Optimal fog services placement in SDN IoT network using Random Neural Networks and Cognitive Network Map

TytułOptimal fog services placement in SDN IoT network using Random Neural Networks and Cognitive Network Map
Publication TypeConference Paper
Rok publikacji2020
AutorzyFröhlich P, Gelenbe E
Conference NameThe 19th International Conference on Artificial Intelligence and Soft Computing
Date Published06/2020
PublisherSpringer
Conference LocationZakopane
Słowa kluczoweArtificial Intelligence, Cloud computing, Fog Computing, IoT, Random Neural Network, Reinforcement Learning, SDN
Abstract

Due to massive increase in number of IoT devices and number of cloud based services a crucial task arises of optimally placing (both topologically and resource-wise ) services in the network so that non of the clients will be victimized and receive best possible time of response. Also - there must be a balance not to instantiate a service on every possible machine - which would take too much resources. Task which must be solved is an optimization of parameters such as QoS between service and client, equality of clients and usage of resources. Using SDN - which is designed to answer some of the problems posed in this section such as QoS and knowledge about topology of the whole network and newly connected clients - is a gateway to better fit service management. Machine learning provides less stiff rules to follow and more intelligent behaviour of the manager.

Refereed DesignationUnknown

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Data aktualizacji: 04/05/2020 - 15:08; autor zmian: Piotr Fröhlich (pfrohlich@iitis.pl)