Learning software agents are able to assist Cloud providers in taking decisions about resource management at any level, as they are able to collect knowledge and improve their performances over time by means of learning strategies. On the other hand Cloud Federations allow providers to share computational infrastructures in order to build a distributed, interoperable multi-cloud context. In this work we present an evolutionary approach based on agent cloning, i.e. a mechanism of agent reproduction allowing providers to substitute an “unsatisfactory” agent acting in a “cloud context” with a clone of an existing agent having a suitable knowledge and a good reputation in the multicloud context. By this approach, cloud agents performances can be improved because they are substituted with agent clones that have shown a better behavior.

Comi, A., Fotia, L., Messina, F., Pappalardo, G., Rosaci, D., Sarne', G. (2015). An evolutionary approach for Cloud learning agents in multi-cloud distributed contexts. In Proceedings - 2015 IEEE 24th International Conference on Enabling Technologies: Infrastructures for Collaborative Enterprises, WETICE 2015 (pp.99-104). Institute of Electrical and Electronics Engineers Inc. [10.1109/WETICE.2015.27].

An evolutionary approach for Cloud learning agents in multi-cloud distributed contexts

SARNE' G
2015

Abstract

Learning software agents are able to assist Cloud providers in taking decisions about resource management at any level, as they are able to collect knowledge and improve their performances over time by means of learning strategies. On the other hand Cloud Federations allow providers to share computational infrastructures in order to build a distributed, interoperable multi-cloud context. In this work we present an evolutionary approach based on agent cloning, i.e. a mechanism of agent reproduction allowing providers to substitute an “unsatisfactory” agent acting in a “cloud context” with a clone of an existing agent having a suitable knowledge and a good reputation in the multicloud context. By this approach, cloud agents performances can be improved because they are substituted with agent clones that have shown a better behavior.
paper
LEARNING AGENTS; CLOUD COMPUTING; CLOUD FEDERATIONS
English
WETICE 2015
15-17 July 2015
Reddy S.M.
Proceedings - 2015 IEEE 24th International Conference on Enabling Technologies: Infrastructures for Collaborative Enterprises, WETICE 2015
978-146737692-1
2015
99
104
7194338
http://dx.doi.org/10.1109/WETICE.2015.27
none
Comi, A., Fotia, L., Messina, F., Pappalardo, G., Rosaci, D., Sarne', G. (2015). An evolutionary approach for Cloud learning agents in multi-cloud distributed contexts. In Proceedings - 2015 IEEE 24th International Conference on Enabling Technologies: Infrastructures for Collaborative Enterprises, WETICE 2015 (pp.99-104). Institute of Electrical and Electronics Engineers Inc. [10.1109/WETICE.2015.27].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/299292
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