Software Defined Networking (SDN) has recently emerged as a new network management platform. The centralized control architecture presents many new opportunities. Among the network management tasks, measurement is one of the most important and challenging one. Researchers have proposed many solutions to better utilize SDN for network measurement. Among them, how to detect Distributed Denial-of-Services (DDoS) quickly and precisely is a very challenging problem. In this paper, we propose methods to detect DDoS attacks leveraging on SDN's flow monitoring capability. Our methods utilize measurement resources available in the whole SDN network to adaptively balance the coverage and granularity of attack detection. Through simulations we demonstrate that our methods can quickly locate potential DDoS victims and attackers by using a constrained number of flow monitoring rules.

Video telephony is increasingly being adopted by end consumers. It is extremely challenging to deliver video calls over wireless networks. In this paper, we conduct a measurement study on three popular mobile video call applications: Face-Time, Google Plus Hangout, and Skype, over both WiFi and Cellular links. We study the following questions: 1) how they encode/decode video in realtime under tight resource constraints on mobile devices? 2) how they transmit video smoothly in the face of various wireless network impairments? 3) what is their delivered video conferencing quality under different mobile network conditions? 4) how different system architectures and design choices contribute to their delivered quality? Through detailed analysis of measurement results, we obtain valuable insights regarding the unique challenges, advantages and disadvantages of existing design solutions, and possible directions to deliver high-quality video calls in wireless networks.

Video telephony requires high-bandwidth and low-delay voice and video transmissions between geographically distributed users. It is challenging to deliver high-quality video telephony to end-consumers through the best-effort Internet. In this paper, we present our measurement study on three popular video telephony systems on the Internet: Google+, iChat, and Skype. Through a series of carefully designed active and passive measurements, we uncover important information about their key design choices and performance, including application architecture, video generation and adaptation schemes, loss recovery strategies, end-to-end voice and video delays, resilience against random and bursty losses, etc. The obtained insights can be used to guide the design of applications that call for high-bandwidth and low-delay data transmissions under a wide range of “best-effort” network conditions.

In dynamic streaming, a user can dynamically choose from different versions of the same video. In P2P dynamic streaming, there is one P2P swarm for each version, and within a swarm, peers can share video chunks with each other, thereby reducing the server's bandwidth cost. Due to economy of scale, cooperation among peers can also reduce the per-peer content price. In this paper, we use cooperative game theory to dynamically assign each peer to a version. To maximally incentivize peer cooperation, we use mechanism design to develop pricing schemes that reflect content and bandwidth cost savings derived from peer cooperation. With this approach, each peer is assigned to a swarm that is commensurate with its upload contribution and the price it is willing to pay. We also develop and simulate a distributed dynamic P2P streaming algorithm, consisting of chunk scheduling, token-based accounting, and video version switching, to dynamically adjust each peer's video version based on the collaborative behaviors of all peers.

Adaptive streaming, such as Dynamic Adaptive Streaming over HTTP (DASH), has been widely deployed to provide uninterrupted video streaming service to users with dynamic network conditions. In this paper, we analytically study the potential of using P2P in conjunction with adaptive streaming. We first study the capacity of P2P adaptive streaming by developing utility maximization models that take into account peer heterogeneity, taxation-based incentives, multi-version videos at discrete rates. We further develop stochastic models to study the performance of P2P adaptive streaming in face of bandwidth variations and peer churn. Through analysis and simulations, we demonstrate that incentive-compatible video sharing between peers can be easily achieved with simple video coding and distribution designs. P2P adaptive streaming not only significantly reduces the load on the servers, but also improves the stability of user-perceived video quality in the face of dynamic bandwidth changes.

Video-conferencing has recently gained its momentum and is widely adopted by end-consumers. But there have been very few studies on the network impacts of video calls and the user Quality-of-Experience (QoE) under different network conditions. In this paper, we study the rate control and video quality of Skype video call, and analyze the network impacts in large-scale networks. We first measure the behaviors of Skype video call on a controlled network testbed. By varying packet loss rate, propagation delay and available network bandwidth, we observe how Skype adjusts its sending rate, FEC redundancy, video rate and frame rate. It is found that Skype is robust against mild packet losses and propagation delays, and can efficiently utilize the available network bandwidth. We also find that it employs an overly aggressive FEC protection strategy. Based on the measurement results, we develop rate control model, FEC model, and video quality model for Skype video calls. Extrapolating from the models, we conduct numerical analysis to study the network impacts. We demonstrate that user back-offs upon quality degradation serve as an effective user-level rate control scheme. We also show that Skype video calls are indeed TCP-friendly and respond to congestion quickly when the network is overloaded. Through a case study of a 4G wireless network, we demonstrate that the proposed models can be used in user-QoE-aware network provisioning.

Video telephony requires high-bandwidth and low-delay voice and video transmissions between geographically distributed users. It is challenging to deliver high-quality video telephony to end-consumers through the best-effort Internet. In this paper, we present our measurement study on three popular video telephony systems on the Internet: Google+, iChat, and Skype. Through a series of carefully designed active and passive measurements, we are able to unveil important information about their key design choices and performance, including application architecture, video generation and adaptation schemes, loss recovery strategies, end-to-end voice and video delays, resilience against random and bursty losses, etc. Obtained insights can be used to guide the design of applications that call for high-bandwidth and low-delay data transmissions under a wide range of "best-effort" network conditions.

Video telephony has recently gained its momentum and is widely adopted by end-consumers. But there have been very few studies on the network impacts of video calls and the user Quality-of-Experience (QoE) under different network conditions. In this paper, we study the rate control and video quality of Skype video calls. We first measure the behaviors of Skype video calls on a controlled network testbed. By varying packet loss rate, propagation delay and bandwidth, we observe how Skype adjusts its rates, FEC redundancy and video quality. We find that Skype is robust against mild packet losses and propagation delays, and can efficiently utilize the available network bandwidth. We also find that Skype employs an overly aggressive FEC protection strategy. Based on the measurement results, we develop rate control model, FEC model, and video quality model for Skype. Extrapolating from the models, we conduct numerical analysis to study the network impacts of Skype. We demonstrate that user back-offs upon quality degradation serve as an effective user-level rate control scheme. We also show that Skype video calls are indeed TCP-friendly and respond to congestion quickly when the network is overloaded.