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Exponential Separations in the Energy Complexity of Leader Election

27 September 2016
Yi-Jun Chang
T. Kopelowitz
Seth Pettie
Ruosong Wang
Wei Zhan
ArXiv (abs)PDFHTML
Abstract

Energy is often the most constrained resource for battery-powered wireless devices and the lion's share of energy is often spent on transceiver usage (sending/receiving packets), not on computation. In this paper we study the energy complexity of LeaderElection and ApproximateCounting in several models of wireless radio networks. It turns out that energy complexity is very sensitive to whether the devices can generate random bits and their ability to detect collisions. We consider four collision-detection models: Strong-CD (in which transmitters and listeners detect collisions), Sender-CD and Receiver-CD (in which only transmitters or only listeners detect collisions), and No-CD (in which no one detects collisions.) The take-away message of our results is quite surprising. For randomized LeaderElection algorithms, there is an exponential gap between the energy complexity of Sender-CD and Receiver-CD, and for deterministic LeaderElection algorithms there is another exponential gap, but in the reverse direction. In particular, the randomized energy complexity of LeaderElection is Θ(log⁡∗n)\Theta(\log^* n)Θ(log∗n) in Sender-CD but Θ(log⁡(log⁡∗n))\Theta(\log(\log^* n))Θ(log(log∗n)) in Receiver-CD, where nnn is the (unknown) number of devices. Its deterministic complexity is Θ(log⁡N)\Theta(\log N)Θ(logN) in Receiver-CD but Θ(log⁡log⁡N)\Theta(\log\log N)Θ(loglogN) in Sender-CD, where NNN is the (known) size of the devices' ID space. There is a tradeoff between time and energy. We give a new upper bound on the time-energy tradeoff curve for randomized LeaderElection and ApproximateCounting. A critical component of this algorithm is a new deterministic LeaderElection algorithm for dense instances, when n=Θ(N)n=\Theta(N)n=Θ(N), with inverse-Ackermann-type (O(α(N))O(\alpha(N))O(α(N))) energy complexity.

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