Conference Papers
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Item A novel meta-heuristic differential evolution algorithm for optimal target coverage in wireless sensor networks(Springer Verlag service@springer.de, 2019) Naik, C.; Shetty D, D.A wireless sensor network (WSN) faces various issues one of which includes coverage of the given set of targets under limited energy. There is a need to monitor different targets in the sensor field for effective information transmission to the base station from each sensor node which covers the target. The problem of maximizing the network lifetime while satisfying the coverage and energy parameters or connectivity constraints is known as the Target Coverage Problem in WSN. As the sensor nodes are battery driven and have limited energy, the primary challenge is to maximize the coverage in order to prolong network lifetime. The problem of assigning a subset of sensors, such that all targets are monitored is proved to be NP-complete. The Objective of this paper is to assign an optimal number of sensors to targets to extend the lifetime of the network. In the last few decades, many meta-heuristic algorithms have been proposed to solve clustering problems in WSN. In this paper, we have introduced a novel meta-heuristic based differential evolution algorithm to solve target coverage in WSN. The simulation result shows that the proposed meta-heuristic method outperforms the random assignment technique. © 2019, Springer Nature Switzerland AG.Item Location Privacy Using Data Obfuscation in Fog Computing(Institute of Electrical and Electronics Engineers Inc., 2019) Naik, C.; Sri Siddhartha, M.; Martin, J.P.; Chandrasekaran, K.In the past few decades, smartphones and Global Positioning System(GPS) devices have led to the popularity of Location Based Services. It is crucial for large MNCs to get a lot of data from people and provide their services accordingly. However, on the other side, the concern of privacy has also increased among the users, and they would like to hide their whereabouts. The rise of data consumption and the hunger for faster network speed has also led to the emergence of new concepts such as the Fog Computing. Fog computing paradigm extends the storage, networking, and computing facilities of the cloud computing towards the edge of the networks while removing the load on the server centers and decreasing the latency at the edge device. The fog computing will help in unlimited growth of location services and this adoption of fog computing calls for the need for more secure and robust algorithms for location privacy. One of the ways we can alter the information regarding the location of the user is Location Obfuscation. This can be done reversibly or irreversibly. In this paper, we address the problem of location privacy and present a solution based on the type of data that has to be preserved (in our case, it is distance). A mobile application has been designed and developed to test and validate the feasibility of the proposed obfuscation techniques for the Fog computing environments. © 2019 IEEE.Item ECABBO: Energy-efficient clustering algorithm based on Biogeography optimization for wireless sensor networks(Institute of Electrical and Electronics Engineers Inc., 2019) Nomosudro, P.; Mehra, J.; Naik, C.; Shetty D, D.Cluster-based communication design is an assuring technique in wireless sensor networks to reduce energy consumption and enhance scalability. The requirement of data collection from neighbor nodes, data gathering, and data forwarding to the sink overloads each cluster head. Therefore, it is a highly significant issue to elect a set of optimal cluster heads from the normal sensor nodes. In this paper, the Biogeography Based Optimization for energy-efficient clustering is introduced for cluster head selection. The simulation outcomes show that the algorithm improves the network endurance as compared to other protocols such as Genetic algorithm, Low energy adaptive clustering hierarchy, and Clustered Routing for Selfish Sensors. © 2019 IEEE.Item Intelligent Interference Minimization Algorithm for Optimal Placement of Sensors using BBO(Springer, 2020) Naik, C.; Shetty D, P.In wireless sensor networks, the performance metric such as energy conservation becomes paramount. One of the fundamental problems of energy drains is due to the interference of sensors during sensing, transmission, and receiving data. The issue of placing sensors on a region of interest to minimize the sensing and communication interference with a connected network is NP-complete. In order to overcome the existing problem, we have proposed a new work for interference minimization technique for optimal placement of sensors by employing biogeography-based optimization scheme. An efficient habitats representation, objective function derivation, migration, and mutation operators are adopted in the scheme. The simulations are performed to obtain the optimal position for sensor placement. Finally, the energy-saving of the network is compared with and without interference aware sensor nodes placement. © 2020, Springer Nature Singapore Pte Ltd.