Abstract
An ambient network provides a homogeneous environment to the mobile node amidst the heterogeneity, which arises from the connections to various clusters over its lifespan. When a mobile node in an ambient network changes its location or communication pattern, these changes force the mobile node to join a new cluster. Therefore, we have extended the molecular self-assembly for the ambient network to search for the best set of clusters to seize all the nodes. An internal-view of a molecular system depicts all its molecules and their relationships as holding together due to the equilibrium between the attraction and repulsion forces among its molecules. Here we have analogized the nodes within the ambient network as molecules where these nodes are also governed by special-forces (relations) to configure a connected topology. In this paper, we have defined three forces, which are the physical distance, incoming traffic and outgoing traffic with respect to the pair-wise relations between the node-to-node (at micro-level of a cluster in an ambient network), to act as attraction and repulsion among nodes and forming clusters in a self-organized manner. The ambient network topology problem is formulated as an optimization problem to find suitable clusters of nodes with an objective to reduce the backbone traffic where a cluster assembles the strongly attracted nodes together with respect to all three forces. The simulation results show that our proposed molecular assembly (MA) algorithm embedded on each node coordinates the clustering and our algorithm leads in reducing the backbone traffic up to 20% under the influence of an individual force and up to 10% with the forces applied together when compared to our previous network redesign algorithm with genetic algorithm (GA), which offered reduction in backbone traffic up to 3% as an optimization tool. The robustness of the proposed algorithm is tested by varying the network sizes with 25 and 50 nodes and the convergence rate of MA, which is faster in comparison with GA.
Similar content being viewed by others
References
Abbasi A, Younis M (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30:2826–2841
Calvo RA, Miozo M, Eisl J, Hollos D, Hepworth E, Badia L (2006) Routing Groups in Ambient Networking. In: ACM Proceedings of the 3rd international conference on Mobile Technology, Applications and Systems, October 25–27, Bangkok, Thailand
Carlson JM, Doyle J (1999) Highly optimized tolerance: a mechanism for power laws in designed systems. Phys Rev E 60(2):1412–1427
Dressler F (2005) Efficient and scalable communication in autonomous networking using bio-inspired mechanisms. Informatica 29:183–188
Gershenson C, Heylighen F (2003) When can we call a system self-organizing? Advances in artificial life. In: Proceedings of 7th European Conference on Artificial Life, September 14–17, Dortmund, Germany, LNAI 2801, Springer, pp 606–614
Gross T (2010) Towards a new human-centered computing methodology for cooperative ambient intelligence. J Ambient Intell Humaniz Comput 1:31–42
Habib S, Marimuthu PN, Taha M (2009) Network consolidation through soft computing. In: Proceedings of the Eighteenth International Symposium on Methodologies for Intelligent Systems (ISMIS’09), September 14–17, Prague, Czech Republic
Habib S, Marimuthu PN, Taha M (2010) Self-organization in ambient networks through molecular assembly. In: Proceedings of the International Conference on Ambient Systems, Networks, and Technologies, (ANT 2010), November 8–10, Paris, France
Heylighen F (2002) The science of self-organization and adaptivity. In: Knowledge management, organizational intelligence and learning and complexity, the encyclopedia of life support systems, EOLSS publishers Co. Ltd
Heylighen F, Gershenson G (2003) The meaning of self-organization in computing. In: IEEE Intelligent Systems, Section Trends and Controversies, Self-organization and Information Systems, pp 72–75
Jain AK, Dubes RC (1988) Algorithms for clustering data. Prentice Hall, Englewood Cliffs
Kruger B, Dressler F (2005) Molecular processes as a basis for autonomous networking. IPSI Trans Adv Res Issues Comput Sci Eng 1(1):43–50
Meisel M, Pappas V, Zhang L (2010) A taxonomy of biologically inspired research in computer networking. Int J Comput Telecommun Netw 54:901–916
Michalewicz Z (1994) Genetic algorithms + data structures = evolution programs, Springer
Niebert N, Prytz M, Schieder A, Papadoglou L, Eggert F (2005) Ambient networks: a future wireless internetworking. In: Proceedings of 61st IEEE Vehicular Technology Conference May 30–June 1, Stockholm, Sweden
Regina F, Serugendo GDM, Serbanuta TF (2010) Ambient intelligence in self-organizing assembly systems using the chemical reaction model. J Ambient Intell Humaniz Comput 1:163–184
Rosvall M, Sneppen K (2006) Self-assembly of information in networks. Eur Phys Lett 74(6):1109–1115
SashiRekha K, Nagalakshmi V, Selvam D (2010) Resource management in ambient network using network processor. Int J Comput Appl (0975–8887) 1(16):122–130
Tapia DI, Abraham A, Corchado JM, Alonso RS (2010) Agents and ambient intelligence: case studies. J Ambient Intell Humaniz Comput 1:85–93
Wakamiya N, Hyodo K, and Masayuki M (2008) Reaction-diffusion based topology self-organization for periodic data gathering in wireless sensor networks. In: Proceedings of the Second International Conference on Self-Adaptive and Self-Organizing Systems, October 20–24, Italy
Wang M, Suda T (2003) The bio-networking architecture: a biologically inspired approach to the design of scalable, adaptive, and survivable/available network applications. In: Proceedings of Symposium on Applications and Internet (SAINT) 2001, 8–12 January 2001, San Diego, CA, USA, pp 43–53
Wokoma I, Sacks L, Marshall I (2002) Biologically inspired models for sensor network design. In: Proceedings of London Communications Symposium, September 9–10, University College, London, UK
Acknowledgments
This work was supported by Kuwait University, Research Grant No. EO02/06.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Habib, S.J., Marimuthu, P.N. Self-organization in ambient networks through molecular assembly. J Ambient Intell Human Comput 2, 165–173 (2011). https://doi.org/10.1007/s12652-011-0054-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-011-0054-2