TY - GEN
T1 - SeedTree
T2 - 42nd IEEE International Conference on Computer Communications, INFOCOM 2023
AU - Pourdamghani, Arash
AU - Avin, Chen
AU - Sama, Robert
AU - Schmid, Stefan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - We consider the fundamental problem of designing a self-adjusting tree, which efficiently and locally adapts itself towards the demand it serves (namely accesses to the items stored by the tree nodes), striking a balance between the benefits of such adjustments (enabling faster access) and their costs (reconfigurations). This problem finds applications, among others, in the context of emerging demand-aware and reconfigurable datacenter networks and features connections to self-adjusting data structures. Our main contribution is SeedTree, a dynamically optimal self-adjusting tree which supports local (i.e., greedy) routing, which is particularly attractive under highly dynamic demands. SeedTree relies on an innovative approach which defines a set of unique paths based on randomized item addresses, and uses a small constant number of items per node. We complement our analytical results by showing the benefits of SeedTree empirically, evaluating it on various synthetic and real-world communication traces.
AB - We consider the fundamental problem of designing a self-adjusting tree, which efficiently and locally adapts itself towards the demand it serves (namely accesses to the items stored by the tree nodes), striking a balance between the benefits of such adjustments (enabling faster access) and their costs (reconfigurations). This problem finds applications, among others, in the context of emerging demand-aware and reconfigurable datacenter networks and features connections to self-adjusting data structures. Our main contribution is SeedTree, a dynamically optimal self-adjusting tree which supports local (i.e., greedy) routing, which is particularly attractive under highly dynamic demands. SeedTree relies on an innovative approach which defines a set of unique paths based on randomized item addresses, and uses a small constant number of items per node. We complement our analytical results by showing the benefits of SeedTree empirically, evaluating it on various synthetic and real-world communication traces.
KW - Online algorithms
KW - Reconfigurable datacenters
KW - Self-adjusting data structure
UR - https://www.scopus.com/pages/publications/85171615294
U2 - 10.1109/INFOCOM53939.2023.10228999
DO - 10.1109/INFOCOM53939.2023.10228999
M3 - Conference contribution
AN - SCOPUS:85171615294
T3 - Proceedings - IEEE INFOCOM
BT - INFOCOM 2023 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers
Y2 - 17 May 2023 through 20 May 2023
ER -