Toward Self-Adjusting $k$-Ary Search Tree Networks

Datacenter networks are becoming increasingly flexible with the incorporation of new optical communication technologies, such as optical circuit switches, enabling self-adjusting topologies that can adapt to the traffic pattern in a demand-aware manner. In this paper, we take the first steps toward demand-aware and self-adjusting
$k$
-ary tree networks. These are more powerful generalizations of existing binary search tree networks (like SplayNet [14]), which have been at the core of self-adjusting network (SAN) designs.
$k$
-ary search tree networks are a natural generalization offering nodes of higher degrees, reduced route lengths, and local routing in spite of reconfigurations (due to maintaining the search property). Our main results are algorithms for static
$k$
-ary tree networks and two online heuristics for self-adjusting
$k$
-ary tree networks.