학술논문

Component based modeling for cross-layer analysis of 802.11 MAC and OLSR routing protocols in ad-hoc networks
Document Type
Conference
Source
MILCOM 2009 - 2009 IEEE Military Communications Conference Military Communications Conference, 2009. MILCOM 2009. IEEE. :1-7 Oct, 2009
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Transportation
Media Access Protocol
Routing protocols
Ad hoc networks
Wireless networks
Performance analysis
Physical layer
Network synthesis
Design methodology
Network topology
Telecommunication traffic
Language
ISSN
2155-7578
2155-7586
Abstract
We present a complete scenario driven component based analytic model of 802.11 MAC and OLSR routing protocols in MANETs. We use this model to provide a systematic approach to study the network performance and cross-layer analysis and design of routing, scheduling, MAC and PHY layer protocols. The routing protocol is divided into multiple components. Componentization is a standard methodology for analysis and synthesis of complex systems. To provide a component based design methodology, we have to develop a component based model of the wireless network that considers cross-layer dependency of performance. The component based model enable us to study the effect of each component on the overall performance of the wireless network, and to design each component separately. For the MAC layer, we use a fixed point loss model of 802.11 protocol that considers effects of hidden nodes and finite retransmission attempts. We have also considered simple models for PHY and scheduling. The main focus of this paper is on integration of these models to obtain a complete model for wireless networks. In several scenario driven studies, with user-specified topologies and traffic demands, we study the performance metrics - throughput and delay. By analyzing the performances under varying network scenarios, we are able to identify a few sources of performance degradation. We also study the effect of certain design parameters on the network performance. Thus, demonstrating the ability of the model to quickly identify problem components and try alternative design parameters.