PhD Dissertation – June 2010
A Credit-based Home Access Point (CHAP) to Improve Application Quality on IEEE 802.11 Networks
Increasing availability of high-speed Internet and wireless access points has allowed home users to connect not only their computers but various other devices to the Internet. Every device running different applications requires unique Quality of Service (QoS). It has been shown that delay-sensitive applications, such as VoIP, remote login and online game sessions, suffer increased latency in the presence of throughput-sensitive applications such as FTP and P2P. Currently, there is no mechanism at the wireless AP to mitigate these effects except explicitly classifying the traffic based on port numbers or host IP addresses. We propose CHAP, a credit-based queue management technique, to eliminate the explicit configuration process and dynamically adjust the priority of all the flows from different devices to match their QoS requirements and wireless conditions to improve application quality in home networks. An analytical model is used to analyze the interaction between flows and credits and resulting queueing delays for packets. CHAP is evaluated using Network Simulator (NS2) under a wide range of conditions against First-In-First-Out (FIFO) and Strict Priority Queue (SPQ) scheduling algorithms. CHAP improves the quality of an online game, a VoIP session, a video streaming session, and a Web browsing activity by 20%, 3%, 93%, and 51%, respectively, compared to FIFO in the presence of an FTP download. CHAP provides these improvements similar to SPQ without an explicit classification of flows and a pre-configured scheduling policy. A Linux implementation of CHAP is used to evaluate its performance in a real residential network against FIFO. CHAP reduces the web response time by up to 85% compared to FIFO in the presence of a bulk file download. Our contributions include an analytic model for the credit-based queue management, simulation, and implementation of CHAP, which provides QoS with minimal configuration at the AP.
Masters Thesis – May 2002
WHITE – Achieving Fair Bandwidth Allocation with Priority Dropping Based on Round Trip Time
Increase in Internet traffic has increased the importance of congestion control and fairness. Active queue management, such as Random Early Detection (RED) seeks to improve congestion and fairness. However, RED serves flows unfairly when there are many TCP flows with various roundtrip times (RTT). Adaptive Explicit Congestion Notification (AECN) is a direct extension of RED to address this issue by classifying flows into three classes: robust, average and fragile, based on their RTTs. We propose an extension to AECN called MAECN (More Adaptive ECN) to improve AECN to handle more diverse traffic mixes. We believe that MAECN will serve various types of traffic more fairly than AECN. We will measure, analyze and compare MAECN with other active queue management schemes through simulations.