A Learning Automata Based and Multicast Routing Energy Efficiency Algorithm Using Minimum Spanning Tree For Wireless Sensor Networks

Wireless sensor networks(WSNs) include a lot of small sensor nodes with limited energy. Multicast routing in wireless sensor networks is an appropriate method for sending a same data to several different receivers in the network. In this paper, A multicast routing algorithm based on learning automata is presented for increasing life time in WSNs. Minimum spanning tree (MST) has an important role in communicative networks and it can create a backbone for these networks. In this algorithm, we use local minimum spanning tree(LMST) for sending messages to the multicast message receivers, then, by getting help of learning automata based algorithm, we pay attention to improve the life time for multicast routing problem in these networks. The developed algorithm is evaluated by investigating the relationship between the life time of made LMST with different transmission ranges and different network scales.

[1]  Yazid M. Sharaiha,et al.  A minimum spanning tree approach to line image analysis , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[2]  Anne Lohrli Chapman and Hall , 1985 .

[3]  Vana Kalogeraki,et al.  Real-Time Traffic Management in Sensor Networks , 2006, 2006 27th IEEE International Real-Time Systems Symposium (RTSS'06).

[4]  Ivan Stojmenovic,et al.  Cost-Efficient Multicast Routing in Ad Hoc and Sensor Networks. , 2007 .

[5]  Rolf Floren A Note on "A Faster Approximation Algorithm for the Steiner Problem in Graphs" , 1991, Inf. Process. Lett..

[6]  Anantha Chandrakasan,et al.  Low-power wireless sensor networks , 2001, VLSI Design 2001. Fourteenth International Conference on VLSI Design.

[7]  Kumpati S. Narendra,et al.  On the Behavior of a Learning Automaton in a Changing Environment with Application to Telephone Traffic Routing , 1980, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  B. R. Harita,et al.  Learning automata with changing number of actions , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[9]  Hans Jürgen Prömel,et al.  RNC-Approximation Algorithms for the Steiner Problem , 1997, STACS.

[10]  Akira Miura,et al.  BAM: branch aggregation multicast for wireless sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[11]  Eli Gafni,et al.  Improvements in the time complexity of two message-optimal election algorithms , 1985, PODC '85.

[12]  J. Widmer,et al.  Scalable position-based multicast for mobile ad-hoc networks , 2004 .

[13]  John Moy,et al.  Multicast routing extensions for OSPF , 1994, CACM.

[14]  Mohammad Reza Meybodi,et al.  Utilizing Distributed Learning Automata to Solve Stochastic Shortest Path Problems , 2006, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[15]  M. Thathachar,et al.  Bounds on the Convergence Probabilities of Learning Automata , 1976 .

[16]  Michael Elkin,et al.  Unconditional lower bounds on the time-approximation tradeoffs for the distributed minimum spanning tree problem , 2004, STOC '04.

[17]  Baruch Awerbuch,et al.  Optimal distributed algorithms for minimum weight spanning tree, counting, leader election, and related problems , 1987, STOC.

[18]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[19]  Ivan Stojmenovic,et al.  Position Based Routing Algorithms for Ad Hoc Networks: A Taxonomy , 2004 .

[20]  Philippe Jacquet,et al.  Multicast overlay spanning trees in ad hoc networks: Capacity bounds, protocol design and performance evaluation , 2008, Comput. Commun..

[21]  Srinivasan Parthasarathy,et al.  Mobility control for throughput maximization in ad hoc networks , 2006, Wirel. Commun. Mob. Comput..

[22]  Maleq Khan,et al.  A fast distributed approximation algorithm for minimum spanning trees , 2007, Distributed Computing.

[23]  Jan M. Rabaey,et al.  PicoRadio Supports Ad Hoc Ultra-Low Power Wireless Networking , 2000, Computer.

[24]  Martha Salazar-Neumann The robust minimum spanning tree problem: Compact and convex uncertainty , 2007, Oper. Res. Lett..

[25]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[26]  M. Thathachar,et al.  A Hierarchical System of Learning Automata , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[27]  Ramesh Govindan,et al.  An Overview of Embedded Sensor Networks ISI TR-2004-594 ? , .

[28]  Jörg Widmer,et al.  Position-based multicast routing for mobile Ad-hoc networks , 2003, MOCO.

[29]  F. Hwang,et al.  The Steiner Tree Problem , 2012 .

[30]  Xin Wang,et al.  Tree-structured data regeneration with network coding in distributed storage systems , 2009, 2009 17th International Workshop on Quality of Service.

[31]  Kumpati S. Narendra,et al.  Learning automata - an introduction , 1989 .

[32]  Francis Y. L. Chin,et al.  An almost linear time and O(nlogn+e) Messages distributed algorithm for minimum-weight spanning trees , 1985, 26th Annual Symposium on Foundations of Computer Science (sfcs 1985).

[33]  Lusheng Ji,et al.  Differential destination multicast-a MANET multicast routing protocol for small groups , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[34]  Maleq Khan,et al.  A Fast Distributed Approximation Algorithm for Minimum Spanning Trees , 2006, DISC.

[35]  Ivan Stojmenovic,et al.  Energy-efficient geographic multicast routing for Sensor and Actuator Networks , 2007, Comput. Commun..

[36]  Nael B. Abu-Ghazaleh,et al.  A taxonomy of wireless micro-sensor network models , 2002, MOCO.

[37]  Robert E. Osteen,et al.  Picture Skeletons Based on Eccentricities of Points of Minimum Spanning Trees , 1974, SIAM J. Comput..

[38]  Michael Elkin,et al.  Distributed approximation: a survey , 2004, SIGA.

[39]  Teresa H. Meng,et al.  Minimum energy mobile wireless networks , 1998, ICC '98. 1998 IEEE International Conference on Communications. Conference Record. Affiliated with SUPERCOMM'98 (Cat. No.98CH36220).

[40]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[41]  Pierre A. Humblet,et al.  A Distributed Algorithm for Minimum-Weight Spanning Trees , 1983, TOPL.

[42]  Pedro M. Ruiz,et al.  LEMA: Localized Energy-Efficient Multicast Algorithm based on Geographic Routing , 2006, Proceedings. 2006 31st IEEE Conference on Local Computer Networks.

[43]  Ivan Stojmenovic,et al.  Cost-Efficient Multicast Routing in Ad Hoc and Sensor Networks , 2007, Handbook of Approximation Algorithms and Metaheuristics.

[44]  R. Prim Shortest connection networks and some generalizations , 1957 .

[45]  Seth Pettie,et al.  Randomized minimum spanning tree algorithms using exponentially fewer random bits , 2008, TALG.

[46]  K. Selçuk Candan,et al.  GMP: Distributed Geographic Multicast Routing in Wireless Sensor Networks , 2006, 26th IEEE International Conference on Distributed Computing Systems (ICDCS'06).

[47]  Sung-Ju Lee,et al.  On-demand multicast routing protocol , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[48]  Chien-Hung Liu,et al.  A near-optimal multicast scheme for mobile ad hoc networks using a hybrid genetic algorithm , 2006, 20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06).

[49]  Stephen E. Deering,et al.  Multicast routing in datagram internetworks and extended LANs , 1990, TOCS.

[50]  D. Shier,et al.  Minimum spanning trees in networks with varying edge weights , 2006, Ann. Oper. Res..

[51]  J. Kruskal On the shortest spanning subtree of a graph and the traveling salesman problem , 1956 .