Resource discovery using mobile agents
Conference paper
Singh, M., Cheng, X. and Belavkin, R. 2010. Resource discovery using mobile agents. Frontier of Computer Science and Technology (FCST), 2010 Fifth International Conference. Changchun, Jilin Province 18 - 22 Aug 2010 IEEE. pp. 72 -77 https://doi.org/10.1109/FCST.2010.93
| Type | Conference paper |
|---|---|
| Title | Resource discovery using mobile agents |
| Authors | Singh, M., Cheng, X. and Belavkin, R. |
| Abstract | The peer-to-peer (P2P) system has a number of nodes that are connected to each other in an unstructured or a structured overlay network. One of the most important problems in a P2P system is locating of resources that are shared by various nodes. Techniques such as Flooding and Distributed Hash-Table (DHT) has been proposed to locate resources shared by various nodes. Flooding suffers from saturation as number of nodes increase, while DHT cannot handle multiple keys to define and search a resource. We present the solution that is more efficient and effective for discovering shared resources on a network that is influenced by content shared by nodes. Our solution presents use of multiple agents that manage the shared information on a node and a mobile agent called reconnaissance agent (RA) that is responsible for querying various nodes. To reduce the search load on nodes that have unrelated content, an efficient migration route is proposed for RA that is based on cosine similarity of content shared by nodes and user query. Results show reduction in search load and traffic due to communication, and increase in locating of resources defined by multiple keys using RA that are logically similar to user query. Furthermore, the results indicate that by use of our technique the relevance of search results is higher that is obtained by minimal traffic generation/communication and hops made by RA. |
| Keywords | cosine similarity;distributed hash-table;flooding;mobile agents;peer-to-peer system;reconnaissance agent;resource discovery;shared resources;structured overlay network;mobile agents;peer-to-peer computing; |
| Research Group | Artificial Intelligence group |
| Conference | Frontier of Computer Science and Technology (FCST), 2010 Fifth International Conference |
| Page range | 72 -77 |
| ISBN | |
| Hardcover | 9781424477791 |
| Publisher | IEEE |
| Publication dates | |
| 18 Aug 2010 | |
| Publication process dates | |
| Deposited | 03 Feb 2012 |
| Output status | Published |
| Copyright Statement | Access via IEEE. |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/FCST.2010.93 |
| Scopus EID | 2-s2.0-77957919346 |
| Language | English |
| Book title | Frontier of Computer Science and Technology (FCST), 2010 Fifth International Conference. |
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Belavkin, R. 2015. Asymmetric topologies on statistical manifolds. 2nd International Conference on Geometric Science of Information. Palaiseau, France 28 - 30 Oct 2015 Springer. https://doi.org/10.1007/978-3-319-25040-3_23Numeric characteristics of generalized M-set with its asymptote
Liu, S., Cheng, X., Fu, W., Zhou, Y. and Li, Q. 2014. Numeric characteristics of generalized M-set with its asymptote. Applied Mathematics and Computation. 243, pp. 767-774. https://doi.org/10.1016/j.amc.2014.06.016Local semantic indexing for resource discovery on overlay network using mobile agents
Singh, M., Cheng, X. and Belavkin, R. 2014. Local semantic indexing for resource discovery on overlay network using mobile agents. International Journal of Computational Intelligence Systems. 7 (3), pp. 432-455. https://doi.org/10.1080/18756891.2013.856257Where antibiotic resistance mutations meet quorum-sensing
Krašovec, R., Belavkin, R., Aston, J., Channon, A., Aston, E., Rash, B., Kadirvel, M., Forbes, S. and Knight, C. 2014. Where antibiotic resistance mutations meet quorum-sensing. Microbial Cell. 1 (7), pp. 250-252. https://doi.org/10.15698/mic2014.07.158On variational definition of quantum entropy
Belavkin, R. 2014. On variational definition of quantum entropy. 34th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2014). Clos Lucé, Amboise, France 21 - 26 Sep 2014 American Institute of Physics. https://doi.org/10.1063/1.4905979Asymmetry of risk and value of information
