@conference {28, title = {Saving Cash by Using Less Cache}, booktitle = {4th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud {\textquoteright}12)}, year = {2012}, abstract = {
Everyone loves a large caching tier in their multi-tier cloud-based web service because it both alleviates\ database load and provides lower request latencies. Even\ when load drops severely, administrators are reluctant to\ scale down their caching tier. This paper makes the case\ that (i) scaling down the caching tier is viable with re-\ spect to performance, and (ii) the savings are potentially\ huge; e.g., a 4x drop in load can result in 90\% savings in\ the caching tier size.
}, url = {http://www3.cs.stonybrook.edu/~anshul/hotcloud_2012.pdf}, author = {Timothy Zhu and Anshul Gandhi and Mor Harchol-Balter and Michael Kozuch} } @conference {23, title = {SOFTScale: Stealing Opportunistically For Transient Scaling}, booktitle = {13th International Middleware Conference (Middleware {\textquoteright}12)}, year = {2012}, abstract = {

Dynamic capacity provisioning is a well studied approach to handling gradual changes in data center load. However, abrupt spikes in load are still problematic in that the work in system rises very quickly during the setup time needed to turn on additional capacity. Performance can be severely affected even if it takes only 5 seconds to bring additional capacity online.

In this paper, we propose SOFTScale, an approach to handling load spikes in multi-tier data centers without having to over-provision resources. SOFTScale works by opportunistically stealing resources from other tiers to alleviate the bottleneck tier, even when the tiers are carefully provisioned at capacity. SOFTScale is especially useful during the transient overload periods when additional capacity is being brought online.

Via implementation on a 28-server multi-tier testbed, we investigate a range of possible load spikes, including an artificial doubling or tripling of load, as well as large spikes in real traces. We find that SOFTScale can meet our stringent response time Service Level Agreement goal of 500ms without using any additional resources even under some extreme load spikes that would normally cause the system (without SOFTScale) to exhibit response times as high as 96 seconds.

}, keywords = {Data centers, load spikes, power management, resource provisioning}, url = {http://www3.cs.stonybrook.edu/~anshul/middleware12.pdf}, author = {Anshul Gandhi and Timothy Zhu and Mor Harchol-Balter and Michael Kozuch} }