  Recent trends see a move away from a fixed-resource server-centric datacenter
model to a more adaptable "disaggregated" datacenter model. These disaggregated
datacenters can then dynamically group resources to the specific requirements
of an incoming workload, thereby improving efficiency. To properly utilize
these disaggregated datacenters, workload allocation techniques must examine
the current state of the datacenter and choose resources that not only optimize
the current workload request, but future ones. Since disaggregated datacenters
are severely bottlenecked by the available network resources, our work proposes
a heuristic-based approach called RISA, which significantly reduces the network
usage of workload allocations in disaggregated datacenters. Compared to the
state-of-the-art, RISA reduces the power consumption for optical components by
33% and reduces the average CPU-RAM round-trip latency by 50%. Additionally,
RISA significantly outperforms the state-of-the-art in terms of execution time.
