Content distribution systems have traditionally adopted one of two architectures: infrastructure-based content delivery networks (CDNs), in which clients download content from dedicated, centrally managed servers, and peer-to-peer CDNs, in which clients download content from each other. The advantages and disadvantages of each architecture have been studied in great detail. Recently, hybrid, or 'peer-assisted', CDNs have emerged, which combine elements from both architectures. The properties of such systems, however, are not as well understood.

In this paper, we study the problem of utility maximization in peer-to-peer (P2P) systems, in which aggregate application-specific utilities are maximized by running distributed algorithms on P2P nodes, which are constrained by their uplink capacities. For certain P2P topologies, we show that routing along a linear number of trees per source can achieve the largest rate region that can be possibly obtained by intrasession and intersession network coding. This observation allows us to develop a simple multitree formulation for the problem. For the resulting nonstrictly concave optimization problem, we develop a Primal-dual distributed algorithm and prove its global convergence using our proposed sufficient conditions. These conditions are general and add understanding to the convergence of primal-dual algorithms under nonstrictly concave settings. We implement the proposed distributed algorithm in a peer-assisted multiparty conferencing system by utilizing only end-to-end delay measurements between P2P nodes. We demonstrate its superior performance through actual experiments on a LAN testbed and the Internet.

We consider multi-rate peer-to-peer multiparty video conferencing applications, where different receivers in the same group can receive videos at different rates using, for example, scalable layered coding. The quality of video received by each receiver can be modeled as a concave utility function of the video bitrate. We study and address the unique challenges introduced by maximizing utility in the multi-rate setting as compared to the single-rate case. We first determine an optimal set of tree structures for routing multi-rate content using scalable layered coding. We then develop Primal and Primal-dual based distributed algorithms to maximize aggregate utility of all receivers in all groups by multi-tree routing and show their convergence. These algorithms can be easily implemented and deployed on today's Internet. We have built a prototype video conferencing system to show that this approach converges to optimal bitrates to improve user experience and offers automatic adaptation to network conditions and user preferences.

Payload attribution can be an important element in network forensics. Given a history of packet transmissions and an excerpt of a possible packet payload, a payload attribution system (PAS) makes it feasible to identify the sources, destinations, and the times of appearance on a network of all the packets that contained the specified payload excerpt. A PAS, as one of the core components in a network forensics system, enables investigating cybercrimes on the Internet by, for example, tracing the spread of worms and viruses, identifying who has received a phishing e-mail in an enterprise, or discovering which insider allowed an unauthorized disclosure of sensitive information. Due to the increasing volume of network traffic in today's networks, it is infeasible to effectively store and query all the actual packets for extended periods of time in order to allow analysis of network events for investigative purposes; therefore, we focus on extremely compressed digests of the packet activity. We propose several new methods for payload attribution, which utilize Rabin fingerprinting, shingling, and winnowing. Our best methods allow building practical payload attribution systems, which provide data reduction ratios greater than 100:1 while supporting efficient queries with very low false positive rates. We demonstrate the properties of the proposed methods and specifically analyze their performance and practicality when used as modules of a network forensics system ForNet. Our experimental results outperform current state-of-the-art methods both in terms of false positives and data reduction ratio. Finally, these approaches directly allow the collected data to be stored and queried by an untrusted party without disclosing any payload information nor the contents of queries.

We consider multi-rate peer-to-peer multi-party conferencing applications, where different receivers in the same group can receive videos at different rates using, for example, scalable layered coding. The quality of video received by each receiver can be modeled as a concave utility function of the video rate. We study and address the unique challenges introduced by multi-rate setting as compared to the single-rate case. We first determine an optimal set of tree structures for routing multi-rate content using scalable layered coding. We then develop primal and primal-dual based distributed algorithms to maximize aggregate utility of all receivers in all groups by multi-tree routing and show their convergence. These algorithms can be easily implemented and deployed on today's Internet. We have built a prototype video conferencing system to show that this approach offers low end-to-end delay, low complexity and high throughput, along with automatic adaptation to network conditions and user preferences.

In this paper, we study the problem of utility maximization in P2P systems, in which aggregate application-specific utilities are maximized by running distributed algorithms on P2P nodes, which are constrained by their uplink capacities. This may be understood as extending Kelly's seminal framework from single-path unicast over general topology to multi-path multicast over P2P topology, with network coding allowed. For certain classes of popular P2P topologies, we show that routing along a linear number of trees per source can achieve the largest rate region that can be possibly obtained by (multi-source) network coding. This simplification result allows us to develop a new multi-tree routing formulation for the problem. Despite of the negative results in literature on applying Primal-dual algorithms to maximize utility under multi-path settings, we have been able to develop a Primal-dual distributed algorithm to maximize the aggregate utility under the multi-path routing environments. Utilizing our proposed sufficient condition, we show global exponential convergence of the Primal-dual algorithm to the optimal solution under different P2P communication scenarios we study. The algorithm can be implemented by utilizing only end-to-end delay measurements between P2P nodes; hence, it can be readily deployed on today's Internet. To support this claim, we have implemented the Primal-dual algorithm for use in a peer-assisted multi-party conferencing system and evaluated its performance through actual experiments on a LAN testbed and the Internet.

Given a history of packet transmissions and an excerpt of a possible packet payload, the payload attribution problem requires the identification of sources, destinations and the times of appearance on a network of all the packets that contained such payload. A module to solve this problem has recently been proposed as the core component in a network forensics system. Network forensics provides useful tools for investigating cybercrimes on the Internet, by, for example, tracing the spread of worms and viruses, identifying who has received a phishing email in an enterprise, or discovering which insider allowed an unauthorized disclosure of sensitive information.