Pradip Kumar Das

Bio: Pradip Kumar Das is an academic researcher from RCC Institute of Information Technology. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 2, co-authored 3 publications receiving 32 citations.

Intrusion Detection at International Borders and Large Military Barracks with Multi-sink Wireless Sensor Networks: An Energy Efficient Solution

Abstract: Wireless Sensor Networks have profound applications in military systems. Intrusion at unmanned borders and at other sensitive places may be tracked using sensor networks. However, the domain of military applications could imply hostile environment and thus monitoring of the nodes of the deployed WSN could be practically impossible. It is thus required that the deployed WSN ensures low energy consumption to give a high network life such that the cost of deployment may be suitably amortized. In this paper we propose an energy efficient solution for detecting intrusions through unmanned borders and other sensitive places with prolonged network lifetime using two routing schemes: KPS and Loop Free (LF)-KPS. We have compared these two schemes with LEACH and TEEN, and have shown how data transfer through KPS and LF-KPS protocols would ensure an enhanced lifetime for the deployed network. At the end we have also shown the effect of looping on the lifetime of the deployed network.

Optimal Energy-Based Clustering with GPS-Enabled Sensor Nodes

Abstract: Wireless Sensor Networks (WSN) consist of a collection of wireless nodes that dynamically create a network themselves. However while doing so, not always energy optimization is considered. But energy consumption should be made as much low as possible since power is a constraint for these nodes. This paper proposes a clustering algorithm in Wireless Sensor Network that uses few GPS-enabled nodes or beacons that help in localization of the nodes and thereby orienting themselves within clusters such that energy consumption becomes optimum during their activities of sensing and communication. The paper focuses on optimizing energy consumption during cluster formation in sensor networks.

On Regulating Lifetime of a 3-sink Wireless Sensor Network Deployed for Precision Agriculture

Abstract: The main motivation behind this work is regulating network lifetime of a WSN deployed in an agricultural land. In this paper we have proposed one 3-sink WSN architecture to be used for precision agriculture applications. The objective of this paper is twofold; to propose a model of WSN to be used for precision agriculture that prolongs network lifetime, and to regulate network lifetime through introduction of two parameters – neighbor density and effective network density. Neighbor density is the measure of density of neighbors around a particular node. Here we have seen that at an optimum value of neighbor density, lifetime of a network reaches its pinnacle. However, regulating network lifetime through neighbor density requires the nodes to be deployed in grid fashion. For networks where nodes are deployed in random fashion, effective network density may be used as regulating parameter for prolonging network lifetime. In this paper we propose two routing schemes: KPS and Loop Free (LF)-KPS for network lifetime enhancement. The results show that LF-KPS in particular outperforms some well-known protocols by a considerable margin.

QoS provisioning-based routing protocols using multiple data sink in IoT-based WSN

Abstract: The Internet of Things (IoT) is a promising paradigm in which the objects are fused with the capabilities of sensing, networking, identifying and processing to make it feasible for them to communic...

A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks

Abstract: Sensors in a Wireless Sensor Network (WSN) sense, process, and transmit information simultaneously. They mainly find applications in agriculture monitoring, environment monitoring, smart city development and defence. These applications demand high-end performance from the WSN. However, the performance of a WSN is highly vulnerable to various types of security threats. Any intrusion may reduce the performance of the WSN and result in fatal problems. Hence, fast intrusion detection and prevention is of great use. This paper aims towards fast detection and prevention of any intrusion using a machine learning approach based on Gaussian Process Regression (GPR) model. We have proposed three methods (S-GPR, C-GPR and GPR) based on feature scaling for accurate prediction of k-barrier coverage probability. We have selected the number of nodes, sensing range, Sensor to Intruder Velocity Ratio (SIVR), Mobile to Static Node Ratio (MSNR), angle of the intrusion path, and required k as the potential features. These features are extracted using an analytical approach. Simulation results demonstrate that the proposed method III accurately predicts the k-barrier coverage probability and outperforms the other two methods (I and II) with a correlation coefficient (R = 0.85) and Root Mean Square Error (RMSE = 0.095). Further, the proposed methods achieve a higher accuracy as compared to other benchmark schemes.

A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink

Abstract: Solutions for energy hole problem in wireless sensor networks (WSNs) have been excessively explored using mobile sink (MS). Although, MS provides a considerable amount of energy saving and extends network lifetime. However, MS introduces varying degree of data acquisition latency depending on the trajectory followed. Therefore, rendezvous based data acquisition methods are proposed to mitigate this issue which are aimed to provide a trade-off between energy consumption and data acquisition latency. There exists a list of surveys that focus on issues related to sink mobility such as mobility aware energy efficient data acquisition schemes, mobility aware data acquisition and routing, etc. However, none of these surveys concern about the issue of providing a trade-off between energy consumption and data acquisition latency. Therefore, this review addresses the same issue and presents a taxonomy of rendezvous based data acquisition methods along with the design goals and associated designing requirements. The methods are grouped into two categories: rendezvous point (RP) based and rendezvous area (RA) based. Furthermore, a phase-wise comprehensive overview of these methods is provided which clearly unfold the way of resolving the targeted issue. Finally, the research issues and challenges are discussed in pursuit of data acquisition by MS.

Energy Efficient Gravitational Search Algorithm and Fuzzy Based Clustering With Hop Count Based Routing For Wireless Sensor Network

Abstract: In Wireless sensor networks, energy efficiency is the significant attribute to be improved. Clustering is the major technique to enhance energy efficiency. Using this technique, sensor nodes in the network region are grouped as several clusters and cluster head (CH) is chosen for each and every cluster. This CH gathers data packet from the non-CH members inside the cluster and forwards the collected data packet to the base station. However, the CH may drain its energy after a number of transmissions. So, we present the Energy efficient Gravitational search algorithm (GSA) and Fuzzy based clustering with Hop count based routing for WSN in this paper. Initially, CH is selected using Gravitational Search Algorithm (GSA), based on its weight sensor nodes are joined to the CH and thus cluster is formed. Among the selected CHs in the network, supercluster head (SCH) is selected using a fuzzy inference system (FIS). This selected SCH gathers the data packet from all CHs and forwards it to the sink or base station. For transmission, the efficient route is established based on the hop count of the sensor nodes. Simulation results show that the performance of our proposed approach is superior to the existing work in terms of delivery ratio and energy efficiency.

Towards Network Lifetime Enhancement of Resource Constrained IoT Devices in Heterogeneous Wireless Sensor Networks.

Abstract: The participating nodes in Wireless Sensor Networks (WSNs) are usually resource-constrained in terms of energy consumption, storage capacity, computational capability, and communication range. Energy is one of the major constraints which requires an efficient mechanism that takes into account the energy consumption of nodes to prolong the network lifetime. Particularly in the large scale heterogeneous WSNs, this challenge becomes more critical due to high data collection rate and increased number of transmissions. To this end, clustering is one of the most popular mechanisms which is being used to minimize the energy consumption of nodes and prolong the lifetime of the network. In this paper, therefore, we propose a robust clustering mechanism for energy optimization in heterogeneous WSNs. In the proposed scheme, nodes declare themselves as cluster head (CH) based on available resources such as residual energy, available storage and computational capability. The proposed scheme employs the multi criteria decision making technique named as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which allows the child nodes to select the optimal CH among several potential CH candidates. Moreover, we also propose mechanisms such as CH-acquaintanceship and CH-friendship in order to prolong the network lifetime. Simulation results show that our proposed scheme minimizes the control overhead, reduces the power consumption and enhances overall lifetime of the network by comparing with the most recent and relevant proposed protocol for WSNs.