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Realising Relative Autonomy and Adaptation in Smart Objects Systems

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Realising Relative Autonomy and Adaptation in Smart Objects Systems THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN COMPUTER SCIENCE Realising Relative Autonomy and Adaptation in Smart Objects Systems by Marco Eric Pérez Hernández Department of Informatics March 1, 2018 Declaration I declare that this thesis is the product of my own work, that it has not been submitted before for any degree or examination in any other university, and that all the sources I have used or quoted have been indicated and acknowledged as complete references. I have previously published some of the contents of this thesis in SMARTCOMP14 [91], FICLOUD15 [92] and FICLOUD16 [93]. I also presented part of the ideas and charts of this project in the BCS Current Leicester Postgraduate Research in Comput- ing 2016. Marco Eric Pérez Hernández March 2018, Leicester 2 Abstract The common approach for engineering of applications for the Internet of Things (IoT) relies heavily on remote resources, particularly in the cloud. As a result, data is col- lected and functionality is centralised in the cloud platforms leaving devices with only raw data gathering and actuation functions. IoT envisions an environment where de- vices can act as smart objects that are able to make decisions and operate autonomously for the benefit of the human users. Usually, autonomous functions are mixed with au- tomatic functions that only consider the human user point of view. In this work, we propose an IoT application development framework based on goal- directed and role-based smart objects. This framework is composed of a conceptual basis, a software architecture, a middleware architecture and an adaptation method. First, we define the concepts of smart object, its autonomy and the collective of smart objects from a thorough examination of the smart object, its properties and key pro- cesses. Then, we develop a set of abstractions and the software architecture for smart objects. For easing the development effort and making this approach practical, we define a mid- dleware architecture, intended to serve as blueprint for concrete middleware solutions. We also implemented a prototype based on this architecture. Functional components of the architecture enable smart object systems to adapt to volatile situations. We pro- pose a method for adaptation based on the selection of smart objects, services and roles. Finally, we develop an agent-based model for simulation of IoT environments under conditions of heterogeneity, volatility and large quantities of smart objects. We use this model together with a case study and a qualitative comparison of existing solutions to evaluate our framework. Our results show that the proposed approach is a feasible and scalable alternative for IoT application development based on smart objects that incorporates the concept of relative autonomy, in this context, and the adaptation at individual and collective level. 3 Acknowledgements There are several persons I would like to thank. First of all, I would like to thank Dr. Stephan Reiff-Marganiec for his supervision along my PhD work. His advice, motivation and support has been fundamental for the development of this thesis. I appreciate his continuous guidance and his experience for providing always valuable contributions, advice and moral support. I would also like to thank Professor Reiko Heckel and Dr. Rami Bahsoon for their valuable suggestions and opinions that were very useful for the final version of this work. Likewise, I would like to thank Dr. Emilio Tuosto and Dr. Fer-Jan de Vries for their relevant opinions along the different stages of this project. I also want to thank Ludovic Clarissou from Télécom Saint-Étienne, for help me in the validation of the em4so middleware prototype. Special thanks also to several people of the department that directly or indirectly sup- port me along this journey. Thanks to Dr. Gilbert Laycock, for his opinions and sug- gestions, particularly during the evaluation. For this project, I have learned and gath- ered ideas from my teaching assistant activities, particularly working with Dr. Stephan Reiff-Marganiec, Dr. Artur Boronat, Dr. Yi Hong and Professor Rick Thomas. Many thanks to all of them. I want to thank the Department of Informatics of the University of Leicester for funding my research studies. Besides the persons already mentioned, many thanks to Professor Thomas Erlebach, Professor Alexander Kurz and Professor Effie Law. Thanks to my colleagues PhD Students, together we listened to each other, gave mutual support. Thanks specially to Laith, Hao, Othman and Badr. Last but not least, I want to thank my wife, parents, sister, family and friends. This thesis is also yours. Thanks to Nidia for her love, support, patience and strength during the ups and downs of this journey. Thanks for all her encouragement and for being part of this. Thanks to Marco Antonio, Martha and Bibiana, their love, motivation and advice give me always that extra boost needed. Thanks to my friends in UK, Spain, US and Colombia, particularly, to my friend Oscar for his frank and timely advice. 