Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Computer Science


Computer Science and Engineering

First Advisor

Gergely Zaruba


This dissertation presents efficient routing and channel assignment schemes for interference avoidance in wireless mesh networks (WMNs). The most significant contributions of this dissertation are the development and design of two routing algorithms that help in improving network throughput by selecting less interference paths both for single and multiple radio WMNs and the design of an intelligent channel assignment scheme which increases the overall network capacity by assigning partially overlapped channels having less interference among neighboring ones for multi radio multi channel wireless mesh networks (MRMC-WMNs). For single radio single channel WMNs, we propose AMIRA (Ant Mesh routing for InteRference Avoidance), an interference-aware routing protocol designed to improve load balancing by avoiding inter and intra flow interference in a typical mesh backbone network. AMIRA is based on the framework of Ant Colony Optimization (ACO) which is a meta-heuristic approach for stochastically solving a problem. ACO is used together with our local heuristic technique to avoid interference within and among packet flows. In AMIRA, each node uses MAC level information to measure link qualities which helps in selecting reduced interference paths thus resulting in improved load balancing in addition to the auto load balancing feature of the ACO framework. We demonstrate through simulations that AMIRA quickly converges to the best path when traffic characteristics change. We tune the parameters of AMIRA to study the effect on the performance of routing load and end-to-end delay. Our simulation results demonstrate that under congestion, AMIRA gives increased throughput and low end-to-end delay when compared to other existing ant-based routing protocols because of its interference aware technique and stochastic data forwarding nature. We then extend our work of AMIRA to develop a forwarding architecture-AntMesh that is designed for both single and multiple radio infrastructure WMNs and take care of both inter and intra flow interferences. AntMesh is a distributed interference-aware data forwarding architecture based on smart ants. In addition, we also propose a novel routing metric called Ant Routing Metric (ARM) designed to effectively utilize the space/channel diversity typically common in infrastructure WMNs. One interesting result of our investigation is that AntMesh has the capability to discover high throughput paths with less inter-flow and intra-flow interference when conventional wireless network routing protocols and metrics fail to do so. This conclusion is based on extensive evaluation and testing of AntMesh under various network scenarios both on fixed nodes mesh networks and on mobile WMN scenarios. The results obtained show AntMesh's advantages that make it a valuable candidate to operate in MRMC mesh networks. In the design of any WMN channel assignment scheme, understanding and mitigating interference is one of the fundamental issues. Therefore, we address the problem of channel assignment considering partially overlapping channels (POCs) for interference avoidance in multi radio multi channel wireless mesh networks (MRMC-WMNs). A novel interference capture model is proposed which provides a systematic approach of measuring the interference caused by links operating on POCs. This model takes both the adjacent channel interference and the corresponding physical distance between mesh nodes into account. Based on this model, we design a centralized and a distributed interference-aware channel assignment algorithm called i- POCA which enables the use of smart ants for assigning orthogonal and non-orthogonal channels to radios in order to minimize total network interference. We evaluate our algorithms through extensive simulations and demonstrate that our proposed algorithms improve network throughput by efficient utilization of the available spectrum.


Computer Sciences | Physical Sciences and Mathematics


Degree granted by The University of Texas at Arlington