Belavkin, R. 2014. Asymmetry of risk and value of information. in: Vogiatzis, C., Walteros, J. and Pardalos, P. (ed.) Dynamics of Information Systems: Computational and Mathematical Challenges Springer.Mutation rate plasticity in rifampicin resistance depends on Escherichia coli cell–cell interactions
Krašovec, R., Belavkin, R., Aston, J., Channon, A., Aston, E., Rash, B., Kadirvel, M., Forbes, S. and Knight, C. 2014. Mutation rate plasticity in rifampicin resistance depends on Escherichia coli cell–cell interactions. Nature Communications. 5, pp. 1-8. https://doi.org/10.1038/ncomms4742Fractal property of generalized M-set with rational number exponent
Liu, S., Cheng, X., Lan, C., Fu, W., Zhou, J., Li, Q. and Gao, G. 2013. Fractal property of generalized M-set with rational number exponent. Applied Mathematics and Computation. 220, pp. 668-675. https://doi.org/10.1016/j.amc.2013.06.096Mechanical verification of cryptographic protocols
Cheng, X., Ma, X., Huang, S. and Cheng, M. 2010. Mechanical verification of cryptographic protocols. Network Security. https://doi.org/10.1007/978-0-387-73821-5_5DNSsec in Isabelle – replay attack and origin authentication
Kammueller, F., Kirsal-Ever, Y. and Cheng, X. 2013. DNSsec in Isabelle – replay attack and origin authentication. SMC 2013: IEEE International Conference on Systems, Man, and Cybernetics. Manchester, UK 13 - 16 Oct 2013 IEEE. pp. 4772-4777 https://doi.org/10.1109/SMC.2013.812Minimum of information distance criterion for optimal control of mutation rate in evolutionary systems
Belavkin, R. 2013. Minimum of information distance criterion for optimal control of mutation rate in evolutionary systems. in: Accardi, L., Freudenberg, W. and Ohya, M. (ed.) Quantum Bio-Informatics V : Proceedings of the Quantum Bio-Informatics 2011. Tokyo University of Science, Japan, 7 – 12 March 2011 World Scientific.Law of cosines and Shannon-Pythagorean theorem for quantum information
Belavkin, R. 2013. Law of cosines and Shannon-Pythagorean theorem for quantum information. in: Nielsen, F. and Barbaresco, F. (ed.) Geometric Science of Information : First International Conference, GSI 2013, Paris, France, August 28-30, 2013. Proceedings Berlin Springer.Optimal measures and Markov transition kernels
Belavkin, R. 2013. Optimal measures and Markov transition kernels. Journal of Global Optimization. 55 (2), pp. 387-416. https://doi.org/10.1007/s10898-012-9851-1Critical mutation rate has an exponential dependence on population size
Channon, A., Aston, E., Day, C., Belavkin, R. and Knight, C. 2011. Critical mutation rate has an exponential dependence on population size. Lenaerts, T., Giacobini, M., Bersini, H., Bourgine, P., Dorigo, M. and Doursat, R. (ed.) ECAL 2011: The 11th European Conference on Artificial Life. Paris, France 08 - 12 Aug 2011 The MIT Press. pp. 117-124 https://doi.org/10.7551/978-0-262-29714-1-ch021Dynamics of information and optimal control of mutation in evolutionary systems
Belavkin, R. 2012. Dynamics of information and optimal control of mutation in evolutionary systems. in: Sorokin, A., Murphey, R., Thai, M. and Pardalos, P. (ed.) Dynamics of Information Systems: Mathematical Foundations New York Springer.A cooperative particle swarm optimizer with statistical variable interdependence learning
Sun, L., Yoshida, S., Cheng, X. and Liang, Y. 2012. A cooperative particle swarm optimizer with statistical variable interdependence learning. Information Sciences. 186 (1), pp. 20-39. https://doi.org/10.1016/j.ins.2011.09.033Maximal connectivity and constraints in the human brain
Belavkin, R. 2012. Maximal connectivity and constraints in the human brain. in: Pardalos, P., Coleman, T. and Xanthopoulos, P. (ed.) Optimization and data analysis in biomedical informatics New York Springer.On evolution of an information dynamic system and its generating operator
Belavkin, R. 2012. On evolution of an information dynamic system and its generating operator. Optimization Letters. 6 (5), pp. 827-840. https://doi.org/10.1007/s11590-011-0325-zSurvey of grid resource monitoring and prediction strategies.