4 Contents List of Figures 11 List of Tables 13 1 Introduction 15 1.1 Research Problem and Challenges.................... 18 1.2 Thesis Statement............................. 21 1.3 Research Scope and Contributions.................... 22 1.4 Thesis Overview and Summary...................... 23 2 Research Background and Related Work 25 2.1 Overview of the Internet of Things.................... 25 2.1.1 IoT Realisation Models...................... 27 2.2 Web of Things............................... 33 2.3 Smart Object-based IoT .......................... 35 2.3.1 Using agents for SOb-IoT .................... 37 2.3.2 Agent’s goals........................... 40 2.3.3 Agent autonomy......................... 41 2.3.4 Joint Use of Agents and Web Services.............. 44 2.3.5 Autonomic Systems....................... 46 2.3.6 Role-based architectures..................... 47 2.4 SOb-IoT Middleware: State of the Art.................. 49 2.4.1 UbiWare Project: Middleware for Industrial Systems...... 49 2.4.2 FedNet .............................. 50 2.4.3 ACOSO .............................. 51 2.4.4 ASAWoO ............................. 52 2.4.5 Leppänen............................. 53 2.4.6 Other platforms.......................... 54 5 2.5 IoT Service Selection........................... 55 2.6 Summary................................. 56 3 Foundations of Smart Object’s Autonomy 59 3.1 Introduction................................ 59 3.2 Research challenges and requirements.................. 60 3.3 Contributions............................... 60 3.4 IoT Autonomous Systems: Individual and Collective.......... 61 3.4.1 Smart Object........................... 62 3.4.2 Collective of Smart Objects................... 63 3.5 E-Ma-Gen3 Framework: An analysis tool................ 63 3.6 SO Analysis using E-Ma-Gen3 ...................... 67 3.6.1 Planes and Scope......................... 67 3.6.2 Knowledge............................ 68 3.6.3 Behaviour............................. 69 3.6.4 Resources............................. 75 3.6.5 Relationships........................... 76 3.6.6 Structure............................. 77 3.6.7 Fundamental Processes...................... 78 3.7 Smart Object’s Autonomy........................ 80 3.8 Summary................................. 83 4 Role-based Smart Objects (RbSOs) 85 4.1 Introduction................................ 85 4.2 Challenges and Requirements....................... 86 4.3 Contributions............................... 87 4.4 The Role-Based SO Software Architecture............... 87 4.4.1 Overall approach......................... 88 4.4.2 Uncoupled Goal-motivated Behaviour.............. 91 4.4.3 SO’s Knowledge Representation................. 101 4.5 Summary................................. 103 5 em4so: A Middleware Architecture for RbSOs 105 5.1 Introduction................................ 105 5.2 Research Challenges and Requirements................. 105 5.3 Contributions............................... 107 5.4 Middleware Architecture......................... 108 6 5.4.1 Design Principles......................... 108 5.4.2 em4so Architecture Overview.................. 111 5.5 Governing Body.............................. 114 5.5.1 Smart Object Controller (SOC)................. 114 5.5.2 Knowledge Base (KB)...................... 116 5.5.3 Reasoning Engine (RE)...................... 117 5.6 SO Management Body.......................... 118 5.6.1 Capability Manager (CM).................... 119 5.6.2 Social Interaction Manager (SIM)................ 120 5.6.3 KB and Storage Manager (KSM)................ 122 5.7 Support Facilities............................. 122 5.7.1 Communication Facilities (CF).................. 122 5.7.2 Device Facilities (DF)...................... 123 5.7.3 Extra Facilities (EF)....................... 123 5.8 SO Protocol................................ 123 5.9 Key interactions between SOs ...................... 124 5.9.1 Creating/Joining the Network.................. 125 5.9.2 Querying within SOs ....................... 128 5.9.3 Coordination & Cooperation................... 128 5.10 Implementation.............................. 129 5.11 Summary................................. 134 6 Adaptation of SO-based IoT Systems 135 6.1 Introduction................................ 135 6.2 Research Challenges and Requirements................. 136 6.3 Contributions............................... 136 6.4 em4so Adaptation Strategy........................ 137 6.4.1 Collective Adaptation...................... 138 6.4.2
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