Distributed graph coloring in wireless ad hoc networks: A light-weight algorithm based on Japanese tree frogs' calling behaviour

Graph coloring concerns the problem of assigning colors to the nodes of a graph such that adjacent nodes do not share the same color. In this paper we deal with the problem of finding valid colorings of graphs in a distributed manner, while minimizing the number of used colors. This problem is at the heart of several problems arising in wireless ad hoc networks. Examples are TDMA slot assignment, wakeup scheduling, and data collection. The proposed algorithm is inspired by the de-synchronization that can be observed in the calling behaviour of male Japanese tree frogs. Experimental results show that our algorithm is very competitive with current state-of-the-art approaches.

[1]  Huang Lee,et al.  Wakeup scheduling in wireless sensor networks , 2006, MobiHoc '06.

[2]  Sébastien Tixeuil,et al.  A Distributed TDMA Slot Assignment Algorithm for Wireless Sensor Networks , 2004, ALGOSENSORS.

[3]  Sof Anthony Lee Firefly inspired distributed graph coloring algorithms , 2008, PDPTA.

[4]  M. Murata,et al.  Frog call-inspired self-organizing anti-phase synchronization for wireless sensor networks , 2009, 2009 2nd International Workshop on Nonlinear Dynamics and Synchronization.

[5]  Injong Rhee,et al.  DRAND: Distributed Randomized TDMA Scheduling for Wireless Ad Hoc Networks , 2009, IEEE Trans. Mob. Comput..

[6]  Roie Zivan Anytime Local Search for Distributed Constraint Optimization , 2008, AAAI.

[7]  Raymond Lister,et al.  Experiments in the dynamics of phase coupled oscillators when applied to graph colouring , 2008, ACSC.

[8]  Christian Lavault,et al.  A distributed algorithm for constructing a minimum diameter spanning tree , 2004, J. Parallel Distributed Comput..

[9]  Saewoong Bahk,et al.  Energy efficient transmission scheduling for infrastructure sensor nodes in location systems , 2010, Comput. Networks.

[10]  K. Wells The social behaviour of anuran amphibians , 1977, Animal Behaviour.

[11]  Seif Haridi,et al.  Distributed Algorithms , 1992, Lecture Notes in Computer Science.

[12]  Christian Blum,et al.  Swarm Intelligence: Introduction and Applications , 2008, Swarm Intelligence.

[13]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[14]  Qi Han,et al.  A data collection protocol for real-time sensor applications , 2009, Pervasive Mob. Comput..

[15]  Sof Anthony Lee,et al.  k-Phase Oscillator Synchronization for Graph Coloring , 2010, Math. Comput. Sci..

[16]  Alessandro Panconesi,et al.  An Experimental Analysis of Simple, Distributed Vertex Coloring Algorithms , 2002, SODA '02.

[17]  Richard M. Karp,et al.  Reducibility Among Combinatorial Problems , 1972, 50 Years of Integer Programming.

[18]  Ikkyu Aihara,et al.  Modeling synchronized calling behavior of Japanese tree frogs. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Kazuyuki Aihara,et al.  Mathematical modeling of frogs’ calling behavior and its possible application to artificial life and robotics , 2008, Artificial Life and Robotics.