Samayveer Singh

Work place: Department of Computer Engineering, Netaji Subhas Institute of Technology, New Delhi, India



Research Interests: Computer Networks, Network Architecture, Network Security


Samayveer Singh received his B.Tech. in Information Technology from Uttar Pradesh Technical University, Lucknow, India in 2007, and his M.Tech. degree in Computer Science & Engineering from National Institute of Technology, Jalandhar, India, in 2010. He is now a PhD student of Department of Computer Engineering at Netaji Subhas Institute of Technology, New Delhi, India. His research interest includes wireless sensor networks.

Author Articles
Heterogeneous Energy Efficient Protocol for Enhancing the Lifetime in WSNs

By Samayveer Singh Aruna Malik

DOI:, Pub. Date: 8 Sep. 2016

In this paper, we propose a 3-level heterogeneous network model for WSNs to enhance the network lifetime, which is characterized by a single parameter. Depending upon the value of the model parameter, it can describe 1-level, 2-level, and 3-level heterogeneity. Our heterogeneous network model also helps to select cluster heads and their respective cluster members by using weighted election probability and threshold function. We compute the network lifetime by implementing HEED protocol for our network model. The HEED implementation for the existing 1-level, 2-level, and 3-level heterogeneous network models are denoted as HEED-1, HEED-2, and HEED-3, respectively, and for our proposed 3-level heterogeneous network model, the SEP implementations are denoted as hetHEED-1, hetHEED-2, and hetHEED-3, respectively. As evident from the simulation results, the hetHEED-3 provides longer lifetime than that of the HEED-3 for all cases.

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Performance Evaluation of Distributed Protocols Using Different Levels of Heterogeneity Models in Wireless Sensor Networks

By Samayveer Singh Satish Chand Bijendra Kumar

DOI:, Pub. Date: 8 Dec. 2014

Most of the protocols for enhancing the lifetime of wireless sensor networks (WSNs) are of a homogeneous nature in which all sensors have equal amount of energy level. In this paper, we study the effect of heterogeneity on the homogeneous protocols. The ALBPS and ADEEPS are the two important homogeneous protocols. We incorporate heterogeneity to these protocols, which consists of 2-level, 3-level and multi-level heterogeneity. We simulate and compare the performance of the ALBPS and ADEEPS protocols in homogeneous and heterogeneous environment. The simulation results indicate that heterogeneous protocols prolong the network lifetime as compared to the homogeneous protocols. Furthermore, as the level of heterogeneity increases, the lifetime of the network also increases.

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Distributed Algorithms for Maximizing Lifetime of WSNs with Heterogeneity and Adjustable Sensing Range for Different Deployment Strategies

By Samayveer Singh Ajay K Sharma

DOI:, Pub. Date: 8 Jul. 2013

Focus of this paper is on energy heterogeneity and distributed algorithms for scheduling and adjustable range. The problem of lifetime enhancement of wireless sensor networks is dealt with the adjustment of transmission or sensing range of the sensor nodes and implementation of heterogeneous energy model. In this work, we deploy the sensor nodes in 2-D using triangular, square, and hexagonal tiles. The initial energies of the sensors and their positions along with the positions of targets are known. For this environment, we investigate the maximum achievable lifetime using heterogeneous deterministic energy efficient protocol with adjustable sensing range (HADEEPS) and heterogeneous load balancing protocol with adjustable sensing range (HALBPS). We observe that deploying the sensors in triangular tiles gives better lifetime.

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3-Level Heterogeneity Model for Wireless Sensor Networks

By Satish Chand Samayveer Singh Bijendra Kumar

DOI:, Pub. Date: 8 Apr. 2013

In this paper, we propose a network model with energy heterogeneity. This model is general enough in the sense that it can describe 1-level, 2-level, and 3-level heterogeneity. The proposed model is characterized by a parameter whose lower and upper bounds are determined. For 1-level heterogeneity, the value of parameter is zero and, for 2-level heterogeneity, its value is (√5-1)/2. For 3-level of heterogeneity, the value of parameter varies between its lower bound and upper bound. The lower bound is determined from the energy levels of different node types, whereas the upper bound is given by (√5-1)/2. As value of parameter decreases from upper bound towards the lower bound, the network lifetime increases. Furthermore, as the level of heterogeneity increases, the network lifetime increases.

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