Information Estimation with Node Placement Strategy in 3D Wireless Sensor Networks

Abstract

The cluster formation in three-dimensional wireless sensor networks (3D-WSN) gives rise to overlapping of signals due to spherical sensing range which leads to information redundancy in the network. To address this problem, we develop a sensing algorithm for 3D-WSN based on dodecahedron topology which we call three-dimensional distributed clustering (3D-DC) algorithm. Using 3D-DC algorithm in 3D-WSN, accurate information extraction appears to be a major challenge due to the environmental noise where a cluster head (CH) node gathers and estimates information in each dodecahedron cluster. Hence, to extract precise information in each dodecahedron cluster, we propose three-dimensional information estimation (3D-IE) algorithm. Moreover, node deployment strategy also plays an important factor to maximize information accuracy in 3D-WSN. In most cases, sensor nodes are deployed deterministically or randomly. But both the deployment scenarios are not aware of where to exactly place the sensor nodes to extract more information in terms of accuracy. Therefore, placing nodes in its appropriate positions in 3D-WSN is a challenging task. We propose a three-dimensional node placement (3D-NP) algorithm which can find the possible nodes and their deployment strategy to maximize information accuracy in the network. We perform simulations using MATLAB to validate the 3D-DC, 3D-IE and 3D-NP, algorithms, respectively.

KEYWORDS:

• Information estimation
• Node placement
• Spatial correlation
• Three-dimensional sensor networks

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. Theoretically, sensor nodes with uniform dodecahedron sensing range can remove the tessellate space for cluster formation, whereas in Algorithm 1, we consider that there are tessellate among clusters since they are not uniform in 3D space.

Additional information

Notes on contributors

Jyotirmoy Karjee

Jyotirmoy Karjee received his Ph.D in Engineering from Indian Institute of Science, Bangalore, India. He did his post-doctoral research from Technische Universitat Munchen, Germany. Presently, he holds the position of Researcher at Embedded Systems and Robotics group, TCS Research and Innovation, Bangalore, India. He is a recipient of Heritage Erasmus Mundus scholarship (fellowship) to do postdoctoral research. He is interested in statistical signal processing, wireless sensor networks, wireless communications, robotic communications and embedded systems, machine learning, cloud computing and Internet of things.

E-mail: [email protected]

H.S. Jamadagni

H.S. Jamadagni received his M.E and Ph.D degrees in Electrical and Communication Engineering from Indian Institute of Science, Bangalore. Currently, he is a professor at Department of Electronic System Engineering, Indian Institute of Science. He is one of the main coordinators for the Intel higher education program, member of Telecommunications Regulatory Authority of India (TRAI) and key mentors for various Intel workshops in India. His current research work is in the areas of communication networks, embedded systems, VLSI for wireless networks, etc.

E-mail: [email protected]