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Public-access networks need to handle persistent congestion and overload caused by high bandwidth aggregates that may occur during times of flooding-based DDoS attacks or flash crowds. The often unpredictable nature of these two activities can severely degrade server performance. Legitimate user requests also suffer considerably when traffic from many different sources aggregates inside the network and causes congestion. This paper studies a family of algorithms that "proactively" protect a server from overload by installing rate throttles in a set of upstream routers. Based on an optimal control setting, we propose algorithms that achieve throttling in a distributed and fair manner by taking important performance metrics into consideration, such as minimizing overall load variations. Using ns-2 simulations, we show that our proposed algorithms 1) are highly adaptive by avoiding unnecessary parameter configuration, 2) provide max-min fairness for any number of throttling routers, 3) respond very quickly to network changes, 4) are extremely robust against extrinsic factors beyond the system control, and 5) are stable under given delay bounds. [ABSTRACT FROM PUBLISHER]

AS Path Prepending (ASPP) is a popular method for the inter-AS inbound traffic engineering, which is known to be more difficult than the outbound traffic engineering. Although the ASPP approach has been extensively practised by many ASes, it is surprising that there still lacks a systematic study of this approach and the basic understanding of its effectiveness. In this paper, we introduce the concept, applicability and potential instability problem of the ASPP approach. Some guidelines are given as the first step to study the method to avoid instability problem. Finally, we study the dynamic prepending behavior of ISPs and show a real-world pathologic case of prepending instability based on our measurement study of RouteViews data. [ABSTRACT FROM PUBLISHER]