Abstract:
The 3D indoor redeployment of connected objects in IoT collection networks is a complex problem that influences the overall performance of the network. In this paper, we ...Show MoreMetadata
Abstract:
The 3D indoor redeployment of connected objects in IoT collection networks is a complex problem that influences the overall performance of the network. In this paper, we aim to resolve this problem using a real prototyping system based on a real-world deployment. The aim is to choose the best positions to add a set of connected objects while optimizing a set of objectives. The used approach is based on a new hybrid optimization algorithm that combines a strategy of incorporation of user preferences (PI-EMO-VF) with a many-objective recent variant of the genetic algorithms (NSGA-III). The obtained numerical results and the real experiments on our testbeds prove the effectiveness of the proposed approach compared with another recent optimization algorithm (MOEA/DD).
Date of Conference: 25-29 June 2018
Date Added to IEEE Xplore: 30 August 2018
ISBN Information:
Electronic ISSN: 2376-6506