Raghavendra Venkatesh Kulkarni - Academia.edu (original) (raw)
Papers by Raghavendra Venkatesh Kulkarni
2008 IEEE Swarm Intelligence Symposium, 2008
There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes ne... more There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is proposed in this paper for network-centric target localization in MANETs that are enhanced by mobile robots. Simulation study of two application scenarios is conducted. While one scenario focuses on quick target localization, the other aims at convergence of MANET nodes around the target. Reduction of swarm size during PSO search is proposed for accelerated convergence. The results of the study show that the proposed algorithm is effective in network-centric collaborative navigation. Emergence of converging behavior of MANET nodes is observed.
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2011
Wireless sensor networks (WSNs) are networks of autonomous nodes used for monitoring an environme... more Wireless sensor networks (WSNs) are networks of autonomous nodes used for monitoring an environment. Developers of WSNs face challenges that arise from communication link failures, memory and computational constraints, and limited energy. Many issues in WSNs are formulated as multidimensional optimization problems, and approached through bio-inspired techniques. Particle swarm optimization (PSO) is a simple, effective and computationally efficient optimization algorithm. It has been applied to address WSN issues such as optimal deployment, node localization, clustering and data-aggregation. This paper outlines issues in WSNs, introduces PSO and discusses its suitability for WSN applications. It also presents a brief survey of how PSO is tailored to address these issues.
IEEE Communications Surveys & Tutorials, 2011
Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or ... more Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. WSNs face many challenges, mainly caused by communication failures, storage and computational constraints and limited power supply. Paradigms of computational intelligence (CI) have been successfully used in recent years to address various challenges such as data aggregation and fusion, energy aware routing, task scheduling, security, optimal deployment and localization. CI provides adaptive mechanisms that exhibit intelligent behavior in complex and dynamic environments like WSNs. CI brings about flexibility, autonomous behavior, and robustness against topology changes, communication failures and scenario changes. However, WSN developers are usually not or not completely aware of the potential CI algorithms offer. On the other side, CI researchers are not familiar with all real problems and subtle requirements of WSNs. This mismatch makes collaboration and development difficult. This paper intends to close this gap and foster collaboration by offering a detailed introduction to WSNs and their properties. An extensive survey of CI applications to various problems in WSNs from various research areas and publication venues is presented in the paper. Besides, a discussion on advantages and disadvantages of CI algorithms over traditional WSN solutions is offered. In addition, a general evaluation of CI algorithms is presented, which will serve as a guide for using CI algorithms for WSNs.
2009 IEEE Symposium on Computational Intelligence in Milti-Criteria Decision-Making, 2009
Security plays a pivotal role in most applications of wireless sensor networks. It is common to f... more Security plays a pivotal role in most applications of wireless sensor networks. It is common to find inadequately secure networks confined only to controlled environments. The issue of security in wireless sensor networks is a hot research topic for over a decade. This paper presents a compact generalized neuron (GN) based medium access protocol that renders a CSMA/CD network secure against denial-of-service attacks launched by adversaries. The GN enhances the security by constantly monitoring multiple parameters that reflect the possibility that an attack is launched by an adversary. Particle swarm optimization, a popular bio-inspired evolutionary-like optimization algorithm is used for training the GN. The wireless sensor network is simulated using Vanderbilt Prowler, a probabilistic wireless network simulator. Simulation results show that the choice of threshold suspicion parameter impacts on the tradeoff between network effectiveness and lifetime.
Proceedings of the 2009 Ieee International Conference on Systems Man and Cybernetics, Oct 11, 2009
Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganes... more Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla, USA e-mail:{arvie, gkumar}@ieee.org ...
Neural Networks, Jun 1, 2010
Proceedings of the 2009 International Joint Conference on Neural Networks, 2009
... Abstract-This paper discusses an application of a neural network in wireless sensor network s... more ... Abstract-This paper discusses an application of a neural network in wireless sensor network security. ... The network of nodes that use the proposed MAC layer has this ability. ... THEMICA2 MOTE AND THE PROWLER SIMULATION ENVIRONMENT MICA, A low-cost prototype field ...
