In the Internet of things (IoT), the activities of daily life are supported by a multitude of heterogeneous, loosely coupled ubiquitous devices. Traditional access control models are not suitable to the nomadic, decentralized and dynamic scenarios in the IoT where identities are not known in advance. This makes the trust management in IoT more promising to address the access control issues .This paper present a Fuzzy approach to the Trust Based Access Control (FTBAC) with the notion of trust levels for identity management. The presented fuzzy approach for trust calculations deals with the linguistic information of devices to address access control in the IoT. The simulation result shows that the fuzzy approach for trust based access control guarantees scalability and it is energy efficient. This paper also proposes FTBAC framework for trust based dynamic access control in distributed IoT. FTBAC framework is a flexible and scalable as increasing number of devices do not affect the functioning and performance.

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Aim of this paper is to present an advanced method to solve Linear programming problem (LPP) in which decision variables, cost coefficients involving in objective function and right hand side coefficients in the constraints are trapezoidal fuzzy numbers. Using multiplication, addition operators of trapezoidal fuzzy numbers (TrFNs) and linear ranking function, Fuzzy Linear programming problem (FLPP) is converted into crisp LPP. Eventually solved it by simplex method and compared results with the results of existing method.

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