An Intelligent Self-Organization Scheme for the Internet of Things

The Internet of Things (IoT) is emerging as the major trend in shaping the development of the next generation of information networks. The challenges of the enormous, dynamic, incredibly diverse and high complexity of the IoT urgently require novel self-organization scheme because most of the existing distributed self-organization schemes cannot be directly applied to it. In this paper, we propose an intelligent self-organizing scheme (ISOS) for the IoT inspired by the endocrine regulating mechanism. For each node in the network, an autonomous area is established, where the node can effectively interact with its peers and perform self-control according to its own status and dynamic circumstance in a decentralized infrastructure. By introducing the hormone mechanism as the medium for information transmission and data sharing, the nodes can collaborate with each other and work in a cooperative way. Through adjusting the release procedure of the hormones, the ability to effectively detect service randomly generated can also be guaranteed in the probabilistic partially-working IoT. Simulation results verify the performance of the proposed mechanism that entitles the IoT to the ability of maintaining its status in a globally stable status, while effectively discovering the random service requests in a resource-critical configuration. The ISOS would be of great significance for the practical implementation of the IoT.

[1]  Serbulent Tozlu,et al.  Wi-Fi enabled sensors for internet of things: A practical approach , 2012, IEEE Communications Magazine.

[2]  Lionel Touseau,et al.  Combining heterogeneous service technologies for building an Internet of Things middleware , 2012, Comput. Commun..

[3]  Özgür B. Akan,et al.  A survey on bio-inspired networking , 2010, Comput. Networks.

[4]  S. Woods,et al.  Glucagon regulation of energy metabolism , 2010, Physiology & Behavior.

[5]  Venugopal V. Veeravalli,et al.  Smart Sleeping Policies for Energy Efficient Tracking in Sensor Networks , 2008, IEEE Transactions on Signal Processing.

[6]  Yongsheng Ding,et al.  A bio-inspired emergent system for intelligent Web service composition and management , 2007, Knowl. Based Syst..

[7]  Ganesh K. Venayagamoorthy,et al.  Computational Intelligence in Wireless Sensor Networks: A Survey , 2011, IEEE Communications Surveys & Tutorials.

[8]  Reinhard German,et al.  A rule-based system for programming self-organized sensor and actor networks , 2009, Comput. Networks.

[9]  Azzedine Boukerche,et al.  A Predictive Energy-Efficient Technique to Support Object-Tracking Sensor Networks , 2011, IEEE Transactions on Vehicular Technology.

[10]  Antonio Iera,et al.  The Social Internet of Things (SIoT) - When social networks meet the Internet of Things: Concept, architecture and network characterization , 2012, Comput. Networks.

[11]  Lei Gao,et al.  Macrodynamics Analysis of Migration Behaviors in Large-Scale Mobile Agent Systems for the Future Internet , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[12]  Alexander Gluhak,et al.  A survey on facilities for experimental internet of things research , 2011, IEEE Communications Magazine.

[13]  Mario Gerla,et al.  Phero-trail: a bio-inspired location service for mobile underwater sensor networks , 2008, IEEE Journal on Selected Areas in Communications.

[14]  Luiz F. M. Vieira,et al.  Phero-trail: a bio-inspired location service for mobile underwater sensor networks , 2010, IEEE J. Sel. Areas Commun..

[15]  Vlad Trifa,et al.  Interacting with the SOA-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services , 2010, IEEE Transactions on Services Computing.

[16]  Özgür B. Akan,et al.  Distributed audio sensing with homeostasis-inspired autonomous communication , 2011, Ad Hoc Networks.

[17]  Falko Dressler,et al.  A study of self-organization mechanisms in ad hoc and sensor networks , 2008, Comput. Commun..

[18]  Ganesh K. Venayagamoorthy,et al.  Particle Swarm Optimization in Wireless-Sensor Networks: A Brief Survey , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[19]  Bernhard Sendhoff,et al.  A systems approach to evolutionary multiobjective structural optimization and beyond , 2009, IEEE Computational Intelligence Magazine.

[20]  Wei-Min Shen,et al.  Hormone-inspired adaptive communication and distributed control for CONRO self-reconfigurable robots , 2002, IEEE Trans. Robotics Autom..

[21]  Ganesh K. Venayagamoorthy,et al.  Bio-inspired Algorithms for Autonomous Deployment and Localization of Sensor Nodes , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[22]  Claudio Cobelli,et al.  Multiscale Modeling of Insulin Secretion , 2011, IEEE Transactions on Biomedical Engineering.

[23]  Marimuthu Palaniswami,et al.  Anomaly Detection in Environmental Monitoring Networks [Application Notes] , 2011, IEEE Computational Intelligence Magazine.

[24]  Yifan Hu,et al.  An Immune Cooperative Particle Swarm Optimization Algorithm for Fault-Tolerant Routing Optimization in Heterogeneous Wireless Sensor Networks , 2012 .

[25]  Lida Xu,et al.  The internet of things: a survey , 2014, Information Systems Frontiers.

[26]  马华东 Internet of Things: Objectives and Scientific Challenges , 2011 .

[27]  Juan Manuel Cueva Lovelle,et al.  Modeling architecture for collaborative virtual objects based on services , 2011, J. Netw. Comput. Appl..

[28]  Masayuki Murata,et al.  Energy efficient self-organizing control for wireless sensor networks inspired by calling behavior of frogs , 2012, Comput. Commun..

[29]  Jiming Chen,et al.  Distributed sensor activation algorithm for target tracking with binary sensor networks , 2011, Cluster Computing.

[30]  J.-W. Lee,et al.  Energy-Efficient Coverage of Wireless Sensor Networks Using Ant Colony Optimization With Three Types of Pheromones , 2011, IEEE Transactions on Industrial Informatics.

[31]  Lixia Zhang,et al.  A taxonomy of biologically inspired research in computer networking , 2010, Comput. Networks.

[32]  Camila Helena Souza Oliveira,et al.  An autonomic bio-inspired algorithm for wireless sensor network self-organization and efficient routing , 2012, J. Netw. Comput. Appl..

[33]  Imrich Chlamtac,et al.  Internet of things: Vision, applications and research challenges , 2012, Ad Hoc Networks.

[34]  Lida Xu,et al.  Compressed Sensing Signal and Data Acquisition in Wireless Sensor Networks and Internet of Things , 2013, IEEE Transactions on Industrial Informatics.