Hu, L., Cheng, X. and Che, X. 2010. Survey of grid resource monitoring and prediction strategies. International Journal of Intelligent Information Processing. 1 (2).Efficient identity-based broadcast encryption without random oracles.
Hu, L., Liu, Z. and Cheng, X. 2010. Efficient identity-based broadcast encryption without random oracles. Journal of Computers. 5 (3), pp. 331-336.Solving job shop scheduling problem using genetic algorithm with penalty function
Sun, L., Cheng, X. and Liang, Y. 2010. Solving job shop scheduling problem using genetic algorithm with penalty function. International Journal of Intelligent Information Processing. 1 (2), pp. 65-77.Theory and practice of optimal mutation rate control in Hamming spaces of DNA sequences
Belavkin, R., Channon, A., Aston, E., Aston, J. and Knight, C. 2011. Theory and practice of optimal mutation rate control in Hamming spaces of DNA sequences. Lenaerts, T., Giacobini, M., Bersini, H., Bourgine, P., Dorigo, M. and Doursat, R. (ed.) ECAL 2011: The 11th European Conference on Artificial Life. Paris, France 08 - 12 Aug 2011 The MIT Press. pp. 85-92 https://doi.org/10.7551/978-0-262-29714-1-ch017Mutation and optimal search of sequences in nested Hamming spaces
Belavkin, R. 2011. Mutation and optimal search of sequences in nested Hamming spaces. IEEE Information Theory Workshop (ITW). Paraty, Brazil 16 - 20 Oct 2011 IEEE. pp. 90-94 https://doi.org/10.1109/ITW.2011.6089592Conflict resolution and learning probability matching in a neural cell-assembly architecture
Belavkin, R. and Huyck, C. 2011. Conflict resolution and learning probability matching in a neural cell-assembly architecture. Cognitive Systems Research. 12 (2), pp. 93-101. https://doi.org/10.1016/j.cogsys.2010.08.003Towards a theory of decision-making without paradoxes.
Belavkin, R. 2006. Towards a theory of decision-making without paradoxes. Fum, D., Missier, F. and Stocco, A. (ed.) Proceedings of the Seventh International Conference on Cognitive Modeling. Trieste, Italy 05 - 08 Apr 2006 Trieste, Italy Edizioni Goliardiche. pp. 38-43Emergence of rules in cell assemblies of fLIF neurons.
Belavkin, R. and Huyck, C. 2008. Emergence of rules in cell assemblies of fLIF neurons. The 18th European Conference on Artificial Intelligence. University of Patras, Greece 21 - 25 Jul 2008A model of probability matching in a two-choice task based on stochastic control of learning in neural cell-assemblies.
Belavkin, R. and Huyck, C. 2009. A model of probability matching in a two-choice task based on stochastic control of learning in neural cell-assemblies. 9th International conference on cognitive modelling {ICCM 2009]. University of Manchester 24 - 26 Jul 2009Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization
Cheng, X., Che, X. and Hu, L. 2010. Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization. International Journal of Computational Intelligence Systems. 3 (1), pp. 70-83. https://doi.org/10.2991/ijcis.2010.3.1.7Utility and value of information in cognitive science, biology and quantum theory.