2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information, 2007
... 1942–1948. [2] SM Guru, SK Halgamuge, S.Fernando, “Particle Swarm Optimizers for Cluster form... more ... 1942–1948. [2] SM Guru, SK Halgamuge, S.Fernando, “Particle Swarm Optimizers for Cluster formation in Wireless Sensor Networks,” Proc. Int. ... 274 – 279 [6] C. Mendis, SM Guru, S. Halgamuge, S. Fernando, “Optimized sink node path using particle swarm optimization,” Proc. ...
2009 International Joint Conference on Neural Networks, 2009
... Abstract-This paper discusses an application of a neural network in wireless sensor network s... more ... Abstract-This paper discusses an application of a neural network in wireless sensor network security. ... The network of nodes that use the proposed MAC layer has this ability. ... THEMICA2 MOTE AND THE PROWLER SIMULATION ENVIRONMENT MICA, A low-cost prototype field ...
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganes... more Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla, USA e-mail:{arvie, gkumar}@ieee.org ...
Proceedings of the International Conference on Advances in Computing, Communications and Informatics - ICACCI '12, 2012
Wireless sensor network (WSN) refers to a group of spatially dispersed and dedicated sensors for ... more Wireless sensor network (WSN) refers to a group of spatially dispersed and dedicated sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location. Sensor Localization is a fundamental challenge in WSN. In this paper localization is modeled as a multi dimensional optimization problem. A comparison study of energy of processing
2012 International Conference on Advances in Mobile Network, Communication and Its Applications, 2012
Neural Networks, 2010
A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The ... more A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity.
Systems, Man, and …, 2010
Page 1. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICSPART C: APPLICATIONS AND REVIEWS, VOL.... more Page 1. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICSPART C: APPLICATIONS AND REVIEWS, VOL. 40, NO. 6, NOVEMBER 2010 663 Bio-inspired Algorithms for Autonomous Deployment and Localization of Sensor Nodes ...
2008 IEEE Swarm Intelligence Symposium, 2008
There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes ne... more There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is proposed in this paper for network-centric target localization in MANETs that are enhanced by mobile robots. Simulation study of two application scenarios is conducted. While one scenario focuses on quick target localization, the other aims at convergence of MANET nodes around the target. Reduction of swarm size during PSO search is proposed for accelerated convergence. The results of the study show that the proposed algorithm is effective in network-centric collaborative navigation. Emergence of converging behavior of MANET nodes is observed.
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2011
Wireless sensor networks (WSNs) are networks of autonomous nodes used for monitoring an environme... more Wireless sensor networks (WSNs) are networks of autonomous nodes used for monitoring an environment. Developers of WSNs face challenges that arise from communication link failures, memory and computational constraints, and limited energy. Many issues in WSNs are formulated as multidimensional optimization problems, and approached through bio-inspired techniques. Particle swarm optimization (PSO) is a simple, effective and computationally efficient optimization algorithm. It has been applied to address WSN issues such as optimal deployment, node localization, clustering and data-aggregation. This paper outlines issues in WSNs, introduces PSO and discusses its suitability for WSN applications. It also presents a brief survey of how PSO is tailored to address these issues.
IEEE Communications Surveys & Tutorials, 2011
Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or ... more Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. WSNs face many challenges, mainly caused by communication failures, storage and computational constraints and limited power supply. Paradigms of computational intelligence (CI) have been successfully used in recent years to address various challenges such as data aggregation and fusion, energy aware routing, task scheduling, security, optimal deployment and localization. CI provides adaptive mechanisms that exhibit intelligent behavior in complex and dynamic environments like WSNs. CI brings about flexibility, autonomous behavior, and robustness against topology changes, communication failures and scenario changes. However, WSN developers are usually not or not completely aware of the potential CI algorithms offer. On the other side, CI researchers are not familiar with all real problems and subtle requirements of WSNs. This mismatch makes collaboration and development difficult. This paper intends to close this gap and foster collaboration by offering a detailed introduction to WSNs and their properties. An extensive survey of CI applications to various problems in WSNs from various research areas and publication venues is presented in the paper. Besides, a discussion on advantages and disadvantages of CI algorithms over traditional WSN solutions is offered. In addition, a general evaluation of CI algorithms is presented, which will serve as a guide for using CI algorithms for WSNs.
