Luận văn Optimization of iot services deployment in cloud-fog system

Nội dung tài liệu: Luận văn Optimization of iot services deployment in cloud-fog system

1. VIETNAM NATIONAL UNIVERSITY, HANOI UNIVERSITY OF ENGINEERING AND TECHNOLOGY DANG VAN DO OPTIMIZATION OF IOT SERVICES DEPLOYMENT IN CLOUD-FOG SYSTEM MASTER THESIS Major: Data Communication and Computer Networks HA NOI - 2019
2. VIETNAM NATIONAL UNIVERSITY, HANOI UNIVERSITY OF ENGINEERING AND TECHNOLOGY Dang Van Do OPTIMIZATION OF IOT SERVICES DEPLOYMENT IN CLOUD-FOG SYSTEM MASTER THESIS Major: Data Communication and Computer Networks Supervisor: Dr. Tran Truc Mai Assoc.Prof. Nguyen Kim Khoa HA NOI - 2019
3. Abstract With the predicted explosion in the number of connected devices, sensors and extremely large amount of data generated need to be analyzed, the current cloud paradigms, which tend to me concentrate computing and storage resources in a few large data centers, will inevitably lead to excessive network load, end-to-end service latency, and overall power consumption. This leads to the creation of new network architectures that extend computing and storage capabilities to the edge of the network, close to end-users. Along with the new network architectures, it enables a new breed of services and applications with tightly Quality of services. The emerging problem is how to efficiently deploy the services to the system that satisfies service resource requirements and QoS constraints while maximizing resource utilization. In this thesis, we investigate the problem of IoT services deployment in Cloud- Fog system to provide IoT services with minimal resource usage cost. We for- mulate the problem using a Mixed-Integer Linear Programming model taking into account the characteristics of computing and transmission resources in Cloud-Fog system as well as the IoT services specific requirements. Our solution provides a multi-layer mapping mechanism that efficiently deploys IoT services to the ap- propriate virtual network in physical infrastructure. Unfortunately, our proposed model is unable to solve in polynomial time due to it is NP-hard. We propose greedy-based algorithms for solving the problem which tries to solve each phase of the deployment process sequentially. We illustrate the utility of our solutions over a motivating example where we compare the efficiency of our solutions with the existing solutions for a traffic monitoring service. The experimental results show that our proposed solution outperforms compared to existing solutions in terms of energy efficiency. iii
4. Acknowledgements I would like to express my sincere gratitude to Dr. Tran Truc Mai and As- soc. Prof Nguyen Kim Khoa, my supervisors, for providing continuous support to my studies and research, for their patience, motivation, enthusiasm and immense knowledge. Their guidance helped me all the time doing this research and writing this thesis. My sincere thanks also go to the Faculty of Information and Technology, Uni- versity of Engineering and Technology, Vietnam National University for provid- ing me all the necessary facilities to make this research project easier. Finally, I would like to say thanks to my family, my friends who have always believed, motivated and supported me throughout the past process to achieve to- day’s results. iv
5. Declaration I hereby declare that this thesis was entirely my own work and that any addi- tional sources of information have been duly cited. I certify that, to the best of my knowledge, my thesis does not infringe upon anyone’s copyright nor violate any proprietary rights and that any ideas, tech- niques, quotations, or any other material from the work of other people included in my thesis, published or otherwise, are fully acknowledged in accordance with the standard referencing practices. Furthermore, to the extent that I have included copyrighted material, I certify that I have obtained written permission from the copyright owner(s) to include such material(s) in my thesis and have included copies of such copyright clear- ances to my appendix. I declare that this thesis has not been submitted for a higher degree to any other University or Institution. v
6. Table of Contents Abstract iii Acknowledgements iv Declaration v Table of Contents vii Acronyms viii List of Figures x List of Tables xi 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 1.2 Problem statement . . . . . . . . . . . . . . . . . . . . . . . . .4 1.3 Research questions . . . . . . . . . . . . . . . . . . . . . . . .6 1.4 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7 1.5 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8 2 Literature review 9 2.1 Fog computing and the Internet of Things . . . . . . . . . . . . .9 2.1.1 Definition . . . . . . . . . . . . . . . . . . . . . . . . .9 2.1.2 Reference Architecture . . . . . . . . . . . . . . . . . . 10 2.2 IoT services . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3 Optimal services deployment problem . . . . . . . . . . . . . . . 16 vi
7. 2.3.1 Algorithms . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.2 Comparison and discussion . . . . . . . . . . . . . . . . 20 3 Methodology 22 3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.1.1 Network model . . . . . . . . . . . . . . . . . . . . . . 22 3.1.2 Service model . . . . . . . . . . . . . . . . . . . . . . . 23 3.1.3 Virtual layer model . . . . . . . . . . . . . . . . . . . . 24 3.2 The optimization of IoT services deployment in Cloud-Fog system 24 3.2.1 MILP formulation. . . . . . . . . . . . . . . . . . . . . 24 3.2.2 Deployment model. . . . . . . . . . . . . . . . . . . . . 32 4 Experiment results and discussion 36 4.1 Experiment results . . . . . . . . . . . . . . . . . . . . . . . . . 36 4.1.1 Simulation details . . . . . . . . . . . . . . . . . . . . . 36 4.1.2 Simulation scenarios . . . . . . . . . . . . . . . . . . . 38 5 Conclusion 42 vii
8. Acronyms 4G Fourth Generation CPU Central Processing Unit DC Data Center Gbps Gigabit per second IoT Internet of Things J/bit Joule per bit Mbps Megabit per second MCF Multi-commodity Flow MILP Mixed Integer Linear Programming MIPS Millions of Instructions Per Second NP Non-deterministic Polynomial-time QoS Quality of Service TCP Transmission Control Protocol UDP User Datagram Protocol viii
9. VM Virtual Machine VNE Virtual Network Embedding VNF Virtual Network Function WSN Wireless Sensor Network ix
10. List of Figures 1.1 Three-layer Cloud-Fog system paradigm . . . . . . . . . . . . .2 1.2 IoT services in Cloud-Fog system . . . . . . . . . . . . . . . . .3 2.1 Fog computing reference architecture [1] . . . . . . . . . . . . . 12 3.1 Traffic monitoring service model. . . . . . . . . . . . . . . . . . 23 3.2 Services deployment problem . . . . . . . . . . . . . . . . . . . 26 4.1 Smart city infrastructure used in our simulations. . . . . . . . . . 37 4.2 Average power consumption of the traffic monitoring service for different amounts of energy consumed by server nodes in idle state. 39 4.3 Average power consumption of the traffic monitoring service for different edge node efficiencies. . . . . . . . . . . . . . . . . . . 40 x