For more than a decade, special purpose DNS [1] servers have been used to direct users to different IP addresses based on characteristics such as proximity, load balancing and failover. In this paper, we examine two of the mechanisms these special purpose DNS servers may use to control user traffic:-short time-to-lives (TTL) and time-splicing multiple responses. We find that although 2% of users are still using a stale DNS response after 15 minutes (despite a 20 second TTL), 90% of user requests will have switched to a new answer within 60 seconds. Further, when trying to direct users to two different locations in the ratio 90:10, we find time-splicing CNAME and A responses (corresponding to the two locations, respectively) is incompatible with a commonly deployed recursive resolver, and results in a ratio policy closer to 10:90. Overall we found that although DNS TTLs are not always respected, we are able manage load at a coarse granularity - provided time-spliced responses are of the same response type.

Datacenter networks have been designed to tolerate failures of network equipment and provide sufficient bandwidth. In practice, however, failures and maintenance of networking and power equipment often make tens to thousands of servers unavailable, and network congestion can increase service latency. Unfortunately, there exists an inherent tradeoff between achieving high fault tolerance and reducing bandwidth usage in network core; spreading servers across fault domains improves fault tolerance, but requires additional bandwidth, while deploying servers together reduces bandwidth usage, but also decreases fault tolerance. We present a detailed analysis of a large-scale Web application and its communication patterns. Based on that, we propose and evaluate a novel optimization framework that achieves both high fault tolerance and significantly reduces bandwidth usage in the network core by exploiting the skewness in the observed communication patterns.

In multi-hop wireless networks, longer-hop UDP and especially TCP flows receive a smaller fraction of the available bandwidth than single-hop flows in the absence of specific resource allocation techniques. Also, inter-node interference effects in multi-hop networks lead to incredibly poor bandwidth utilization. This paper begins to address these and other related issues through the novel concept of an investment function which captures the investments (network resources consumed, price paid for service quality, etc.) that are made in packet flows. The investment value of packets or packet flows can then be used to control their treatment in the network, with the goal of providing fair and efficient utilization of network resources through minimizing wasted investment and/or maximizing investment throughput. We show that a simple investment function can significantly improve flow fairness by smoothing out the disparities in distribution of bandwidth among flows with different hop length while simultaneously improving bandwidth utilization efficiency