Henry Larkin


 

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Research

  1. Hock Chuan Lim, Rob Stocker, Michael Barlow, Henry Larkin: Interplay of ethical trust and social moral norms: Environment modelling and computational mechanisms in agent-based social simulation (ABSS). Web Intelligence and Agent Systems 9(4): 377-391 (2011)
  2. Norbert Gyorbíró, Henry Larkin, Michael Cohen: Spaced repetition tool for improving long-term memory retention and recall of collected personal experiences. Advances in Computer Entertainment Technology 2010: 124-125
  3. Hock Chuan Lim, Rob Stocker, Michael Barlow, Henry Larkin: Modelling interplay in normative social systems: towards a heuristics formalism of agents and networks. MEDES 2010: 1-8
  4. Norbert Gyorbíró, Henry Larkin, Michael Cohen: Long-term memory retention and recall of collected personal memories. SIGGRAPH Posters 2010
  5. Hock Chuan Lim, Rob Stocker, Michael Barlow, and Henry Larkin (2009). “Experimental study on ethical trust and social moral norms: A serious games- and network-inspired simulation approach.,” in International Simulation and Gaming Association ISAGA, 40th Annual Conference, Singapore.
  6. Marhusin, F., Lokan, C., Henry Larkin, David Cornforth (2009). "Data mining Approach for Detection of Self-Propagating Worm". To appear in Proceedings of the International Conference on Network and System Security (NSS). Gold Coast, Australia.
  7. Rob Stocker, Henry Larkin (2008). “Association in Multi-agent Simulations of Dynamic Random Social Networks”. To appear in Bionetics 2008.
  8. Lim, H., C., Rob Stocker, Henry Larkin (2008). “Ethical Trust and Social Moral Norms Simulation: A bio-inspired agent-based modelling approach”. To appear in IEEE/WIC/ACM International Conference on Intelligent Agent Technology 2008.
  9. Hock Chuan Lim, Rob Stocker, Henry Larkin (2008). “Review of Trust and Machine Ethics Research: Towards a Bio-inspired Computational Model of Ethical Trust (CMET)”. To appear in Bionetics 2008.
  10. Marhusin, F., Henry Larkin, Lokan, C., David Cornforth (2008). “An Evaluation of API calls Tracing Performance: towards an Effective Malware Detection Technique”. To appear in IEEE International Conference on Computational Intelligence and Security 2008.
  11. Marhusin, F., Henry Larkin, David Cornforth (2008). “An Overview of Recent Advances in Intrusion Detection”. 8th IEEE International Conference on Computer and Information Technology University of Technology, Sydney, Australia.
  12. Henry Larkin (2008). “Object Oriented Regular Expressions”. 8th IEEE International Conference on Computer and Information Technology University of Technology, Sydney, Australia.
  13. Marhusin, F., Henry Larkin, David Cornforth (2008). “Malicious Code Detection Architecture Inspired by Human Immune System”. To appear in Springer's Studies in Computation Intelligence (SCI).
  14. Henry Larkin (2007). “Data Representations for Mobile Devices”. 13th IEEE International Conference on Parallel and Distributed Systems (ICPADS’07), Hsinchu, Taiwan.
  15. David Cornforth J., Abbas, H. A., Henry Larkin (2007). “Intelligent Evacuation Models for Fire and Chemical Hazard”. Proceedings of the 2007 Research Network Secure Australia: Security Technology Conference (RNSA’07), Melbourne, Australia.
  16. Henry Larkin (2007). “Word Indexing for Mobile Device Data Representations”. IEEE International Conference on Computer and Information Technology (CIT’07), Aizu-Wakamatsu, Japan.
  17. Henry Larkin (2007). “Applying Concurrent Versioning to Serverless Mobile Device Synchronisation”. IEEE International Conference on Computer and Information Science (ICIS’07), Melbourne, Australia.
  18. Henry Larkin (2006). “Overview of Smart Queries in Databases”. IEEE International Conference on Computer and Information Technology (CIT’06), Seoul, Korea.
  19. Henry Larkin (2006). “Variables and Reversibility in Object Oriented Regular Expressions”. IEEE International Conference on Computer and Information Technology (CIT’06), Seoul, Korea.
  20. Henry Larkin, Zheng da Wu, Warren Toomey. (2005). “Performance of Prediction in Wireless Ad Hoc Routing Algorithms”. Proceedings of The 13th IEEE International Conference on Networks (ICON’05), Kuala Lumpur, Malaysia, pp. 240-243.
  21. Henry Larkin, Zheng da Wu, Warren Toomey. (2005). “Performance of Signal Loss Maps for Wireless Ad hoc Networks”. IFIP International Conference on Embedded And Ubiquitous Computing (EUC'05), Nagasaki, Japan.
  22. Henry Larkin, Zheng da Wu, Warren Toomey. (2005). “Validity of Predicting Connectivity in Wireless Ad hoc Networks”. The International Conference on Mobile Ad-hoc and Sensor Networks (MSN'05), Wuhan, China.
  23. Henry Larkin, Zheng da Wu, Warren Toomey. (2005). “Algorithms for Predicting Node Connectivity in Wireless Ad hoc Networks”. International Conference on Wireless Networks (ICWN'05), Las Vegas, USA.
  24. Henry Larkin, Zheng da Wu, Warren Toomey. (2005). “Predicting Network Topology for Autonomous Wireless Nodes”. European Wireless 2005 (EW'05), Nicosia, Cyprus, VDE-Verlag, pp. 413-417.
  25. Henry Larkin (2004). “Wireless Signal Strength Topology Maps in Mobile Adhoc Networks”. International Conference on Embedded and Ubiquitous Computing (EUC'04), Aizu, Japan, Springer-Verlag, pp. 538-547.
  26. Henry Larkin, Zheng da Wu, Warren Toomey. (2004). “Mapping Wireless Signal Strength for Mobile Adhoc Networks”. Proceedings of the International Conference on Wireless Networks (ICWN'04), Las Vegas, USA, CSREA Press, pp. 151-157.

