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Energy Consumption of Group Search on a Line

Authors Jurek Czyzowicz, Konstantinos Georgiou, Ryan Killick, Evangelos Kranakis, Danny Krizanc, Manuel Lafond, Lata Narayanan, Jaroslav Opatrny, Sunil Shende



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Author Details

Jurek Czyzowicz
  • Université du Québec en Outaouais, Gatineau, Québec, Canada
Konstantinos Georgiou
  • Department of Mathematics, Ryerson University, Toronto, Ontario, Canada
Ryan Killick
  • School of Computer Science, Carleton University, Ottawa, Ontario, Canada
Evangelos Kranakis
  • School of Computer Science, Carleton University, Ottawa, Ontario, Canada
Danny Krizanc
  • Department of Mathematics & Comp. Sci., Wesleyan University, Middletown, CT, USA
Manuel Lafond
  • Department of Computer Science, Université de Sherbrooke, Sherbrooke, Québec, Canada
Lata Narayanan
  • Department of Comp. Sci. and Software Eng., Concordia University, Montreal, Québec, Canada
Jaroslav Opatrny
  • Department of Comp. Sci. and Software Eng., Concordia University, Montreal, Québec, Canada
Sunil Shende
  • Department of Computer Science, Rutgers University, Camden, NJ, USA

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Jurek Czyzowicz, Konstantinos Georgiou, Ryan Killick, Evangelos Kranakis, Danny Krizanc, Manuel Lafond, Lata Narayanan, Jaroslav Opatrny, and Sunil Shende. Energy Consumption of Group Search on a Line. In 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 132, pp. 137:1-137:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.ICALP.2019.137

Abstract

Consider two robots that start at the origin of the infinite line in search of an exit at an unknown location on the line. The robots can collaborate in the search, but can only communicate if they arrive at the same location at exactly the same time, i.e. they use the so-called face-to-face communication model. The group search time is defined as the worst-case time as a function of d, the distance of the exit from the origin, when both robots can reach the exit. It has long been known that for a single robot traveling at unit speed, the search time is at least 9d - o(d); a simple doubling strategy achieves this time bound. It was shown recently in [Chrobak et al., 2015] that k >= 2 robots traveling at unit speed also require at least 9d group search time. We investigate energy-time trade-offs in group search by two robots, where the energy loss experienced by a robot traveling a distance x at constant speed s is given by s^2 x, as motivated by energy consumption models in physics and engineering. Specifically, we consider the problem of minimizing the total energy used by the robots, under the constraints that the search time is at most a multiple c of the distance d and the speed of the robots is bounded by b. Motivation for this study is that for the case when robots must complete the search in 9d time with maximum speed one (b=1; c=9), a single robot requires at least 9d energy, while for two robots, all previously proposed algorithms consume at least 28d/3 energy. When the robots have bounded memory and can use only a constant number of fixed speeds, we generalize an algorithm described in [Baeza-Yates and Schott, 1995; Chrobak et al., 2015] to obtain a family of algorithms parametrized by pairs of b,c values that can solve the problem for the entire spectrum of these pairs for which the problem is solvable. In particular, for each such pair, we determine optimal (and in some cases nearly optimal) algorithms inducing the lowest possible energy consumption. We also propose a novel search algorithm that simultaneously achieves search time 9d and consumes energy 8.42588d. Our result shows that two robots can search on the line in optimal time 9d while consuming less total energy than a single robot within the same search time. Our algorithm uses robots that have unbounded memory, and a finite number of dynamically computed speeds. It can be generalized for any c, b with cb=9, and consumes energy 8.42588b^2d.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Mobile agents
  • Theory of computation → Online algorithms
Keywords
  • Evacuation
  • Exit
  • Line
  • Face-to-face Communication
  • Robots
  • Search

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