Beeping a maximal independent set

We consider the problem of computing a maximal independent set (MIS) in an extremely harsh broadcast model that relies only on carrier sensing. The model consists of an anonymous broadcast network in which nodes have no knowledge about the topology of the network or even an upper bound on its size. Furthermore, it is assumed that an adversary chooses at which time slot each node wakes up. At each time slot a node can either beep, that is, emit a signal, or be silent. At a particular time slot, beeping nodes receive no feedback, while silent nodes can only differentiate between none of its neighbors beeping, or at least one of its neighbors beeping. We start by proving a lower bound that shows that in this model, it is not possible to locally converge to an MIS in sub-polynomial time. We then study four different relaxations of the model which allow us to circumvent the lower bound and find an MIS in polylogarithmic time. First, we show that if a polynomial upper bound on the network size is known, it is possible to find an MIS in $$\mathcal O (\log ^3 n)$$ time. Second, if we assume sleeping nodes are awoken by neighboring beeps, then we can also find an MIS in $$\mathcal O (\log ^3 n)$$ time. Third, if in addition to this wakeup assumption we allow sender-side collision detection, that is, beeping nodes can distinguish whether at least one neighboring node is beeping concurrently or not, we can find an MIS in $$\mathcal O (\log ^2 n)$$ time. Finally, if instead we endow nodes with synchronous clocks, it is also possible to find an MIS in $$\mathcal O (\log ^2 n)$$ time.

[1]  Roger Wattenhofer,et al.  The price of being near-sighted , 2006, SODA '06.

[2]  Peng-Jun Wan,et al.  Distributed Construction of Connected Dominating Set in Wireless Ad Hoc Networks , 2004, Mob. Networks Appl..

[3]  Christian Scheideler,et al.  An O(log n) dominating set protocol for wireless ad-hoc networks under the physical interference model , 2008, MobiHoc '08.

[4]  Fabian Kuhn,et al.  Deploying Wireless Networks with Beeps , 2010, DISC.

[5]  Michael Luby,et al.  A simple parallel algorithm for the maximal independent set problem , 1985, STOC '85.

[6]  Pankaj K. Agarwal,et al.  Selection in Monotone Matrices and Computing kth Nearest Neighbors , 1994, J. Algorithms.

[7]  Roger Wattenhofer,et al.  What Is the Use of Collision Detection (in Wireless Networks)? , 2010, DISC.

[8]  Roger Wattenhofer,et al.  Efficient computation of maximal independent sets in unstructured multi-hop radio networks , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[9]  David Peleg,et al.  Distributed Computing: A Locality-Sensitive Approach , 1987 .

[10]  P. Maini,et al.  Pattern formation by lateral inhibition with feedback: a mathematical model of delta-notch intercellular signalling. , 1996, Journal of theoretical biology.

[11]  Roger Wattenhofer,et al.  Fast Deterministic Distributed Maximal Independent Set Computation on Growth-Bounded Graphs , 2005, DISC.

[12]  Roger Wattenhofer,et al.  What cannot be computed locally! , 2004, PODC '04.

[13]  PanconesiAlessandro,et al.  On the Complexity of Distributed Network Decomposition , 1996 .

[14]  Radhika Nagpal,et al.  DESYNC: Self-Organizing Desynchronization and TDMA on Wireless Sensor Networks , 2007, International Symposium on Information Processing in Sensor Networks.

[15]  Roger Wattenhofer,et al.  Maximal independent sets in radio networks , 2005, PODC '05.

[16]  Noga Alon,et al.  A Biological Solution to a Fundamental Distributed Computing Problem , 2011, Science.

[17]  Noga Alon,et al.  A Fast and Simple Randomized Parallel Algorithm for the Maximal Independent Set Problem , 1985, J. Algorithms.

[18]  Peng-Jun Wan,et al.  Distributed Construction of Connected Dominating Set in Wireless Ad Hoc Networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[19]  Andrew V. Goldberg,et al.  Network decomposition and locality in distributed computation , 1989, 30th Annual Symposium on Foundations of Computer Science.

[20]  Roger Wattenhofer,et al.  A log-star distributed maximal independent set algorithm for growth-bounded graphs , 2008, PODC '08.

[21]  Leonidas J. Guibas,et al.  Lightweight Coloring and Desynchronization for Networks , 2009, IEEE INFOCOM 2009.

[22]  Andrzej Pelc,et al.  Fast radio broadcasting with advice , 2008, Theor. Comput. Sci..

[23]  Tomasz Jurdzinski,et al.  Probabilistic Algorithms for the Wakeup Problem in Single-Hop Radio Networks , 2002, ISAAC.

[24]  J. Degesys,et al.  DESYNC: Self-Organizing Desynchronization and TDMA on Wireless Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[25]  Aravind Srinivasan,et al.  On the Complexity of Distributed Network Decomposition , 1996, J. Algorithms.

[26]  Roger Wattenhofer,et al.  Slotted programming for sensor networks , 2010, IPSN '10.

[27]  Yves Métivier,et al.  An optimal bit complexity randomized distributed MIS algorithm , 2011, Distributed Computing.

[28]  Wojciech Rytter,et al.  Deterministic broadcasting in unknown radio networks , 2000, SODA '00.