patent link

Optimal VM Coalition Selection for Multi-Tier Applications Over Multi-Cloud Broker Environment

Sourav Kanti Addya, Anurag Satpathy, Sandip Chakraborty and Soumya K Ghosh
11th International Conference on Communication Systems & Networks (IEEE/ACM COMSNETS 2019)
Publication year: 2019-01-11

A hybrid queuing model for Virtual Machine placement in cloud data center

Sourav Kanti Addya, Ashok Kumar Turuk, Bibhudatta Sahoo and Mahasweta Sarkar
IEEE International Conference on Advanced Networks and Telecommunications Systems (IEEE ANTS 2015)
Publication year: 2015-12-18

A Strategy for Live Migration of Virtual Machines in a Cloud Federation

Sourav Kanti Addya, Ashok Kumar Turuk, Anurag Satpathy, Bibhudatta Sahoo, Mahasweta Sarkar
IEEE Systems Journal
Publication year: 2018-10-09


Migration of virtual machines (VMs) from one data center to another is essential to deal with scenarios such as load balancing, maintenance, power management, VM failures, etc. Application of VM migration is not only limited to a single cloud service provider, but also to inter-cloud architectures such as cloud federation. Migration in a federation is a complex operation as it encompasses many autonomous service providers with different standards, rules, and protocols. Migration can be carried out in two ways, first, live and, second, non-live. In case of live migration, a VM continues to execute at the source in contrast to non-live where its execution is suspended. In this paper, a framework for secure live migration of VMs in a cloud federation is proposed. Costs associated with it is analyzed for serial, parallel, and improved serial strategies. The proposed framework is simulated using a CloudSim simulator. Metrics considered for evaluation are communication overhead, migration time, and downtime. Further, power consumption for all strategies is calculated and compared. It is observed that downtime is least for parallel, whereas migration time is least for improved serial. The power consumption is highest for parallel and least for improved serial.

Crow search based virtual machine placement strategy in cloud data centers with live migration

Anurag Satpathy, Sourav Kanti Addya, Ashok Kumar Turuk, Banshidhar Majhi, Gadadhar Sahoo
Computers & Electrical Engineering, Elsevier
Publication year: 2018-07-01


Cloud computing has emerged as the most revolutionary technology in the field of computing. The cloud service providers (CSPs) have high computational facilities called data centers (DCs) at their disposal. CSPs provide services to the users through virtual machines (VMs). VM placement is the mapping of VMs onto physical machine called hosts. In this paper, we propose a two-tier virtual machine placement algorithm. Firstly, we propose a queueing structure to manage and schedule a large set of VMs. Secondly, a multi-objective VM placement algorithm called crow search based VM placement (CSAVMP) is proposed to reduce the resources wastage and power consumption at the data centers. VM migration is an indispensable part of any cloud platform for activities like maintenance, load balancingfault tolerance etc. Three different migration strategies namely serial, parallel, improved serial have been tested and a comparative result has been produced.

A Game Theoretic Approach to Estimate Fair Cost of VM Placement in Cloud Data Center

Sourav Kanti Addya, Ashok Kumar Turuk, Bibhudatta Sahoo, Anurag Satpathy and Mahasweta Sarkar
IEEE Systems Journal
DOI: 10.1109/JSYST.2017.2776117
Publication year: 2017-12-12


Pricing of virtual machines (VMs) with different dimensions is a challenging task. VM pricing involves both capital and operational expenditures. Capital expenditure is fixed in nature, while operational expenditure is variable. A fraction of capital expenditure is included for VM pricing. An individual pays the cloud service provider (CSP) for his requested VM. If the users cooperate among themselves they may end up paying less to CSP for their requested VMs vis-a-vis they would have paid had they requested individually. In this paper, an n -person cooperative game is adopted to determine the price that users would pay for their requested VMs under a cooperative environment. Shapley value is used to estimate the fraction of capital expenditure that would be included in the VM price. An integer linear programming is proposed for energy-efficient placement. For evaluation, VM configurations and pricing of popular CSPs—Microsoft Azure and Amazon EC2—are considered. Results show that users would pay less for their requested VMs if they cooperate. The energy consumed by the proposed VM placement technique is compared with first fit decreasing (FFD) and enhanced first fit decreasing (EFFD). It is observed that the proposed technique consumes lesser energy compared to FFD and EFFD.


