| Type of Document |
Master's Thesis |
| Author |
Bhat, Aniket Anant
|
| Author's Email Address |
bhat@vt.edu |
| URN |
etd-07092004-152907 |
| Title |
Stochastic Petri Net Models of Service Availability in a PBNM System for Mobile Ad Hoc Networks. |
| Degree |
Master of Science |
| Department |
Electrical and Computer Engineering |
| Advisory Committee |
| Advisor Name |
Title |
| DaSilva, Luiz A. |
Committee Chair |
| Midkiff, Scott F. |
Committee Member |
| Phanse, Kaustubh S. |
Committee Member |
| Varadarajan, Srinidhi |
Committee Member |
|
| Keywords |
- Service availability
- Stochastic Petri Nets
- non-Markovian modeling
- mobile ad hoc networks
- policy-based network management
|
| Date of Defense |
2004-07-06 |
| Availability |
unrestricted |
Abstract
Policy based network management is a promising approach for provisioning and management of quality of service in mobile ad hoc networks. In this thesis, we focus on performance evaluation of this approach in context of the amount of service received by certain nodes called policy execution points (PEPs) or policy clients from certain specialized nodes called the policy decision points (PDPs) or policy servers. We develop analytical models for the study of the system behavior under two scenarios; a simple Markovian scenario where we assume that the random variables associated with system processes follow an exponential distribution and a more complex non-Markovian scenario where we model the system processes according to general distribution functions as observed through simulation. We illustrate that the simplified Markovian model provides a reasonable indication of the trend of the service availability seen by policy clients and highlight the need for an exact analysis of the system without relying on Poisson assumptions for system processes. In the case of the more exact non-Markovian analysis, we show that our model gives a close approximation to the values obtained via empirical methods. Stochastic Petri Nets are used as performance evaluation tools in development and analysis of these system models.
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