Belavkin, R. 2010. Utility and value of information in cognitive science, biology and quantum theory. Accardi, L., Freudenberg, W. and Ohya, M. (ed.) Quantum Bio-Informatics III. Tokyo, Japan 11 - 14 Mar 2009 London World Scientific. pp. 33-47 https://doi.org/10.1142/9789814304061_0004Information trajectory of optimal learning
Belavkin, R. 2010. Information trajectory of optimal learning. in: Hirsch, M., Pardalos, P. and Murphey, R. (ed.) Dynamics of Information Systems: Theory and Applications Springer.Learning behaviour patterns of classroom and distance students using flexible learning resources.
Dimitrova, M., Belavkin, R., Milankovic-Atkinson, M., Sadler, C. and Murphy, A. 2003. Learning behaviour patterns of classroom and distance students using flexible learning resources. in: Lee, K. and Mitchell, K. (ed.) International conference on computers in education 2003: a conference of the Asia-Pacific chapter of the association for the advancement of computing in education (AACE). Hong Kong ICCE.Resource discovery using mobile agents
Singh, M., Cheng, X. and He, X. 2009. Resource discovery using mobile agents. in: Tao, D., Xu, D. and Li, X. (ed.) Semantic Mining Technologies for Multimedia Databases. New York, USA Information Science Reference. pp. 419-448New e-Learning system architecture based on knowledge engineering technology
Li, Y., Chen, Z., Huang, R. and Cheng, X. 2009. New e-Learning system architecture based on knowledge engineering technology. 2009 IEEE International Conference on Systems, Man and Cybernetics. San Antonio, TX, USA 11 - 14 Oct 2009 IEEE. pp. 5140-5144 https://doi.org/10.1109/ICSMC.2009.5346013Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals
Li, Y., Guo, H., Gao, G., Huang, R. and Cheng, X. 2009. Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals. in: Kim, J., Delen, D., Jinsoo, P., Ko, F., Rui, C., Hyung, J., Lee, W. and Kou, G. (ed.) NCM 2009: Fifth International Joint Conference on INC, IMS, and IDC; [proceedings]. IEEE. pp. 1081-1086Bounds of optimal learning
Belavkin, R. 2009. Bounds of optimal learning. 2009 IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning. Nashville, TN, USA 30 Mar - 02 Apr 2009 IEEE. pp. 199-204 https://doi.org/10.1109/ADPRL.2009.4927545Formal verification of the merchant registration phase of the SET protocol.
Cheng, X. and Ma, X. 2005. Formal verification of the merchant registration phase of the SET protocol. International Journal of Automation and Computing. 2 (2), pp. 155-162. https://doi.org/10.1007/s11633-005-0155-5Counting with neurons: rule application with nets of fatiguing leaking integrate and fire neurons.
Huyck, C. and Belavkin, R. 2006. Counting with neurons: rule application with nets of fatiguing leaking integrate and fire neurons. 7th International Conference on Cognitive Modelling. Trieste, Italy pp. 142-147The use of entropy for analysis and control of cognitive models
Belavkin, R. and Ritter, F. 2003. The use of entropy for analysis and control of cognitive models. The Fifth International Conference on Cognitive Modelling. Bamberg, Germany 2003 pp. 21-26Conflict resolution by random estimated costs
Belavkin, R. 2003. Conflict resolution by random estimated costs. 17th European Simulation Multiconference. Nottingham UK pp. 105-110On relation between emotion and entropy
Belavkin, R. 2004. On relation between emotion and entropy. AISB'04 Symposium on Emotion, Cognition and Affective Computing. Leeds UK pp. 1-8OPTIMIST: A new conflict resolution algorithm for ACT-R.
Belavkin, R. and Ritter, F. 2004. OPTIMIST: A new conflict resolution algorithm for ACT-R. Sixth International Conference on Cognitive Modelling. Mahwah, NJ pp. 40-45