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Item Construction of minimum power 3-connected subgraph with k backbone nodes in wireless sensor networks(Springer International Publishing, 2019) Shetty D, D.; Lakshmi, M.Minimizing the total power in a wireless sensor network (WSN) has great significance, since the nodes are powered by a small battery of limited capacity. By using an appropriate topology, the energy utilization of the network can be minimized which results in an increased lifetime of a WSN. In reality, WSN is modeled as an undirected graph in which each vertex represents a sensor node and an edge represents the link between the two sensor nodes. We define a distance function that maps a pair of vertices to a positive real number, i.e., Euclidean distance between the two vertices. On this initial topology, we construct a reduced topology satisfying special connectivity constraints like bi-connectivity, k-connectivity, bounded diameter, degree restricted, etc. We assign power to each node as the maximum distance of all its adjacent edges, and total power of the network is the sum of the powers of all the vertices. Fault tolerance addresses the issue of a node or link failure in a WSN. Fault-tolerant network aims at k-connectivity in the network so that there exist at least k vertex disjoint paths between any two sensor nodes of the network. Minimum power 2-connected subgraph (MP2CS) problem is to contrive a 2-connected network with minimum total power. It is proved that MP2CS problem is NP-hard. Minimum power k backbone node 2-connected subgraph (MPkB2CS) problem is a special case of MP2CS problem, which seeks a power assignment satisfying 2-connectivity with k backbone nodes. In this paper, the problem of finding a 3-connected network for a given set of nodes, which minimizes the total power with k backbone nodes, is addressed which is termed as MPkB3CS problem. We propose an algorithm for MPkB3CS problem and establish that the proposed algorithm has an approximation ratio of 4k + 1, for k ≥ 3. © Springer Nature Switzerland AG 2019.Item Novel schemes for energy-efficient IoT(Springer Verlag service@springer.de, 2019) Venkateshwarlu, K.; Shetty D, D.Internet of things (IoT) is a global infrastructure for the information society which enables advanced services by interconnecting physical and virtual things based on existing and evolving inter-operable information and communication technologies. Developing green IoT is a difficult task because IoT has more devices and has complex structure, so most of the current schemes for deploying nodes in wireless sensor networks (WSNs) cannot be applied directly in IoT. In this paper, we propose a scheme which gives an energy-efficient IoT. Here, we propose two schemes for framework structure of a network, and then we propose clustering algorithms and routing algorithms for network formation which is based on minimum spanning tree. After numerous simulations, we show that these schemes result in minimal energy consumption and enhance the network lifetime. Thus, the proposed schemes are more energy-efficient compared to a typical WSN deployment scheme; hence, these schemes are applicable to the green IoT deployment. We show that in the proposed schemes, the nodes are alive for more number of rounds as compared to the existing algorithms. © 2019, Springer Nature Singapore Pte Ltd.Item Minimizing the total range with two power levels in wireless sensor networks(Springer Verlag service@springer.de, 2019) Shetty D, D.; Lakshmi, M.Minimizing the total energy consumed by wireless sensor network (WSN) is a significant problem, since the sensor nodes are attached with a small battery of restricted capacity. In a WSN, any pair of sensor nodes must be able to communicate with each other in the network, so bidirectional connectivity of WSN is an important characteristic to be achieved. The range assignment problem in a WSN aims to assign transmission range to each sensor node of the network such that the specified connectivity constraints such as strong connectivity, k-connectivity are to be satisfied by the reduced network. Most sensors in recent days operate with discrete power levels. So, in this paper, we consider the range assignment problem with two power levels. Our aim is to assign each sensor node in the network with one of the available set of power levels such that the reduced topology is strongly connected and the total power consumption is minimized. The dual power assignment problem is well studied in the literature. We present an improved algorithm for dual power assignment problem in which the power levels are taken as input. Performance of the proposed algorithms is analyzed through extensive simulation. We establish the theoretical approximation ratio bound of the proposed algorithm for dual power assignment problem as 2. But, the simulation results indicate that the performance ratio is much less than 2. © 2019, Springer Nature Singapore Pte Ltd.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 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 Differential evolution meta-heuristic scheme for k-coverage and m-connected optimal node placement in wireless sensor networks(Machine Intelligence Research (MIR) Labs contact@mirlabs.org, 2019) Naik, C.; Shetty D, D.A wireless sensor network (WSN) faces a wide range of issues, which includes coverage of the given set of targets under specified connectivity constraint. There is a need to monitor different targets in the sensor field for effective information communication to the base station from each wireless sensor node which monitors the target by maintaining required connectivity among them. The problem of ensuring every target covered by at least k sensors and each sensor directly communicate with m sensors is termed as k-coverage and m-connectivity problem in wireless sensor networks. As the wireless sensor nodes are battery driven and have limited energy, the primary challenge is to have an optimal placement of sensor nodes in the field of deployment to minimize energy consumption. The objective of this work is to deploy the optimal number of sensor nodes with k-coverage and m-connectivity constraints in an area of interest. In the last few years, many meta-heuristic algorithms have been proposed to solve different problems like clustering and localization in WSN. In this paper, we introduce a meta-heuristic based differential evolution algorithm to solve k-coverage and m-connectivity problem in WSN. The simulation result shows that the proposed meta-heuristic method out performs the genetic algorithm. © MIR Labs.Item Approximation algorithm for receiver interference problem in dual power Wireless Sensor Networks(Springer Verlag service@springer.de, 2019) Shetty D, D.; Lakshmi, M.P.The problem of assigning power levels to the nodes of a wireless sensor network from a given a set of two power levels is called Dual power management problem and the underlying network is called Dual power network. We consider the problem of minimizing the maximum receiver interference of such a network. The interference disrupts the communication and forces the data packets to be retransmitted. The motivation is to conserve the energy by minimizing the interference and maintaining the connectivity of the dual power network. Receiver interference problem is proved to be NP-hard. In this paper, an approximation algorithm is derived for minimizing the maximum receiver interference of a dual power network by utilizing the approximation algorithm for Dual Power Management Problem. The proposed algorithm is supported by the simulation results. We term this problem as Dual Power Receiver Interference Problem and show that it is NP-complete using a polynomial time reduction from Degree Constrained Minimum Spanning Tree problem. We also prove the NP-completeness of Dual Power Management Problem by a polynomial reduction from Vertex Cover Problem. © 2019, Korean Society for Computational and Applied Mathematics.Item Optimal algorithm for minimizing interference with two power levels in wireless sensor networks(Engineering and Technology Publishing, 2019) Lakshmi, M.P.; Shetty D, D.Interference is a major hindrance to the communication in wireless sensor networks which needs to be optimized in order to minimize the total power consumption of the network. A sensor node in a WSN is assigned certain transmission range for sensing and transmission of data. If the transmission between any two nodes is affected by a third node, then it leads to interference. Sender interference of a node in WSN is the number of nodes that lie within the transmission range of that vertex. The receiver interference of a node x is the number of other nodes which include x in their transmission range. In recent days WSNs are operated by a discrete set of power levels in which a limited number of power levels are available which can be assigned to a node. The problem of minimizing the maximum sender interference of a WSN using only two power levels is studied in this paper. An optimal algorithm is presented in this paper which assigns transmission power to the sensor nodes of a given network such that the maximum sender interference is minimized and it results in a connected topology. An algorithm for receiver interference is also proposed using a similar concept, and an extensive simulation is performed to compare the maximum sender and receiver interference for the same instances. © 2019 Journal of Communications.