Data Mining - Concepts and Techniques.

At some point in the future, how far out we do not exactly know, wireless access to the Internet will outstrip all other forms of access bringing the freedom of mobility to the way we access the we...

ACM SIGCOMM computer communication review

The success of swarming content delivery has motivated a new approach to live peer-to-peer (P2P) streaming that we call mesh-based streaming. In this approach, participating peers form a random mesh and incorporate swarming content delivery to stream live content. Despite the growing popularity of this approach, neither the design tradeoffs nor the basic performance bottlenecks in mesh-based P2P streaming are well understood. This paper presents PRIME, the first mesh-based P2P streaming for live content that effectively incorporates swarming content delivery. We identify two performance bottlenecks in a mesh-based P2P streaming, namely bandwidth bottleneck and content bottleneck. We derive proper peer connectivity to minimize bandwidth bottleneck as well as an efficient pattern of delivery for live content over a random mesh to minimize content bottleneck. We show that the pattern of delivery can be divided into diffusion and swarming phases and then identify proper packet scheduling algorithm at individual peers. Using ns simulations, we examine key characteristics, design tradeoffs and the relationship between main system parameters.

/pdf/peer-to-peer-receiver-driven-mesh-based-streaming-26v27a8gk4.pdf

Peer-to-Peer Receiver-driven Mesh-based Streaming

Most of the real deployed peer-to-peer streaming systems adopt pull-based streaming protocol. In this paper, we demonstrate that, besides simplicity and robustness, with proper parameter settings, when the server bandwidth is above several times of the raw streaming rate, which is reasonable for practical live streaming system, simple pull-based P2P streaming protocol is nearly optimal in terms of peer upload capacity utilization and system throughput even without intelligent scheduling and bandwidth measurement. We also indicate that whether this near optimality can be achieved depends on the parameters in pull-based protocol, server bandwidth and group size. Then we present our mathematical analysis to gain deeper insight in this characteristic of pull-based streaming protocol. On the other hand, the optimality of pull-based protocol comes from a cost -tradeoff between control overhead and delay, that is, the protocol has either large control overhead or large delay. To break the tradeoff, we propose a pull-push hybrid protocol. The basic idea is to consider pull-based protocol as a highly efficient bandwidth-aware multicast routing protocol and push down packets along the trees formed by pull-based protocol. Both simulation and real-world experiment show that this protocol is not only even more effective in throughput than pull-based protocol but also has far lower delay and much smaller overhead. And to achieve near optimality in peer capacity utilization without churn, the server bandwidth needed can be further relaxed. Furthermore, the proposed protocol is fully implemented in our deployed GridMedia system and has the record to support over 220,000 users simultaneously online.

/pdf/understanding-the-power-of-pull-based-streaming-protocol-can-40pvve0br8.pdf

Understanding the Power of Pull-Based Streaming Protocol: Can We Do Better?

The border gateway protocol (BGP) is the Internet’s default inter-domain routing protocol that manages connectivity among autonomous systems (ASes) Over the past two decades many anomalies of BGP have been identified that threaten its stability and reliability This survey discusses and classifies these anomalies and discusses the 20 most significant techniques used to identify them Our classification is based on the broad category of approach, BGP features used to identify the anomaly, effectiveness in identifying the anomaly and effectiveness in identifying which AS was the location of the event that caused the anomaly We also discuss a number of key requirements for the next generation of BGP anomaly detection techniques

BGP Anomaly Detection Techniques: A Survey

This paper presents design and evaluation of an adaptive streaming mechanism from multiple senders to a single receiver in Peer-to-Peer (P2P) networks, called P2P Adaptive Layered Streaming, or PALS . PALS is a receiver-driven mechanism. It enables a receiver peer to orchestrate quality adaptive streaming of a single, layer encoded video stream from multiple congestion controlled senders, and is able to support a spectrum of non-interactive streaming applications. The primary challenge in design of a multi-source streaming mechanism is that available bandwidth from each peer is not known a priori, and could significantly change during a session. In PALS , the receiver periodically performs quality adaptation based on aggregate bandwidth from all senders to determine (i) overall quality (i.e. number of layers) that can be collectively delivered from all senders, and more importantly (ii) specific subset of packets that should be delivered by each sender in order to gracefully cope with any sudden change in its bandwidth. Our detailed simulation-based evaluations illustrate that PALS can effectively cope with several angles of dynamics in the system including: bandwidth variations, peer participation, and partially available content at different peers. We also demonstrate the importance of coordination among senders and examine key design tradeoffs for the PALS mechanism.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

/pdf/adaptive-multisource-streaming-in-heterogeneous-peer-to-peer-2kadtzi0r7.pdf

Adaptive multisource streaming in heterogeneous peer-to-peer networks

Abnormal BGP events such as attacks, misconfigurations, electricity failures, can cause anomalous or pathological routing behavior at either global level or prefix level, and thus must be detected in their early stages. Instead of using ad hoc methods to analyze BGP data, in this paper we introduce an Internet Routing Forensics framework to systematically process BGP routing data, discover rules of abnormal BGP events, and apply these rules to detect the occurrences of these events. In particular, we leverage data mining techniques to train the framework to learn rules of abnormal BGP events, and our results from two case studies show that these rules are effective. In one case study, rules of worm events discovered from the BGP data during the outbreaks of the CodeRed and Nimda worms were able to successfully detect worm impact on BGP when an independent worm, the Slammer, subsequently occurred. Similarly, in another case study, rules of electricity blackout events obtained using BGP data from the 2003 East Coast blackout were able to detect the BGP impact from the Florida blackout caused by Hurricane Frances in 2004.

/pdf/an-internet-routing-forensics-framework-for-discovering-2ipdi6d4or.pdf

Vikash Agarwal

Papers

Adaptive multisource streaming in heterogeneous peer-to-peer networks

An internet routing forensics framework for discovering rules of abnormal BGP events