Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 1 Software Engineering Concerns in Observing Autonomic Systems Networks Prof. A. Taleb-Bendiab School of Computing Liverpool John Moores University Software Engineering Concerns in Observing Autonomic Systems Networks Prof. A. Taleb-Bendiab School of Computing Liverpool John Moores University

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 2Outline Much is known about model-based autonomic systems design based on: Much is known about model-based autonomic systems design based on: Feedback control loop, Sensor&Effector, Policy-based management Feedback control loop, Sensor&Effector, Policy-based management Centralised and design-time control and monitoring strategies for autonomic systems, Etc. Centralised and design-time control and monitoring strategies for autonomic systems, Etc. SE techniques exist to handle exhaustive monitoring of a system (e.g. event driven programming, OO design patterns, such as observer/listener registration), Design by contract, etc. Engineering Networks of Autonomic Systems Engineering Networks of Autonomic Systems Are small scale AC systems design models Scalable? Are they applicable to large networks of AC systems If the exhaustive monitoring of a random network of AC is computationally expensive then If the exhaustive monitoring of a random network of AC is computationally expensive then what is the minimal feedback/observation vertices set to enable the monitoring of the whole Networks what is the minimal feedback/observation vertices set to enable the monitoring of the whole Networks Our approach Our approach Algorithm and associated metrics and SE support partial observation of random networks of AC Algorithm and associated metrics and SE support partial observation of random networks of AC Experiment and case-study Experiment and case-study Conclusions, further works and Q&A Conclusions, further works and Q&A

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 3 Large-Scale P2P Self-Organising Overlays Readings Show Example-4 Monitoring & Sensor & Actuator Overlay Network Consumer Service Provider

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 4 Exploiting Topological Self-Organisation In a Scale-Free Network we can monitor “only” high degree nodes (highly connected) In a Scale-Free Network we can monitor “only” high degree nodes (highly connected) Efficient monitoring of nodes is possible without topological knowledge Efficient monitoring of nodes is possible without topological knowledge 17-23% reduction of the number of nodes to be monitored [EASE’07] 17-23% reduction of the number of nodes to be monitored [EASE’07] Approach Approach Random Acquaintance Monitoring method Random Acquaintance Monitoring method Characterise the network via SF signatures including Characterise the network via SF signatures including Hub Connection Density metric Hub Connection Density metric Acquaintance Nomination metric Acquaintance Nomination metric Calculate the acquaintance nomination graph Calculate the acquaintance nomination graph Adapted acquaintance immunisation algorithm [ ] Adapted acquaintance immunisation algorithm [ R Cohen et al ] Selection nominated nodes (often hubs) Selection nominated nodes (often hubs) Establish observer graph (overlay) Establish observer graph (overlay) Deploy typed observer agents. Deploy typed observer agents.

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 5 So Far … Simulation framework Simulation framework Network Characterisation Network Characterisation Such as acquaintance monitoring algorithm, metrics, etc. Such as acquaintance monitoring algorithm, metrics, etc. Meta-language for network governance and observation Meta-language for network governance and observation A method of externalising observation and deployment logic for ease of self-adaptation and evolution A method of externalising observation and deployment logic for ease of self-adaptation and evolution Software design patterns for observer agent generation and deployment Software design patterns for observer agent generation and deployment

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 6 Case-Studies: P2P Network Simulation

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 7 Case-Studies: Salt World Testbed

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 8 Conclusions We argued that AC design model can be used to design large-scale networks of AC systems We argued that AC design model can be used to design large-scale networks of AC systems When we used Random Acquaintance Monitoring method When we used Random Acquaintance Monitoring method As monitoring/feedback of scale-free autonomic networks can be improved by reducing the number of monitored nodes As monitoring/feedback of scale-free autonomic networks can be improved by reducing the number of monitored nodes with near complete network knowledge with near complete network knowledge Further work is required Further work is required To evaluate the method in other case-studies including To evaluate the method in other case-studies including The impact of heterogeneity of monitored AC nodes The impact of heterogeneity of monitored AC nodes reasoning issues. reasoning issues. Extension of the method to other network types including random, regular, etc. Extension of the method to other network types including random, regular, etc. Enhance the software framework. Enhance the software framework.

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 9 That’s the end – so I’m off !

Prof. A. Taleb-Bendiab, Talk: SOAS’07, Contact: Date: 12/09/2015, Slide: 10Acknowledgements Acknowledgements My thanks to the Team Useful Links