Conference Papers

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    Heuristic-based iot application modules placement in the fog-cloud computing environment
    (Institute of Electrical and Electronics Engineers Inc., 2018) Natesha, B.V.; Guddeti, R.M.
    Nowadays many Smart City applications make use of Internet of Things (IoT) devices for monitoring the environment. The increase in use of IoT for smart city applications causes exponential increase in the volume of data. Using centralised cloud for time sensitive IoT applications is not feasible due to more delay because of the network congestion. Hence, fog computing is used for processing the data near to the edge of the network, where processing is done by distributed network nodes. But, there is a challenge to select the fog nodes which can host and process the application modules. The placement of application module on these fog devices is known as NP-hard problem. Hence, we need better placement strategies to decide placement of application modules in fog infrastructure to minimize the application latency. In this paper, we design a First-Fit Decreasing (FFD) heuristic based approach for placing IoT application modules on Fog-Cloud and carried out the experiment using iFogsim simulator. The simulation results demonstrate that the proposed method shows significant decrease in both the application latency and energy consumption of Fog-Cloud as compared to the benchmark method. © 2018 IEEE.
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    GA-PSO: Service Allocation in Fog Computing Environment Using Hybrid Bio-Inspired Algorithm
    (Institute of Electrical and Electronics Engineers Inc., 2019) Yadav, V.; Natesha, B.V.; Guddeti, R.M.R.
    Internet of Thing (IoT) applications require an efficient platform for processing big data. Different computing techniques such as Cloud, Edge, and Fog are used for processing big data. The main challenge in the fog computing environment is to minimize both energy consumption and makespan for services. The service allocation techniques on a set of virtual machines (VMs) is the decidable factor for energy consumption and latency in fog servers. Hence, the service allocation in fog environment is referred to as NP-hard problem. In this work, we developed a hybrid algorithm using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) technique to solve this NP-hard problem. The proposed GA-PSO is used for optimal allocation of services while minimizing the total makespan, energy consumption for IoT applications in the fog computing environment. We implemented the proposed GA-PSO using customized C simulator, and the results demonstrate that the proposed GA-PSO outperforms both GA and PSO techniques when applied individually. © 2019 IEEE.
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    HTmRPL++ : A Trust-Aware RPL Routing Protocol for Fog Enabled Internet of Things
    (Institute of Electrical and Electronics Engineers Inc., 2020) Subramanian, N.; Mitra, S.; Martin, J.P.; Chandrasekaran, K.
    With the proliferation of Fog computing, computation is moved to edge devices and is not based on a purely centralized approach. In a Fog computing network, the network topology is dynamic. New nodes will join and leave. One of the major issues in Fog computing is trust. Trust is the level of assurance that an object will behave in a satisfactory manner. The Routing Protocol for Low Power and Lossy Networks (RPL) is a protocol used for routing in IoT networks. RPL provides meager protection against routing or other forms of attacks. The resource-constrained nature of Fog nodes prevents the use of heavyweight cryptographic algorithms to achieve secured communication. A lightweight mechanism is thus essential to impart security in Fog-IoT networks. Trust analysis provides a behavior-based analysis of entities in the system with the power to predict future behavior. In this paper, a lightweight Recommendation based Trust Mechanism is proposed to impart security to RPL. © 2020 IEEE.
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    Efficient Task Offloading in IoT-Fog Network
    (Association for Computing Machinery, 2023) Morey, J.V.; Addya, S.K.
    Applications using AI or augmented reality which are resource hungry and cannot be computed on the end user device are sent to the cloud for processing. But cloud may not be nearer to the edge device and hence time required to execute that application is more. This paper presents a brief introduction to offloading in IoT-Fog Network. Various aspects and problems present in this area are mentioned. We also performed an analytical analysis to calculate the values quality of service parameters(QOS) for an optimal mapping. © 2023 Owner/Author.