TY - GEN
T1 - Brief Announcement
T2 - 40th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, PODC 2021
AU - Dani, Varsha
AU - Gupta, Aayush
AU - Hayes, Thomas P.
AU - Pettie, Seth
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/7/23
Y1 - 2021/7/23
N2 - We consider networks of small, autonomous devices that communicate with each other wirelessly. Minimizing energy usage is an important consideration in designing algorithms for such networks, as battery life is a crucial and limited resource. Working in a model where both sending and listening for messages deplete energy, we consider the problem of finding a maximal matching of the nodes in a radio network of arbitrary and unknown topology. We present a distributed randomized algorithm that produces, with high probability, a maximal matching. The maximum energy cost per node is O(log2 n), and the time complexity is O(Δlog(n)). Here n is any upper bound on the number of nodes, and Δis any upper bound on the maximum degree; n and Δare parameters of our algorithm that we assume are known a priori to all the processors. We note that there exist families of graphs for which our bounds on energy cost and time complexity are simultaneously optimal up to polylog factors, so any significant improvement would need additional assumptions about the network topology. We also consider the related problem of assigning, for each node in the network, a neighbor to back up its data in case of eventual node failure. Here, a key goal is to minimize the maximum load, defined as the number of nodes assigned to a single node. We present an efficient decentralized low-energy algorithm that finds a neighbor assignment whose maximum load is at most a polylog(n) factor bigger that the optimum.
AB - We consider networks of small, autonomous devices that communicate with each other wirelessly. Minimizing energy usage is an important consideration in designing algorithms for such networks, as battery life is a crucial and limited resource. Working in a model where both sending and listening for messages deplete energy, we consider the problem of finding a maximal matching of the nodes in a radio network of arbitrary and unknown topology. We present a distributed randomized algorithm that produces, with high probability, a maximal matching. The maximum energy cost per node is O(log2 n), and the time complexity is O(Δlog(n)). Here n is any upper bound on the number of nodes, and Δis any upper bound on the maximum degree; n and Δare parameters of our algorithm that we assume are known a priori to all the processors. We note that there exist families of graphs for which our bounds on energy cost and time complexity are simultaneously optimal up to polylog factors, so any significant improvement would need additional assumptions about the network topology. We also consider the related problem of assigning, for each node in the network, a neighbor to back up its data in case of eventual node failure. Here, a key goal is to minimize the maximum load, defined as the number of nodes assigned to a single node. We present an efficient decentralized low-energy algorithm that finds a neighbor assignment whose maximum load is at most a polylog(n) factor bigger that the optimum.
KW - distributed algorithms
KW - energy-aware computation
KW - maximal matching
KW - radio networks
KW - sensor networks
UR - https://www.scopus.com/pages/publications/85112361720
U2 - 10.1145/3465084.3467950
DO - 10.1145/3465084.3467950
M3 - Conference contribution
AN - SCOPUS:85112361720
T3 - Proceedings of the Annual ACM Symposium on Principles of Distributed Computing
SP - 151
EP - 153
BT - PODC 2021 - Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing
PB - Association for Computing Machinery
Y2 - 26 July 2021 through 30 July 2021
ER -