@article {27, title = {AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers}, journal = {ACM Transactions on Computer Systems (TOCS {\textquoteright}12)}, volume = {30}, year = {2012}, month = {11/2012}, abstract = {

Energy costs for data centers continue to rise, already exceeding $15 billion yearly. Sadly much of this power is\ wasted. Servers are only busy 10-30\% of the time on average, but they are often left on, while idle, utilizing 60\% or more of peak power when in the idle state.

We introduce a dynamic capacity management policy,\ AutoScale, that greatly reduces the number of servers needed in data centers driven by unpredictable, time-varying load, while meeting response time SLAs.\ AutoScale\ scales the data center capacity, adding or removing servers as needed.\ AutoScale\ has two key features: (i) it autonomically maintains just the right amount of spare capacity to handle bursts in the request rate; and (ii) it is robust not just to changes in the request rate of real-world traces, but also\ request size\ and\ server efficiency.

We evaluate our dynamic capacity management approach via implementation on a 38-server multitier data center, serving a web site of the type seen in Facebook or Amazon, with a key-value store workload. We demonstrate that\ AutoScale\ vastly improves upon existing dynamic capacity management policies with respect to meeting SLAs and robustness.

}, keywords = {Data centers, power management, resource provisioning}, doi = {10.1145/2382553.2382556}, url = {http://www3.cs.stonybrook.edu/~anshul/tocs12.pdf}, author = {Anshul Gandhi and Mor Harchol-Balter and Ram Raghunathan 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} }