Other Conference Publications

  1. Mancho, G., Henry Larkin (2008). “A Wiki as an Intercultural Learning Environment for Students of Computer Science in Australia and Spain”. EDEN 2008, Lisbon, Portugal.

Invited Talks

  1. Henry Larkin (2007). "Intelligent Evacuation Models for Fire and Chemical Hazard". Mass Transport, Mass Gathering and Precinct Security 2007 Conference

PhD Summary

The prevalence of wireless networks is on the increase. Society is becoming increasingly reliant on ubiquitous computing, where mobile devices play a key role. The use of wireless networking is a natural solution to providing connectivity for such devices. However, the availability of infrastructure in wireless networks is often limited. Such networks become dependent on wireless ad hoc networking, where nodes communicate and form paths of communication themselves. Wireless ad hoc networks present novel challenges in contrast to fixed infrastructure networks. The unpredictability of node movement and route availability become issues of significant importance where reliability is desired.

To improve reliability in wireless ad hoc networks, predicting future connectivity between mobile devices has been proposed. Predicting connectivity can be employed in a variety of routing protocols to improve route stability and reduce unexpected drop-offs of communication. Previous research in this field has been limited, with few proposals for generating future predictions for mobile nodes. Further work in this field is required to gain a better insight into the effectiveness of various solutions.

This thesis proposes such a solution to increase reliability in wireless ad hoc routing. This research presents two novel concepts to achieve this: the Communication Map (CM), and the Future Neighbours Table (FNT). The CM is a signal loss mapping solution. Signal loss maps delineate wireless signal propagation capabilities over physical space. With such a map, connectivity predictions are based on signal capabilities in the environment in which mobile nodes are deployed. This significantly improves accuracy of predictions in this and in previous research. Without such a map available, connectivity predictions have no knowledge of realistic spatial transmission ranges.

The FNT is a solution to provide routing algorithms with a predicted list of future periods of connectivity between all nodes in an established wireless ad hoc network. The availability of this information allows route selection in routing protocols to be greatly improved, benefiting connectivity. The FNT is generated from future node positional iii information combined with the CM to provide predicted signal loss estimations at future intervals. Given acceptable signal loss values, the FNT is constructed as a list of periods of time in which the signal loss between pairs of nodes will rise above or fall below this acceptable value (predicted connectivity). Future node position information is ideally found in automated networks. Robotic nodes commonly operate where future node task movement is developed and planned into the future, ideal for use in predicted connectivity. Non-automated prediction is also possible, as there exist some situations where travel paths can be predictable, such as mobile users on a train or driving on a highway. Where future node movement is available, predictions of connectivity between nodes are possible.

Detailed analysis of the two proposed concepts are presented in this thesis. Comparisons with existing prediction algorithms illustrate that employing a signal loss map (the CM) vastly improves the accuracy of predictions. The fundamental concepts of the FNT are validated, though in the testing environment the FNT is not shown to be the ideal predicted connectivity architecture for wireless ad hoc networks in comparison to previous work.

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