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Elitist Simulated Annealing Algorithm for Solving Multi Objective Optimization Problems in Internet of Things Design


Affiliations
1 AVP – IT, Magma Fincorp Limited, India
2 School of Computing and Informatics, "Brain Trust" University of Louisiana at Lafayette, USA, United States
 

Internet of Things (IoT) is going to introduce billions of data collection and computing nodes all over the world in next few years. IoT would be impacting daily life in many ways by virtue of more granular field-level data collection via those nodes and thus delivering faster actions. One of the key challenges in IoT design decision is resource constraintwhich often limits the space, battery capacity, computing power available in each of the nodes. This presents an optimization problem with multiple objectives, with competing objectives. This paper proposes an algorithm based on Simulated annealing. Simulated Annealing is inspired by the physical annealing process which leads to a gradual movement towards a solution set. This paper proposes to use a variant of this mechanism to solve multi-objective optimization problems in IoT space to come out with a set of solutions which are nondominated from each other.

Keywords

Internet of Things, IoT, Simulated Annealing, Multiobjective Optimization Problem.
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  • Elitist Simulated Annealing Algorithm for Solving Multi Objective Optimization Problems in Internet of Things Design

Abstract Views: 133  |  PDF Views: 5

Authors

Subhamoy Chakraborti
AVP – IT, Magma Fincorp Limited, India
Sugata Sanyal
School of Computing and Informatics, "Brain Trust" University of Louisiana at Lafayette, USA, United States

Abstract


Internet of Things (IoT) is going to introduce billions of data collection and computing nodes all over the world in next few years. IoT would be impacting daily life in many ways by virtue of more granular field-level data collection via those nodes and thus delivering faster actions. One of the key challenges in IoT design decision is resource constraintwhich often limits the space, battery capacity, computing power available in each of the nodes. This presents an optimization problem with multiple objectives, with competing objectives. This paper proposes an algorithm based on Simulated annealing. Simulated Annealing is inspired by the physical annealing process which leads to a gradual movement towards a solution set. This paper proposes to use a variant of this mechanism to solve multi-objective optimization problems in IoT space to come out with a set of solutions which are nondominated from each other.

Keywords


Internet of Things, IoT, Simulated Annealing, Multiobjective Optimization Problem.