Varsha Dani
ABSTRACT
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(Δ log(n)). Here n is any upper bound on the number of nodes, and Δ is any upper bound on the maximum degree; n and Δ are 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.
Supplemental Material
- Reuven Bar-Yehuda, Oded Goldreich, and Alon Itai. Efficient emulation of single-hop radio network with collision detection on multi-hop radio network with no collision detection. Distributed Computing, 5(2):67--71, 1991.Google Scholar
Digital Library
- Reuven Bar-Yehuda, Oded Goldreich, and Alon Itai. On the time-complexity of broadcast in multi-hop radio networks: An exponential gap between determinism and randomization. Journal of Computer and System Sciences, 45(1):104--126, 1992.Google ScholarCross Ref
- Matthew Barnes, Chris Conway, James Mathews, and DK Arvind. Ens: An energy harvesting wireless sensor network platform. In 2010 Fifth International Conference on Systems and Networks Communications, pages 83--87. IEEE, 2010.Google ScholarDigital Library
- Yi-Jun Chang, Varsha Dani, Thomas P Hayes, Qizheng He, Wenzheng Li, and Seth Pettie. The energy complexity of broadcast. In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing, pages 95--104, 2018.Google ScholarDigital Library
- Yi-Jun Chang, Varsha Dani, Thomas P Hayes, and Seth Pettie. The energy complexity of BFS in radio networks. In Proceedings of the 39th Symposium on Principles of Distributed Computing, pages 273--282, 2020.Google ScholarDigital Library
- Soumyottam Chatterjee, Robert Gmyr, and Gopal Pandurangan. Sleeping is efficient: Mis in o (1)-rounds node-averaged awake complexity. In Proceedings of the 39th Symposium on Principles of Distributed Computing, pages 99--108, 2020.Google ScholarDigital Library
- Andrzej Czygrinow, Michał Hanćkowiak, Edyta Szyma'nska, and Wojciech Wawrzyniak. On the distributed complexity of the semi-matching problem. Journal of Computer and System Sciences, 82(8):1251--1267, 2016.Google ScholarDigital Library
- Ran Duan and Seth Pettie. Linear-time approximation for maximum weight matching. Journal of the ACM (JACM), 61(1):1--23, 2014.Google Scholar
- Nicholas JA Harvey, Richard E Ladner, László Lovász, and Tami Tamir. Semi-matchings for bipartite graphs and load balancing. Journal of Algorithms, 59(1):53--78, 2006.Google ScholarDigital Library
- Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan. Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual Hawaii international conference on system sciences, pages 10--pp. IEEE, 2000.Google ScholarCross Ref
- Dénes König. Über graphen und ihre anwendung auf determinantentheorie und mengenlehre. Mathematische Annalen, 77(4):453--465, 1916.Google ScholarCross Ref
- Thomas Moscibroda and Rogert Wattenhofer. Maximal independent sets in radio networks. In Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing, pages 148--157, 2005.Google ScholarDigital Library
- Joseph Polastre, Robert Szewczyk, and David Culler. Telos: Enabling ultra-low power wireless research. In IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005., pages 364--369. IEEE, 2005.Google ScholarCross Ref
- Xiumei Wang, Xiaoxin Song, and Jinjiang Yuan. On matching cover of graphs. Mathematical Programming, 147(1):499--518, 2014.Google ScholarDigital Library
Index Terms
- Brief Announcement: Wake Up and Join Me! An Energy Efficient Algorithm for Maximal Matching in Radio Networks
Recommendations
Wake up and join me! An energy-efficient algorithm for maximal matching in radio networks
AbstractWe 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. ...
Brief Announcement: Broadcast in Radio Networks, Time vs. Energy Tradeoffs
PODC '18: Proceedings of the 2018 ACM Symposium on Principles of Distributed ComputingIn wireless networks, consisting of battery-powered devices, energy is a costly resource and most of it is spent on transmitting messages. Broadcast is a problem where a message needs to be transmitted from one node to all other nodes of the network. We ...
Radio-Triggered Wake-Up for Wireless Sensor Networks
Power management is an important technique to prolong the lifespan of sensor networks. Many power management protocols employ wake-up/sleep schedules, which are often complicated and inefficient. We present power management schemes that eliminate such ...
Comments