The Case For Cloud Network Systems Engineering
IoT networking requirements are vastly different from those supported by today’s cloud network. The processing and transport levels are multiple orders of magnitude higher than ever seen before. More importantly though, societal economic and the safety ramifications of making mistakes during this transition are off the scale. This is why system engineering of the cloud computing network is now an immediate global imperative.
System engineering has many different aspects, but it all starts with the question, “What do I really want to know?” This is the beginning of the CONOPSdocument referenced earlier. This document captures User Needs which are formal statements of what the user wants from the system. This CONOPS leads to Derived Requirements which, through an iterative process, are analyzed against a Target Architecture. Once a project is underway, methods of Integration are planned in order to provide Validation(did we build the right system?) and Verification (did we build the system right?) of the requirements. Further considerations for SE include: how to conduct Peer Reviews of a design (either Systems, Hardware, or Software), studying Defects, and establishing processes to ensure the Qualityof the final product and Compliance with Standards.
While multiple sources indicate that the business world is investing heavily in the IoT, there are no indication that these investments are addressing the question of what does society really want to know in the IoT world. To ensure success, design formality is necessary, lest “IoT” become the latest retired buzzword. Dr. Juran, in Juran on Leadership for Quality, makes the point that quality improvement programs failed because leadership assigned vague goals and responsibilities, while failing to commit resources to staff projects and reward achievements. This caused TQM, 6 Sigma, and the like to be relegated to the “dustbin” of quality programs. Is it wise to relive this error in our transition to IoT?
Ten Steps of Design Rigor
- Performing a safety or security assessment;
- Determining a target system failure rate;
- Using the target system failure rate to determine the appropriate level of development rigor;
- Using a formal requirements capture process;
- Creating software that adheres to an appropriate coding standard;
- Tracing all code back to their source requirements;
- Developing all software and system test cases based on requirements;
- Tracing test cases to requirements;
- Using coverage analysis to test completeness against both requirements and code; and
- For certification, collect and collate the process artifacts required to demonstrate that an appropriate level of rigor has been maintained.”
Using this model, security issues must be addressed through a multi-layered approach. From a system engineering point of view, users must be forced to implement complex passwords and Public Key Infrastructure (PKI) certifications must be a minimum requirement for operating across the IoT network. The article, “How to protect Wearable Devices Against Cyberattacks,” in IEEE Roundup online magazine, postulated that, where there are devices with limited functionality, they can be linked to the user’s smartphone, which can act as a conduit for the device’s information, thus securing it from the outside world. Most importantly of all, though, is ensuring that the proper amount of Systems Engineering design rigor has been exercised in the development process. This makes defects easier to find and much less costly than a multimillion-dollar security breach.
Although it would be simply impossible to implement this type of rigor globally across the cloud and its underlying network, embedded systems tenets could be applied to individual IoT projects. Since embedded systems also have a history of low development overhead, minimal memory or storage per unit, and cost-driven development cycles, a more rigorous IoT design process may save society from seeing a collapse of the cloud. In the past, this type of design rigor has paid off in successful, maintainable designs. Let’s therefore use what we’ve learned from the past to avoid a future that none of us want to see.
Dwight Bues, of Engility Corp., is a Georgia Tech Computer Engineer with 30+ years’ experience in computer hardware, software, and systems and interface design. He has worked in Power Generation, Communications, RF, Command/Control, and Test Systems. Dwight is a Certified Scrum Master and teaches courses in Architecture, Requirements, and IVV&T. He is also a certified Boating Safety instructor with the Commonwealth of Virginia and the United States Power Squadrons. He is currently working several STEM projects, sponsoring teams for competitions in the Aerospace Industries Association’s (AIA) Team America Rocketry Challenge (TARC) and the Robotics Education and Competition Foundation’s, Vex Skyrise Robotics Challenge.
Kevin L. Jackson is a globally recognized cloud computing expert, a cloud computing and cybersecurity Thought Leader for Dell and IBM and Founder/Author of the award winning “Cloud Musings” blog. Mr. Jackson has also been recognized as a “Top 100 Cybersecurity Influencer and Brand” by Onalytica (2015), a Huffington Post “Top 100 Cloud Computing Experts on Twitter” (2013), a “Top 50 Cloud Computing Blogger for IT Integrators” by CRN (2015) and a “Top 5 Must Read Cloud Blog” by BMC Software (2015). His first book, “GovCloud: Cloud Computing for the Business of Government” was published by Government Training Inc. and released in March 2011. His next publication, “Practical Cloud Security: A Cross Industry View”, will be released by Taylor & Francis in the spring of 2016
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