Voice over Internet (VoIP) has been experiencing enormous growth in recent years. While posed to replace traditional PSTN for both enterprise and residential customers, VoIP has yet to achieve the same level of quality and reliability as PSTN. One key challenge is that a growing segment of customers is increasingly relying on WiFi connections. VoIP over WiFi (VoWiFi) experiences significant degradation in quality because of packet losses, mostly due to WiFi's low capacity, varying signal strength, interference, etc. To understand this problem, we have developed and deployed a comprehensive measurement platform in a global enterprise network. From large-scale real-world traces, we quantitatively analyze the impact of WiFi connections and study measures to mitigate such impact. Our results confirm that WiFi connections incur significantly more packet losses than wirelines, but these losses can be effectively concealed by sending each packet up to five times (heavy replication). Due to WiFi's inherent overhead, heavy replication only marginally increases WiFi airtime. To avoid the overhead on wirelines, we further propose a relay-based solution, where heavy replication only occurs between endpoints and nearby relays, and is removed before packets are transmitted on inter-branch long haul links or the public Internet. The solution has been implemented and deployed in the global enterprise network, and measurement results confirm that it can indeed greatly improve the performance of VoIP for WiFi users. In particular, it reduces the percentage of poor calls from 35% to 10%; and increases the percentage of acceptable ones from 45% to 70%.

Global enterprises are increasingly adopting unified communication solutions over traditional telephone systems. Such solutions provide integrated audio/video conferencing and messaging services, and enable flexible working environments by allowing mobile and dispersed users to communicate and collaborate easily and efficiently. The ultimate goal of unified communications is to ensure a smooth and best possible user experience across all scenarios. To address this challenge and understand the impact of various network scenarios on unified audio/video conferencing, we have developed a distributed experimental platform - SureCall - and deployed it on over 80 machines across a global enterprise and many residential networks. SureCall has collected worth of more than 6 months of packet-level audio/video conferencing traces. Through in-depth analysis of these traces, we have quantitatively compared how key performance metrics, such as packet loss and jitter, as well as the correlation between them, are affected by the enterprise and residential networks, by WiFi connections and VPN links, etc. In addition, we show how SureCall can serve as an ideal platform to design, experiment and validate new schemes and algorithms. We have developed a new audio quality classifier using the SureCall platform, which is being experimented with the recent release of Office Communicator solution for large-scale validation.

There is a growing need to support real-time applications over the Internet. Real-time interactive applications often have multiple quality-of-service (QoS) requirements which are application specific. Traditional provisioning of QoS in the Internet through IP routing - Intserv or Diffserv - faces many technical challenges, and is also deterred by the huge deployment issues. As an alternative, application providers often build their own application-specific overlay networks to meet their QoS requirements. In this paper, we present a unified framework which can serve diverse applications with multiple QoS constraints. Our scalable flow route management architecture, called MCQoS, employs a hybrid approach using a path vector protocol to disseminate aggregated path information combined with on-demand path discovery to find paths that match the diverse QoS requirements. It uses a distributed algorithm to dynamically adapt to an alternate path when the current path fails to satisfy the required QoS constraints. We do large-scale simulation and analysis to show that our approach is both efficient and scalable, and that it substantially outperforms the state of the art protocols in accuracy. Our simulation results show that MCQoS can reduce the false negative percentage to less than 1% compared with 5-10% in other approaches, and eliminates false positives, whereas other schemes have false positive rates of 10-20% with minimal increase in protocol overhead. Finally, we implemented and deployed our system on the Planetlab testbed for evaluation in a real network environment.

We treat the problem of large-scale TCP poisoning: an attacker, who is able to monitor TCP packet headers in the network, can deny service to all flows traversing the monitoring point simply by injecting a single spoofed data or control packet into each of the flows. One of the entities responsible for this severe vulnerability is certainly the TCP protocol itself: it behaves as a "dummy" state machine that can more-than-easily become desynchronized by an attacker. In this paper, we explore ways for upgrading TCP endpoints into viable DoS-resilient protocol entities, capable of mitigating large-scale poisoning attacks. We show, by means of analytical modeling, simulations, and Internet experiments, how small upgrades implemented by the endpoints can dramatically improve resilience to attacks. The key mechanisms unique to our approach are (i) deferred protocol reaction, used to accurately detect poisoning attacks; (ii) forward nonces, applied to distinguish among different traffic sources during the attack; and (iii) self-clocking-based correlation, utilized for successfully detecting legitimate packet streams. Our solution solely relies on the protocol design, it is incrementally deployable, and TCP friendly.

Short TCP flows may suffer significant response-time performance degradations during network congestion. Unfortunately, this creates an incentive for misbehavior by clients ofinteractiveapplications(e.g., gaming, telnet, Web): to send "dummy" packets into the network at aTCP-fairrate even when they have no data to send, thus improving their performance in moments when they do have data to send. Even though no "law" is violated in this way, a large-scale deployment of such an approach has the potential to seriously jeopardize one of the core Internet's principles -statisticalmultiplexing. We quantify, by means of analytical modeling and simulation, gains achievable by the above misbehavior. Further, we explore techniques that both misbehaving and regular clients can apply to optimize their performance. Our research indicates that easy-to-implement application-level techniques are capable of dramatically reducing incentives for conducting the above transgressions, still without compromising the idea of statistical multiplexing.