2009 IEEE Symposium on Computational Intelligence in Milti-Criteria Decision-Making, 2009
Security plays a pivotal role in most applications of wireless sensor networks. It is common to f... more Security plays a pivotal role in most applications of wireless sensor networks. It is common to find inadequately secure networks confined only to controlled environments. The issue of security in wireless sensor networks is a hot research topic for over a decade. This paper presents a compact generalized neuron (GN) based medium access protocol that renders a CSMA/CD network secure against denial-of-service attacks launched by adversaries. The GN enhances the security by constantly monitoring multiple parameters that reflect the possibility that an attack is launched by an adversary. Particle swarm optimization, a popular bio-inspired evolutionary-like optimization algorithm is used for training the GN. The wireless sensor network is simulated using Vanderbilt Prowler, a probabilistic wireless network simulator. Simulation results show that the choice of threshold suspicion parameter impacts on the tradeoff between network effectiveness and lifetime.
Proceedings of the 2009 Ieee International Conference on Systems Man and Cybernetics, Oct 11, 2009
Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganes... more Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla, USA e-mail:{arvie, gkumar}@ieee.org ...
Neural Networks, Jun 1, 2010
Proceedings of the 2009 International Joint Conference on Neural Networks, 2009
... Abstract-This paper discusses an application of a neural network in wireless sensor network s... more ... Abstract-This paper discusses an application of a neural network in wireless sensor network security. ... The network of nodes that use the proposed MAC layer has this ability. ... THEMICA2 MOTE AND THE PROWLER SIMULATION ENVIRONMENT MICA, A low-cost prototype field ...
2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information, 2007
... 1942–1948. [2] SM Guru, SK Halgamuge, S.Fernando, “Particle Swarm Optimizers for Cluster form... more ... 1942–1948. [2] SM Guru, SK Halgamuge, S.Fernando, “Particle Swarm Optimizers for Cluster formation in Wireless Sensor Networks,” Proc. Int. ... 274 – 279 [6] C. Mendis, SM Guru, S. Halgamuge, S. Fernando, “Optimized sink node path using particle swarm optimization,” Proc. ...
2009 International Joint Conference on Neural Networks, 2009
... Abstract-This paper discusses an application of a neural network in wireless sensor network s... more ... Abstract-This paper discusses an application of a neural network in wireless sensor network security. ... The network of nodes that use the proposed MAC layer has this ability. ... THEMICA2 MOTE AND THE PROWLER SIMULATION ENVIRONMENT MICA, A low-cost prototype field ...
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganes... more Page 1. Bio-Inspired Node Localization in Wireless Sensor Networks Raghavendra V. Kulkarni, Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology Rolla, USA e-mail:{arvie, gkumar}@ieee.org ...
Proceedings of the International Conference on Advances in Computing, Communications and Informatics - ICACCI '12, 2012
Wireless sensor network (WSN) refers to a group of spatially dispersed and dedicated sensors for ... more Wireless sensor network (WSN) refers to a group of spatially dispersed and dedicated sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location. Sensor Localization is a fundamental challenge in WSN. In this paper localization is modeled as a multi dimensional optimization problem. A comparison study of energy of processing
2012 International Conference on Advances in Mobile Network, Communication and Its Applications, 2012
Neural Networks, 2010
A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The ... more A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity.
Systems, Man, and …, 2010
Page 1. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICSPART C: APPLICATIONS AND REVIEWS, VOL.... more Page 1. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICSPART C: APPLICATIONS AND REVIEWS, VOL. 40, NO. 6, NOVEMBER 2010 663 Bio-inspired Algorithms for Autonomous Deployment and Localization of Sensor Nodes ...