Simulated annealing based VM placement strategy to maximize the profit for Cloud Service Providers

Sourav Kanti Addya, Ashok Kumar Turuk, Bibhudatta Sahoo, Mahasweta Sarkar, Sanjay Kumar Biswash
Engineering Science and Technology, Elsevier
Publication year: 2017-09-30


Virtual machine (VM) placement strategies reported in the literature focuses mainly on minimization of power consumption and maximization of placed VMs. The revenue earned by a cloud service provider (CSP) depends on the number of VMs placed. Increasing the number of VMs placed by a CSP not only increases the power consumption but also decreases the profit margin of the CSP. In this paper, we propose a technique called maximum VM placement with minimum power consumption (MVMP) to maximize the profit earned by a CSP. The proposed technique attempts to maximize the revenue and minimize the power budget. It is formulated as a bi-objective optimization problem, and is solved using simulated annealing (SA) technique. To reach a sub-optimal solution more randomness is applied to SA. Our MVMP algorithm is compared to five state of the art algorithms in the realm of strategic VM placement, namely Marotta and Avallone (MA) approach, Hybridgenetic algorithm (HGA), Modified Best-Fit decreasing (MBFD), First-Fit decreasing (FFD) and Random deployment. We observe that MVMP performs better than Marotta and Avallone (MA) approach, HGA, MBFD, FFD and Random placement in terms of number of servers used, energy consumption, profit and execution time. Scalabil

A Resource Aware VM Placement Strategy in Cloud Data Centers Based on Crow Search Algorithm

Anurag Satpathy, Sourav Kanti Addya, Ashok Kumar Turuk, Bansidhar Majhi, Gadadhar Sahoo
2017 4th International Conference On Advanced Computing And Communication Systems (ICACCS)
Publication year: 2017-01-06

Resource Management and Efficiency in Cloud Computing Environments

Ashok Kumar Turuk, Bibhudatta Sahoo, Sourav Kanti Addya
ISBN13: 9781522517214
Publication year: 2016-11-30


Today’s advancements in technology have brought about a new era of speed and simplicity for consumers and businesses. Due to these new benefits, the possibilities of universal connectivity, storage, and computation are made tangible, thus leading the way to new Internet-of Things solutions.
Resource Management and Efficiency in Cloud Computing Environments is an authoritative reference source for the latest scholarly research on the emerging trends of cloud computing and reveals the benefits cloud paths provide to consumers. Featuring coverage across a range of relevant perspectives and topics, such as big data, cloud security, and utility computing, this publication is an essential source for researchers, students and professionals seeking current research on the organization and productivity of cloud computing environments.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Big Data
  • Cloud Application Services (SaaS)
  • Cloud Security
  • Hybrid Cloud
  • Internet of Things (IoT)
  • Private Cloud
  • Public Cloud
  • Service Oriented Architecture (SOA)
  • Utility Computing
  • Virtualization Technology

Research Interest

Cloud Computing

I am mainly working on system development related issues on the single and multi-cloud environment. In addition to these, I am also looking into the problems on virtual machine migration for both environments.

Research Collaboration

Dr. Mahasweta Sarkar, ECE, SDSU, CA, USA.

Dr. Ashok Kumar Turuk, CSE, NIT Rourkela, India.

Dr. Sandip Chakraborty, CSE, IIT Kharagpur, India.

Dr. Soumya K Ghosh, CSE, IIT Kharagpur, India.

Dr. Bibhudatta Sahoo, CSE, NIT Rourkela, India.



“When words become unclear, I shall focus with photographs. When images become inadequate, I shall be content with silence.”
— Ansel Adams

At my office

You can find me at my office located at IIT Kharagpur.
I am at my office every day from 10:00am until 18:00 pm, but you may consider a call to fix an appointment.

Contact Info

  •   +919437141181
      Department of Computer Science and Engineering, Takshashila Building, Indian Institute of Technology, Kharagpur 721302, India