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2. Application of Biological principles towards Autonomic Networks. Autonomic networking focuses onApplying autonomic principles to govern network behaviore.g Self-organisation, Self-Management, Self-ConfigurationOur applications include:Self-Management of network resources at System levelSelf-
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1. Applying Biological Principles towards Self-Governance in Autonomic Networks
2. 2 Application of Biological principles towards Autonomic Networks Autonomic networking focuses on
Applying autonomic principles to govern network behavior
e.g Self-organisation, Self-Management, Self-Configuration
Our applications include:
Self-Management of network resources at System level
Self-Organisation of routes at device level
Combined Biological and Social inspired techniques for Trust Management
Bio-inspired interaction supporting Social Networking
3. 3 Combine different Biological principles
Molecular Biology
Principles cells used to self-organise
Physiological systems used to self-manage
Translate the biological mechanisms to policy based management system
Develop policies for self-regulation
Develop policies to evaluate equilibrium alterations (e.g. link failure) and stabilise equilibrium through Autonomic Element functionality
Develop polices for cooperative self-organisation between Autonomic elements
Overview of Bio-inspired Autonomic Management
4. 4 Biological life cycle Combined these biological mechanisms into a biological life cycle
The lifecycle address three key self-governing mechanisms
Self-organisation
Self-management
Self-learning
Aim is to map this lifecycle to communication systems
5. 5 Mapping of Biological model to Policy Continuum System/Network level – Mapping from Blood Glucose Homeostasis for self-management of resources
Device/Instance – Map from Chemotaxis, Reaction Diffusion, and Hormone signalling for self-organisation of traffic QoS supported paths
6. 6 Multi-layer Bio-inspired Management of Infrastructure Networks
7. 7 Blood Glucose Homeostasis – Self-Management of Resources Blood Glucose Homeostasis under varying intensity of the body is compared to the intensity of bandwidth usage in the network
Glucose is available in other forms: Glycogen, Fat
Glycogen compared to the demand profile and Fat is compared to new or fluctuating traffic
Rules of converting from Glycogen to Fat (and vice versa) is compared to mechanism for maintaining revenue
8. 8 Route Management Hormone signalling is applied for hop count from destination to source
Reaction Diffusion – Diffusion of neighbour load information and reaction is calculation of weight value in each node
Chemotaxis is formation of this chemical gradient along the highest weight to create a path (for each source and destination)
9. 9 Bio-inspired Interaction Supporting Social Networking A crucial challenge in Pervasive computing is the ability to share and disseminate information for human interaction during social networking (e.g. conference meetings)
Self-organisation mechanism that will automatically cluster groups in large conference hall
Two Layer
Context Management Layer
Self-Organisation Layer
10. 10 Self-organisation layer uses Bio-inspired techniques
Chemotaxis for formation of primary and secondary clusters
Quorum Sensing used to mature the cluster as number of devices joining cluster grows
Bio-inspired Interaction Supporting Social Networking
11. 11 Conclusion Autonomic Network Management can benefit from various biological models
Many aspects of networking can rely on autonomic mechanism, and in turn rely on specific biological mechanisms
In our work, we have outlined different biological mechanisms for different types of network applications
The use of Bio-inspired analogies is one form of solution to solve problems
Can lead to hybrid solution
Provides research opportunity for the development of novel communications service applications to support the management of the emerging next generation internet.
12. 12 Published and accepted papers
Sasitharan Balasubramaniam, Keara Barrett, John Strassner, William Donnelly, Sven van der Meer, Bio-inspired Policy Based Management (bioPBM) for Autonomic Communication Systems, Proceedings of 7th IEEE workshop on Policies for Distributed Systems and Networks (Policy 2006), Ontario, Canada, June 2006.
Sasitharan Balasubramaniam, William Donnelly, Dmitri Botvich, Nazim Agoulmine, John Strassner, Towards Integrating Principles of Molecular Biology for Autonomic Network Management, Proceedings of 13th HP Open View University Association Workshop (HP-OVUA), Sophia Antipolis, France, May 2006. (short paper)
Sasitharan Balasubramaniam, Dmitri Botvich, William Donnelly, Nazim Agoulmine, Applying Blood Glucose Homeostatic model towards Self-Management of IP QoS Provisioned Networks, Proceedings of 6th IEEE International Workshop on IP Operations and Management (IPOM 2006), LNCS, Dublin, Ireland, October 2006.
Sasitharan Balasubramaniam, Dmitri Botvich, William Donnelly, Mícheál Ó’Foghlú, John Strassner, Application of Blood Glucose Homeostasis, Chemotaxis, and Hormone signaling towards Self-Governance and Self-Organisation for Autonomic Networks, Proceedings of First International Conference on Bio Inspired models of Networks, Information and Computing Systems (BIONETICS), Cavalese, Italy, December 2006.
Nazim Agoulmine, Sasitharan Balasubramaniam, Dmitri Botvich, John Strassner, Elyes Lehtihet, William Donnelly, Challenges for Autonomic Network Management, Proceedings of 1st conference on Modelling Autonomic Communication Environment (MACE), Dublin, Ireland, October 2006. Publications (1):
13. 13 Sasitharan Balasubramaniam, Dmitri Botvich, Tao Gu, William Donnelly, Chemotaxis and Quorum Sensing Inspired Device Interaction supporting Social Networking, Proceedings of 65th IEEE Vehicular Technology Conference (VTC), Dublin 2007.
Sasitharan Balasubramaniam, Dmitri Botvich, William Donnelly, Mícheál Ó Foghlú, John Strassner, Bio-inspired Framework for Autonomic Communication Systems, in “Advances in biologically inspired information Systems: Models, Methods, and Tools”, Studies in Computational Intelligence, Springer Verlag. Editors Falko Dressler and Iacopo Carreras, 2007.
Jimmy McGibney, Dmitri Botvich, Sasitharan Balasubramaniam, A Combined Biologically and Socially Inspired Approach to Mitigating Ad Hoc Network Threats, Proceedings of 66th IEEE Vehicular Technology Conference (VTC 2007 Fall), Baltimore, USA, September - October 2007.
Sasitharan Balasubramaniam, Dmitri Botvich, William Donnelly, John Strassner, A Biologically Inspired Policy Based Management System for Survivability in Autonomic Networks, Proceedings of 4th International Conference on Broadband Communications, Networks, and Systems (IEEE BROADNETS 2007), Raleigh, North Carolina, USA, September 2007.
Gajaruban Kandavanam, Dmitri Botvich, Sasitharan Balasubramaniam, Ponnuthurai Suganthan, William Donnelly, A Multi-layered solution for supporting ISP traffic demand using Genetic Algorithm, Proceedings of IEEE Congress on Evolutionary Computation, Singapore, September 2007
Publications (2):