Membrane computing technology for self-organization of devices in the internet of things

Aurimas Gedminas

Doctoral dissertation

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In the thesis is analyzed membrane computing, Internet of Things technologies and related metaheuristic algorithms, ant colony optimization algorithms, Internet of Things information management, and distribution algorithms. Membrane computing is a field of computer science in which computational ideas and models are abstracted from the structure of biological cells. The Internet of Things is a set of independent devices that are presented to users as a single sustainable system (structure) for connecting smart tools to sensors and multiple devices to control them or obtain their basic information. In order for the systems to operate continuously and sustainably, it is necessary to solve the problems of self-management data routing in the Internet of Things.

The object of research of this dissertation is the self-organizing Internet of Things network. The aim of the thesis is to offer an original metaheuristic based P system solution by creating and investigating a system for simulating and testing membrane computing in the Internet of Things. The thesis is designed to contribute to the development of sustainable Internet of Things systems. An analytical review of the literature on membrane computing and the Internet of Things is presented, substantiating the relevance of the problem raised in the work and possible solutions for further research. Based on the presented literature review and adapting the processes taking place in nature, a new max-min ants’ P system algorithm and methodology for self-management of the Internet of Things is proposed. The proposed method is investigated in MATLABTM software by creating a virtual network simulating the Internet of Things.

The dissertation consists of an introduction, three chapters, and general conclusions. The first chapter presents essential theoretical knowledge about membrane computing and the Internet of Things, analyzes the self-organizing Internet of Things, metaheuristic algorithms, formulates thesis tasks, defines the problem of Internet of Things data routing. The second chapter introduces the methodology of self-organizing the Internet of Things based on natural processes, presents the rules of the evolution of the P system, and the pseudocode of the program. In the third chapter, qualitative evaluation criteria are formulated, in MATLABTM software are performed experiments by investigating the max-min ants’ P system for the distribution and management of information on the Internet of Things and presents the results of the experimental research.

The main results of the thesis were published in 5 scientific publications: three of them were printed in peer-reviewed scientific journals, two articles – in conference proceedings. The research results were presented in 6 scientific conferences.

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