  We propose in this paper to study the energy-, thermal- and performance-aware
resource management in heterogeneous datacenters. Witnessing the continuous
development of heterogeneity in datacenters, we are confronted with their
different behaviors in terms of performance, power consumption and thermal
dissipation: Indeed, heterogeneity at server level lies both in the computing
infrastructure (computing power, electrical power consumption) and in the heat
removal systems (different enclosure, fans, thermal sinks). Also the physical
locations of the servers become important with heterogeneity since some servers
can (over)heat others. While many studies address independently these
parameters (most of the time performance and power or energy), we show in this
paper the necessity to tackle all these aspects for an optimal resource
management of the computing resources. This leads to improved energy usage in a
heterogeneous datacenter including the cooling of the computer rooms. We build
our approach on the concept of heat distribution matrix to handle the mutual
influence of the servers, in heterogeneous environments, which is novel in this
context. We propose a heuristic to solve the server placement problem and we
design a generic greedy framework for the online scheduling problem. We derive
several single-objective heuristics (for performance, energy, cooling) and a
novel fuzzy-based priority mechanism to handle their tradeoffs. Finally, we
show results using extensive simulations fed with actual measurements on
heterogeneous servers.
