| This thesis addresses the following question: Is it possible to deliver latency-sensitive applications (LSAs), e.g., streaming audio and video, with satisfactory quality of service (QoS) in large-scale network without compromising scalability and bandwidth efficiency?; We have proposed an innovative distributed control architecture, the Clearing House (CH), and a set of adaptive mechanisms to address these issues. Our design rationale is influenced by discussions with two major U.S. Internet service providers and driven by a realistic model of application-level performance requirements. Towards this end, we focus on Voice-over-IP (VoIP) as an example workload and perform subjective experiments to quantify the impact of packet losses and delays on perceived voice quality. Our results show that packet loss rate should be below 1% and per-hop delay should at most be 5 ms to guarantee high-quality VoIP delivery.; Two key ideas that contribute to the scalability of our CH architecture are: aggregation and hierarchical control. In our model, various basic routing domains are aggregated to form logical domains (LDs), which can then be aggregated to form larger LDs and so forth. This introduces a hierarchical tree of the LDs, and a CH-node is associated with each LD. The processing load and state maintenance required to manage an entire ISP domain are now distributed to various CH-nodes at different levels of granularity.; We have also designed a scalable mechanism, called MDAP (Malicious Flow Detection via Aggregate Policing,) for detecting and policing malicious flows without keeping per-flow state at any edge routers. MDAP aggregates admitted flows for group policing without compromising the ability to identify individual malicious flows when necessary. The key insight behind MDAP is a coordinated way of assigning a unique flow-identifier Fid to every flow based on its ingress and egress point. As a result, the amount of state maintained by edge routers can be reduced from O(n) to O(), where n is the number of admitted flows. We study the performance and robustness of MDAP through ns simulations. Our results show that we can successfully detect a majority (64–83%) of the malicious flows with almost zero false alarms. Packet losses suffered by legitimate flows due to undetected malicious activity are insignificant (0.02–0.9%). The average detection time for correctly identified malicious flows is less than 1/10 of the average flow lifetime. (Abstract shortened by UMI.)... |
