Learning Automata and Agent based Architecture for Processing Data Locallyin Internet of Things
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Abstract
As the Internet of Things (IoT) facilitates the communication among the things/nodes in the network, it created its remarkable place in the current research. The sensors are the main nodes in IoT which generates data continuously and hence huge amount of data is generated in IoT. This paper presents a Learning Automata (LA)and agent based architecture for processing data locally inIoT. As the data being generated in IoT is huge, mostly the data will be offloaded to cloud or any servers which are capable of performing huge and complex computations. But in the case of proposed architecture, the data is made to process locally. The data processing is done by the master M-agent of a particular node and slave m-agent from other nodes. This agent is capable of migrating among different nodes in the network. Learning Automata is used to determine the number of replications of agentis to be done. The cost function is used to test the performance of proposed system. The proposed architecture is proved to be performing effectively when compared to the system without LA..
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