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Balancing plays a vital role in cloud data centers to distribute traffic among instances of network functions or services. State-of-the-art load balancers dispatch traffic obliviously without considering the real-time utilization of service instances and therefore can lead to uneven load distribution and sub-optimal performance.In this paper, we design and implement Spotlight, a scalable and distributed load balancing architecture that maintains connection-to-instance mapping consistency at the edge of data center networks. Spotlight uses a new stateful flow dispatcher which periodically polls instances' load and dispatches incoming connections to instances in proportion to their available capacity. Our design utilizes a distributed control plane and in-band flow dispatching; thus, it scales horizontally in data center networks. Through extensive flow-level simulation and packet-level experiments on a testbed with HTTP traffic on unmodified Linux kernel, we demonstrate that compared to existing methods Spotlight distributes traffic more efficiently and has near-optimum performance in terms of overall service utilization. Compared to existing solutions, Spotlight improves aggregated throughput and average flow completion time by at least 20% with infrequent control plane updates. Moreover, we show that Spotlight scales horizontally as it updates the switches at O(100ms) and is resilient to lack of control plane convergence.

The success of Skype has inspired a generation of peer-to-peerbased solutions for real-time multimedia services over the Internet. However, there lacks still a robust metric quantifying the perceptual quality of a Skype call. The widely-used PESQ (Perceptual Evaluation of Speech Quality) falls short of modeling superwideband calls, which are characteristics of SILK -Skype's codec made public in 2011. Towards a robust QoE (Quality of Experience) metric for VoIP call analysis, we propose a model, referred to as WF-Regression model, to capture the call rate and perceptual quality relationship. The model is shown through a user study that it is robust, R-square = 0.9990 and outperform PESQ modeling the quality of Skype calls, error ratio = 3.68% vs. 14.59%.

The effective end-to-end transport of delay-sensitive voice data has long been a problem in multimedia networking. One of the major issues is determining the sending rate of real-time VoIP streams such that the user experience is maximized per unit network resource consumed. A particularly interesting complication that remains to be addressed is that the available bandwidth is often dynamic. Thus, it is unclear whether a marginal increase warrants better user experience. If a user naively tunes the sending rate to the optimum at any given opportunity, the user experience could fluctuate.To investigate the effects of magnitude and frequency of rate changes on user experience, we recruited 127 human participants to systematically score emulated Skype calls with different combinations of rate changes, including varying magnitude and frequency of rate changes. Results show that 1) the rate change frequency affects the user experience on a logarithmic scale, echoing Weber-Fechner's Law [1], 2) the effect of rate change magnitude depends on how users perceive the quality difference, and 3) this study derives a closed-form model of user perception for rate changes for Skype calls.