Sharma A.,DAV Institute of Engineering and Technology |
Sharma A.K.,Lrdav College |
Agnihotri K.,SBS State Technical Campus
Nonlinear Dynamics | Year: 2015
The present paper aims to study the interaction of toxin producing phytoplankton (TPP)–zooplankton (a prey–predator interaction) and its role in plankton ecology. The delay in the zooplankton predation is considered and its effect on the overall dynamic of phytoplankton–zooplankton interaction is studied. Moreover, Holling IV type response function is used for zooplankton grazing to account for the effect of toxication by the TPP population. It is shown that time delay can destabilise the given system and induce oscillation in population due to Hopf-bifurcation. Further stability of the bifurcating periodic solution is determined by using normal form theory and centre manifold arguments. Some numerical simulations are executed to validate the analytical findings. © 2015, Springer Science+Business Media Dordrecht.
Kumar A.,Panipat Institute of Engineering and Technoly |
Khosla A.,National Institute of Technology Jalandhar |
Saini J.S.,Sudan University of Science and Technology |
Singh S.,SBS State Technical Campus
Advances in Intelligent Systems and Computing | Year: 2013
This paper proposes two range based 3D node localization algorithms using application of Hybrid Particle Swarm Optimization (HPSO) and Biogeography Based Optimization (BBO) for anisotropic Wireless Sensor Networks (WSNs). Target nodes and anchor nodes are randomly deployed with constraints over three layer boundaries. The anchor nodes are randomly distributed over top layer only and target nodes over middle and bottom layers. Radio irregularity factor, i.e., an anisotropic property of propagation media and an heterogenous property (different battery backup statuses) of devices are considered. PSO models provide fast but less mature convergence whereas the proposed HPSO algorithm provides fast and mature convergence. Biogeography is based upon the collective learning of geographical allotment of biological organisms. BBO has a new comprehensive energy based on the science of biogeography and apply migration operator to share selective information between different habitats, i.e., problem solutions. Due to size and complexity of WSN, localization problem is articulated as an NP-hard optimization problem . In this work, an error model in a highly noisy environment is depicted for estimation of optimal node location to minimize the location error using HPSO and BBO algorithms. The simulation results establish the strength of the proposed algorithms by equating the performance in terms of the number of target nodes localized with accuracy, and computation time. It has been observed that existing sensor networks localization algorithms are not significant to support the rescue operations involving human lives. Proposed algorithms are beneficial for rescue operations too to find out the accurate location of target nodes in highly noisy environment. © 2013 Springer.
Gulati M.K.,Khalsa College for Women |
Kumar K.,SBS State Technical Campus
International Journal of Communication Networks and Distributed Systems | Year: 2016
Due to the mobility and limited energy of the mobile nodes, frequent link failures occur in mobile ad hoc network (MANET) which makes quality of service (QoS) routing a challenging task. In this paper, we consider these issues and propose a cross layer weight based on demand routing protocol (CLWORP) which uses the weight-based route strategy to select a stable and energy efficient route in order to enhance quality of service performance. The weight of a route is decided by three factors: link signal strength, residual energy and drain rate. Multiple routes are discovered from the source node to the destination node with the different weight values. Then the path with the largest weight value is selected at the destination. Simulation results show that the proposed CLWORP outperforms AODV especially in a high mobility environment. © Copyright 2016 Inderscience Enterprises Ltd.
Ghumman N.S.,SBS State Technical Campus |
Kaur R.,SBS State Technical Campus
6th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2015 | Year: 2015
Cloud Computing is a new technology. Cloud Computing provides many facilities like on demand self-services, unlimited resources, rapid elasticity and measured services to end users. All users access these resources directly through internet. Users can use these resources and services as they want on pay per use concept. In cloud computing architecture load balancing is a very important issue. There are many algorithms for load balancing in cloud computing. All algorithms work different ways. We proposed a Improved Max-Min Ant colony Algorithm. Improved Max-Min used the concept of original Max-Min. Improved Max-Min is based on the execution time not on completion time as a selection basis. The main motive of our work is to balance the total load of cloud system.We try to minimizing the total makespan. We simulated results using the CloudSim toolkit. Results show the comparison between improved max min and new hybrid improved Max-Min ant approach. It mainly focuses on total processing time and processing cost. © 2015 IEEE.
Kaur K.,SBS State Technical Campus |
Behal S.,SBS State Technical Campus
Procedia Computer Science | Year: 2015
Captcha is stands for Completely Automated Public Turing test to tell Computer and Human Apart. As the increase of automated bots systems or software that misuse and corrupt the public web services, the user must required going through and solving a Turing test problem, before they are use web services. This Turing test is called Captcha. In this paper we have discuss an improved text-based captcha which is more secure, and more robust as compared to another Captchas. © 2015 The Authors. Published by Elsevier B.V.