Energy Conservation in Datacenters through Cluster Memory Management and Barely-Alive Memory Servers

As a result of current resource provisioning schemes in Internet services, servers end up less than 50% utilized almost all the time. At this level of utilization, the servers’ energy efficiency is less than half their efficiency at peak utilization. A solution to this problem could be consolidating workloads into fewer servers and turning others off. However, services typically resist doing so. A major reason is the fear of slow response times during re-activation in handling traffic spikes. Another reason is that services want to maximize the amount of main memory available for data caching across the server cluster. In this paper, we propose an approach that does not completely shutdown idle servers and allows free memory space to be used for cooperative data caching. Specifically, we make two key contributions. First, we propose to send servers to a new “barely-alive” power state, instead of turning them off after consolidation. Our barely-alive servers allow remote accesses to their main memories even when all processing cores have been turned off. Second, we design a distributed middleware that accommodates barely-alive servers and is capable of dynamically re-sizing the amount of cache space across the cluster to the minimum required to respect the service’s service-level agreement (SLA). Any memory that is not in use by the middleware can be used by applications. Our trace-driven simulations of a server cluster using our middleware and barely-alive servers show very encouraging results.