Architecting an IIoT solution which scales? Here comes the key aspects and points to remember.
Technical
- SOA design - When the number of things is large, scalability is problematic at different levels including data transfer and networking, data processing and management, and service provisioning
- Network considerations - It is a challenging task to develop networking technologies and standards that can allow data gathered by a large number of devices to move efficiently within IoT networks. Managing connected things in terms of facilitating the collaboration between different entities and the administering devices addressing, identification, and optimization at the architectural and protocol levels is a research challenge
- Integration – of IT and OT systems
- Data maturity & Data landscape – quantity, quality and granularity
- Ability to handle large volumes of data and making it reusable
Standardization
Various standards used in IoT (e.g., security standards, communication standards, and identification standards) might be the key enablers for the spread of IoT technologies and need to be designed to embrace emerging technologies. Specific issues in IoT standardization include interoperability issue, radio access level issues, semantic interoperability, and security and privacy issues
Hidden technical debt
- Developing & deploying is still relatively fast and cheap compared to maintenance
- Debt at system level and code level
- Abstraction boundaries are not strict – as it is data dependent
- Changing Anything Changes Everything (CACE) applies not only to input signals, but also to hyper-parameters, learning settings, sampling methods, convergence thresholds, data selection, and essentially every other possible tweak
Info security and privacy protection
- Definition of security & privacy from the viewpoint of social, legal, and culture
- Trust and reputation mechanism
- Communication security such as end-to-end encryption
- Privacy of communication and user data and
- Security on services and applications.
Would you like to add to the list? Comment below.
References -
1. XU et al.: INTERNET OF THINGS IN INDUSTRIES: A SURVEY
2. C. Flügel and V. Gehrmann, “Scientific workshop 4: Intelligent objects for the internet of things: Internet of things-application of sensor networks in logistics,” Commun. Comput. Inf. Sci., vol. 32, pp. 16–26, 2009
3. Hidden Technical Debt in Machine Learning Systems https://papers.nips.cc/paper/
4. M. Fowler. Refactoring: improving the design of existing code. Pearson Education India, 1999.
