TY - GEN
T1 - How to Wake up Your Neighbors
T2 - 36th International Symposium on Distributed Computing, DISC 2022
AU - Dani, Varsha
AU - Hayes, Thomas P.
N1 - Publisher Copyright:
© Varsha Dani and Thomas P. Hayes.
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Recent work [7, 8, 11] has shown that it is sometimes feasible to significantly reduce the energy usage of some radio-network algorithms by adaptively powering down the radio receiver when it is not needed. Although past work has focused on modifying specific network algorithms in this way, we now ask the question of whether this problem can be solved in a generic way, treating the algorithm as a kind of black box. We are able to answer this question in the affirmative, presenting a new general way to modify arbitrary radio-network algorithms in an attempt to save energy. At the expense of a small increase in the time complexity, we can provably reduce the energy usage to an extent that is provably nearly optimal within a certain class of general-purpose algorithms. As an application, we show that our algorithm reduces the energy cost of breadth-first search in radio networks from the previous best bound of 2O(√log n) to polylog(n), where n is the number of nodes in the network A key ingredient in our algorithm is hierarchical clustering based on additive Voronoi decomposition done at multiple scales. Similar clustering algorithms have been used in other recent work on energy-aware computation in radio networks, but we believe the specific approach presented here may be of independent interest.
AB - Recent work [7, 8, 11] has shown that it is sometimes feasible to significantly reduce the energy usage of some radio-network algorithms by adaptively powering down the radio receiver when it is not needed. Although past work has focused on modifying specific network algorithms in this way, we now ask the question of whether this problem can be solved in a generic way, treating the algorithm as a kind of black box. We are able to answer this question in the affirmative, presenting a new general way to modify arbitrary radio-network algorithms in an attempt to save energy. At the expense of a small increase in the time complexity, we can provably reduce the energy usage to an extent that is provably nearly optimal within a certain class of general-purpose algorithms. As an application, we show that our algorithm reduces the energy cost of breadth-first search in radio networks from the previous best bound of 2O(√log n) to polylog(n), where n is the number of nodes in the network A key ingredient in our algorithm is hierarchical clustering based on additive Voronoi decomposition done at multiple scales. Similar clustering algorithms have been used in other recent work on energy-aware computation in radio networks, but we believe the specific approach presented here may be of independent interest.
KW - Clustering
KW - Low Energy Computation
KW - Radio Networks
UR - https://www.scopus.com/pages/publications/85140902329
U2 - 10.4230/LIPIcs.DISC.2022.16
DO - 10.4230/LIPIcs.DISC.2022.16
M3 - Conference contribution
AN - SCOPUS:85140902329
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 36th International Symposium on Distributed Computing, DISC 2022
A2 - Scheideler, Christian
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Y2 - 25 October 2022 through 27 October 2022
ER -