Faculty Publications
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Item Sink attributes analysis for energy efficient operations of wireless sensor networks under randomly varying temporal and spatial aspects of query generation(Elsevier GmbH, 2015) Kumar, P.; Chaturvedi, A.Rapid advances and the development, compactness and economic viability; in IC technology, network hardware components and associated software have completely change the networking paradigm. The wireless sensor networks (WSNs) have also been not isolated from this unexpected changeover. This paper addresses three principal aspects that have been of interest in the WSN researcher community. These are investigating the suitable cluster formation scheme from some prominent scheme, incorporating the Spatio-temporal aspects of random query generation and subsequently model it using appropriate and extensively used probabilistic distribution functions, and exploring the importance of sink node(s) attributes towards much better energy profile of the WSN, as the energy consumption have been a vital component in deciding the overall network service conditions. The integration of these three aspects led to various case studies, which principally involves, uses of SKM, SFCM, DKM and DFCM as clustering schemes, uniform and Poisson probability mass functions uses to mathematically model the Spatio-temporal dependence of query distribution pattern, and the network surveillance by a single stationary sink, a moveable sink and four stationary sinks. The simulation results of various case studies are analyzed and compared. © 2015 Elsevier GmbH.Item Probabilistic query generation and fuzzy c -means clustering for energy-efficient operation in wireless sensor networks(John Wiley and Sons Ltd vgorayska@wiley.com Southern Gate Chichester, West Sussex PO19 8SQ, 2016) Kumar, P.; Chaturvedi, A.Depending upon sensing attributes, wireless sensor networks (WSNs) are classified as event driven, time driven, and query driven. In a given surveillance area, approximation of query generation process using uniform probability mass function (PMF) model seems to be reasonable in aggregate terms based on observations extracted from lifetime span of WSNs. However, owing to random generation aspects of query and the associated temporal variations, the Poisson distribution-based model appears to be more appropriate to resemble the realistic query generation pattern. Invariably, in all the sensor network architectures, the energy management requires an important consideration owing to limited energy resources. For the optimal utilization of energy resources, we propose fuzzy c-means (FCM) algorithm to form clusters in a hierarchical network configuration. Network performance is measured in terms of key performance measures, namely, average residual energy status, critical residual energy status (CRES), and number of network nodes that attain the CRES mark. These performance measures are estimated and analyzed for three different PMF models of query generation namely Uniform, Gaussian and Poisson. The merit of deploying FCM algorithm in terms of maintaining much better energy profile of the entire network is discussed. © Copyright 2016 John Wiley & Sons, Ltd.Item Spatio-temporal probabilistic query generation model and sink attributes for energy-efficient wireless sensor networks(Institution of Engineering and Technology journals@theiet.org, 2016) Kumar, P.; Chaturvedi, A.Proliferation in Micro-Electro-Mechanical-Systems (MEMS) technology along with advancement in distributed computing infrastructure has facilitated the versatile usage and deployment of wireless sensors networks (WSNs) in last one and half decades. WSNs support large number of applications from the civilian and military regimes. Irrespective of these regimes; owing to difficulty associated with battery replenishment, proper energy usage has been at centre stage in WSNs operations. The lifetime of WSNs typically depends upon sensor's energy dissipation pattern, which is non-homogeneous with respect to spatial distribution over any short epochs. The genesis behind this nonhomogeneity is random generation of queries, which owes to application specific spatio-temporal parameters. Importance of spatio-temporal parameters is ubiquitous in WSNs paradigm and uncertainties are inevitable with these parameters, although the degree of uncertainties varies in accordance to applications served. Thus, from network design perspectives, precision involved with spatio-temporal aspects must be given due priority to obtain a mathematical model that maintains a good rapport with realistic query generation process. With these motivations, the study explores: (i) uses of energy-efficient clustering schemes, (ii) incorporation of spatio-temporal parameters uncertainties into probabilistic model of query generation using fuzzy-intervals bound, and (iii) sink attributes to enhance network lifetime. For various network surveillance scenarios; the performance measures average residual energy status and service-time-duration are estimated and analysed. © The Institution of Engineering and Technology 2016.