Title page for ETD etd-01242005-192139


Type of Document Master's Thesis
Author Mallanda, Cariappa D
URN etd-01242005-192139
Title Sensorsimulator: Simulation Framework for Sensor Networks
Degree Master of Science in Systems Science (M.S.S.S.)
Department Computer Science
Advisory Committee
Advisor Name Title
S. Sitharama Iyengar Committee Chair
Arjan Durresi Committee Member
Rajgopal Kannan Committee Member
Keywords
  • performance evaluation
  • sensor network
  • simulation
Date of Defense 2004-12-02
Availability unrestricted
Abstract
Wireless sensor networks have the potential to become significant subsystems of engineering applications. Before relegating important and safety-critical tasks to such subsystems, it is necessary to understand the dynamic behavior of these subsystems in simulation environments. There is an urgent need to develop a simulation platform that is useful to explore both the networking issues and the distributed computing aspects of wireless sensor networks. Current approaches to simulating wireless sensor networks largely focus on the networking issues. These approaches use well-known network simulation tools that are often difficult to extend to explore distributed computing issues.

Discrete-event simulation is a trusted platform for modeling and simulation of a variety of systems. SensorSimulator is a discreet event simulation framework for sensor networks built over OMNeT++. It is a customizable and an extensible framework for wireless sensor network simulation. This framework allows the user to debug and test software for distributed sensor networks independent of hardware constraints. The extensibility of SensorSimulator allows developers and researchers to investigate topological, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, and to defeat those algorithms through simulated failure. The framework provides modules for various layers. Applications can be implemented by using these framework modules by sub classing the framework classes and customizing their behavior at various network layers.

We validate and demonstrate the usability of these capabilities through analyzing the simulation results of Directed Diffusion and GEAR. A comparison study of performance of SensorSimulator v/s NS2 for various network densities and traffic have shown that SensorSimulator is able to achieve higher scalability and requires less time for execution.

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