Faculty Publications
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Item Architecture and Deployment Models-SDN Protocols, APIs, and Layers, Applications and Implementations(Springer Science and Business Media Deutschland GmbH, 2022) Rudra, B.; S, T.The current Internet infrastructure is not anticipating such a growth of IoT and increasing the network complexity. New network architecture for the management of IoT data flow and also catering to the Quality of Service of different IoT services is required. The existing incompatible solutions are limited to the early adoption of IoT. The standardization bodies, industries, researches were involved in developing standards to support end-to-end connection, interoperation between devices from different vendors and also provide cost-efficient solutions. The Working Groups (WG) at the IETF introduced new solutions that have allowed the connection of low-power wireless networks to the Internet. In spite of the vast exploration of solutions for deploying IoT, the management of IoT networks requires complex routing topologies with a simplified user operation. This gives rise to the need for centralized network control which is facilitated by Software Defined Networking (SDN). SDN was a standard technology for Wireless Sensor Networks (WSNs) already available which is the early version of IoT as the world knows it today. SDN provides a framework to ease the complexity involved in the management of sophisticated networks. We discuss various protocols present in the architecture along with the research challenges for the future. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Item Multi-Objective Energy Efficient Virtual Machines Allocation at the Cloud Data Center(Institute of Electrical and Electronics Engineers, 2019) Sharma, N.K.; Guddeti, R.M.R.Due to the growing demand of cloud services, allocation of energy efficient resources (CPU, memory, storage, etc.) and resources utilization are the major challenging issues of a large cloud data center. In this paper, we propose an Euclidean distance based multi-objective resources allocation in the form of virtual machines (VMs) and designed the VM migration policy at the data center. Further the allocation of VMs to Physical Machines (PMs) is carried out by our proposed hybrid approach of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) referred to as HGAPSO. The proposed HGAPSO based resources allocation and VMs migration not only saves the energy consumption and minimizes the wastage of resources but also avoids SLA violation at the cloud data center. To check the performance of the proposed HGAPSO algorithm and VMs migration technique in the form of energy consumption, resources utilization and SLA violation, we performed the extended amount of experiment in both heterogeneous and homogeneous data center environments. To check the performance of proposed HGAPSO with VM migration, we compared our proposed work with branch-and-bound based exact algorithm. The experimental results show the superiority of HGAPSO and VMs migration technique over exact algorithm in terms of energy efficiency, optimal resources utilization, and SLA violation. © 2019 IEEE.Item Elucidating the challenges for the praxis of fog computing: An aspect-based study(John Wiley and Sons Ltd vgorayska@wiley.com Southern Gate Chichester, West Sussex PO19 8SQ, 2019) Martin, J.P.; Kandasamy, A.; Chandrasekaran, K.; Joseph, C.T.The evolutionary advancements in the field of technology have led to the instigation of cloud computing. The Internet of Things paradigm stimulated the extensive use of sensors distributed across the network edges. The cloud datacenters are assigned the responsibility for processing the collected sensor data. Recently, fog computing was conceptuated as a solution for the overwhelmed narrow bandwidth. The fog acts as a complementary layer that interplays with the cloud and edge computing layers, for processing the data streams. The fog paradigm, as any distributed paradigm, has its set of inherent challenges. The fog environment necessitates the development of management platforms that effectuates the orchestration of fog entities. Owing to the plenitude of research efforts directed toward these issues in a relatively young field, there is a need to organize the different research works. In this study, we provide a compendious review of the research approaches in the domain, with special emphasis on the approaches for orchestration and propose a multilevel taxonomy to classify the existing research. The study also highlights the application realms of fog computing and delineates the open research challenges in the domain. © 2019 John Wiley & Sons, Ltd.