Zone of control: the basic computing unit for web of everything

In the era of Web of Everything (WoE), numerous things devices are connected to the Internet. They produce massive data and provide Web-based services at the network edge. New computing paradigms, such as edge computing, have been proposed to handle this data as close to where they are generated as possible. However, the Paradox of Classis Insecta (PCI) problem has become a hindrance of processing them on things devices located in the network edge. In this paper, we discuss the PCI problem, and propose Zone of Control (ZoC) architecture as a basic computing unit to address it. Unlike personal computer (PC) Web and mobile Web which are unified by their own hardware-software stack and REST architecture style, WoE consists of various domain-specific and physical-environment-oriented small distributed systems and is hard to form a unified technology stack. We need a basic system architecture abstraction to guide developers in the building of a more intelligent and efficient WoE system. The fundamental idea of ZoC is to divide WoE into multiple domain-specific zones with same or similar management, privacy and security policies. We introduce ZoC algebra with four operators to provide theoretical support for manipulating zones at system runtime. Early experiment results show that ZoC is beneficial to reducing overall data transmission and protecting privacy.

[1]  Xiaohui Peng,et al.  The Φ-stack for smart web of things , 2017, SmartIoT@SEC.

[2]  Chao Lu,et al.  Zone-Oriented Architecture: An Architectural Style for Smart Web of Everything , 2019 .

[3]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[4]  Wang Yifan,et al.  Web Enabled Things Computing System , 2018 .

[5]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[6]  Carsten Bormann,et al.  6LoWPAN: The Wireless Embedded Internet , 2009 .

[7]  Lida Xu,et al.  The internet of things: a survey , 2014, Information Systems Frontiers.

[8]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[9]  Xiaohui Peng,et al.  T-REST: An Open-Enabled Architectural Style for the Internet of Things , 2019, IEEE Internet of Things Journal.

[10]  Carles Gomez,et al.  Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology , 2012, Sensors.

[11]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[12]  John A. Stankovic,et al.  t-kernel: providing reliable OS support to wireless sensor networks , 2006, SenSys '06.

[13]  Roy Fielding,et al.  Architectural Styles and the Design of Network-based Software Architectures"; Doctoral dissertation , 2000 .

[14]  David E. Culler,et al.  TinyOS: An Operating System for Sensor Networks , 2005, Ambient Intelligence.

[15]  Weisong Shi,et al.  Edge Computing: Vision and Challenges , 2016, IEEE Internet of Things Journal.

[16]  John A. Stankovic,et al.  Research Directions for the Internet of Things , 2014, IEEE Internet of Things Journal.

[17]  Zhi-Wei Xu,et al.  Cloud-Sea Computing Systems: Towards Thousand-Fold Improvement in Performance per Watt for the Coming Zettabyte Era , 2014, Journal of Computer Science and Technology.