Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
15 results
Search Results
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 Improved Algorithm for Minimum Power 2-Connected Subgraph Problem in Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2018) Lakshmi, M.; Shetty D, D.A Wireless Sensor Network (WSN) consists of small sensor nodes which communicate with each other using wireless radio channel and are used to monitor certain environmental parameters. Since the nodes are powered by a small battery of limited capacity, it is important to minimize the energy consumption in a WSN. By using an appropriate topology the energy utilization of the network can be minimized which results in an increased lifetime of a WSN. In practice, the transmission power of a sensor node can be tuned to obtain a required topology that satisfies certain connectivity constraints and this problem is known as Range Assignment Problem. For a given network, a reduced topology is constructed satisfying some connectivity constraints like k-connectivity, bounded diameter etc. Fault tolerance addresses the issue of node or link failure which aims at k-connectivity so that, the network has at least k vertex disjoint paths between any two nodes of the network. With the motivation of achieving fault tolerant network with minimum transmission energy, we consider Minimum power 2-connected subgraph (MP2CS) problem which is proved to be NP-hard. A polynomial time heuristic is proposed in this paper for the MP2CS problem and simulation is performed to compare with the existing algorithm. © 2018 IEEE.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 Quantum PSO algorithm for clustering in wireless sensor networks to improve network lifetime(Springer Verlag service@springer.de, 2019) Kanchan, P.; Shetty D, D.Clustering is done in wireless sensor networks (WSN) to conserve the energy of sensor nodes in the network. The network lifetime of WSN can be defined as the duration for which the network remains operational. It is a critical design issue in WSN’s since once a node is deployed, it may not be feasible to replace or recharge the sensor nodes. In this paper, we proposed a quantum PSO algorithm for improving network lifetime called quantum PSO clustering algorithm to improve network lifetime(QPCINL). The QPCINL uses quantum bits. A quantum bit can exist in ‘0’ state, ‘1’ state or a linear superposition of ‘0’ and ‘1’ states, unlike the binary bit which can exist in only ‘0’ state or ‘1’ state. We define a factor called network lifetime factor(NLF) which allows us to compare various algorithms. We test our algorithm by giving different values to the number of sensor nodes and cluster heads, varying the base station position, etc. Then, we compare our results to existing algorithms and demonstrate the superiority of our algorithm. © Springer Nature Singapore Pte Ltd. 2019.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 Health Assessment of 1485 Top Level Domain's Name Servers(Institute of Electrical and Electronics Engineers Inc., 2023) Adiwal, S.; Rajendran, B.; Shetty D, D.; Sudarsan, S.D.Domain Name System (DNS) has evolved as a critical component in the accessibility of Internet services and has therefore become a key attack vector in major Internet attacks. It is essential to monitor various DNS communications parameters, take corrective actions when needed, and prevent abuse. We propose a new set of metrics that could be monitored to assess the health of a given Top Level Domains (TLDs) nameserver. We then conduct passive probes and determine the values of the proposed parameters for the nameservers serving the 1485 TLDs of the Internet. The values of the identified metrics help to detect sluggishness in performance and form the basis for arriving at a score of their health. The presented approach is scalable across the DNS hierarchy and can be repeated periodically to detect and prevent DNS abuses. © 2023 IEEE.Item An Approach for Predicting Election Results with Trending Twitter Hashtag Information Using Graph Techniques and Sentiment Analysis(Springer Science and Business Media Deutschland GmbH, 2023) Patra, C.; Shetty D, D.; Chakraborty, S.India is one of the largest democracies in the world where the Lok Sabha and the Rajya Sabha elections are held every five years. Nowadays, social media acts as an important and inexpensive platform for propagating messages of the political parties. In the present study, a methodology is proposed by combining sentiment analysis and graph techniques to look into the trending hashtag networks propagated by the political parties using Twitter. The demonstration of the proposed methodology is done on the trending hashtag’s information collected from Twitter on the Uttar Pradesh (U.P) state elections, 2022. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item An Approach for Efficient Graph Mining from Big Data Using Spark(Springer Science and Business Media Deutschland GmbH, 2023) Gupta, R.K.; Shetty D, D.; Chakraborty, S.Huge amount of data is generated and accumulated over the last decade, and therefore, the use of data mining techniques is required to extract usable information from these massive data sets. Gaining important connections between data helps in getting useful insights. Depiction of relationships between the data using graphical approach is observed to be a helpful method. It provides an effective technique for demonstrating the working in a variety of situations, including biological networks, social networks, Web networks, and so on. Clustering techniques used in graph mining can be helpful for accumulating significant information. In this paper, an approach for graph mining from big data in Spark (AGMBS) is proposed on the basis of label propagation. The suggested technique enhances the efficiency of the conventional label propagation algorithm by making it more resilient. In addition to this, AGMBS employs a sparse matrix as its primary data structure, resulting in quicker performance. Thereafter, GraphX is used for managing the processing of the graphical data. The experiments were conducted on two graph data sets from the real world, and it is observed that the suggested AGMBS gives faster results as compared to the best available clustering algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.