Automated Performance Modeling for IoT Systems
As the Internet of Things becomes increasingly more utilized, a mainstay for IT, developers and architects are seeing how very different these infrastructures are from any other cloud based or virtual application. As software performance engineering professionals, we know the constraints, effort and objections to building design-stage models, but now is the time for embedding SPE in the development lifecycle. With IoT come architectural and design decisions regarding data analysis and storage, security and encryption, best processing placement: at the edge vs. the core vs. the cloud and network constraints. This paper/presentation presents an automated methodology for translating model-based engineering designs into performance models that can be used to predict performance and evaluate design alternatives early in the lifecycle. For demonstration, we include a case study based on a sensor network application that requires encryption to prevent security breaches. The key to the successful implementation of this system is the automated translation of the design into performance models that evaluate software decisions and hardware infrastructure options.
Dr. Connie U. Smith, CTO, Performance Engineering Services Division of L&S Computer Technology, Inc.
Dr. Connie U. Smith, CTO of the Performance Engineering Services Division of L&S Computer Technology, Inc., is known for her pioneering work in defining the field of Software Performance Engineering (SPE) and integrating SPE into the development of new software systems. Dr. Smith received the Computer Measurement Group’s prestigious A.A. Michelson lifetime achievement award for technical excellence and professional contributions for her SPE work. She is the author of the original SPE book, Performance Engineering of Software Systems, published in 1990 by Addison-Wesley, co-author of the more recent book: Performance Solutions: A Practical Guide to Building Responsive, Scalable Software also published by Addison-Wesley, and approximately 100 scientific papers. She is the creator of the SPE·EDTM performance engineering tool. She has over 25 years of experience helping clients design and implement software that meets performance requirements. Recently she has been leading a research effort, funded by USAF SBIRs, to automate the performance modeling of software and system designs with focus on IoT and Real Time Embedded Systems.
Amy has over 25 years of hands on experience in performance engineering, infrastructure capacity planning, and modeling. She has worked with hundreds of Fortune 1000 companies, assisting them to efficiently manage their IT infrastructure while improving end-user response times. One of her specialties is coordinating with IT and business partners to ensure that applications and IT services meet service level agreements and performance requirements cost effectively. Amy’s technology focus over the last 8 years has been in Cloud and digital infrastructures (a holistic view of the entire service delivery stack from the business, application, IT, to facilities). She has held multiple positions at The Uptime Institute, 451 Research and HyPerformix as a leader in consulting practices for Digital Infrastructure capacity planning and performance engineering.