Submission deadline: 1 September 2019
Author notification: 1 December 2019
Publication date: April 2020
Modern systems, such as cooperative robotic systems, mobile computing systems, transportation systems, and financial systems, are becoming distributed, ubiquitous, and systems of systems composed of autonomous entities. They have to operate in highly dynamic and volatile environments, where physical infrastructure, social and societal context, network topologies, and workloads are continuously fluctuating. Consequently, smart and autonomous software-intensive behaviors become indispensable characteristics of such systems.
A Smart Autonomous System (SAS) is a composition of communicating autonomous components whose behavior may be volatile, i.e., components may break down, become unavailable due to network problems or change their behavior. Thus, the system has to be “smart” to recognize the faulty behavior, adapt itself to new arising situations if possible, and return to its original processing in case the cause of the problem has been removed. Thus, monitoring the system’s environment and adapting the behavior to critical situations is another defining characteristic of SASs. Apart from being aware of their capabilities and limitations, SASs are also capable of reasoning over a diverse body of knowledge. The use of SASs is escalating in the textile industry, agriculture, transportation, health care, business, finance, and many more. The core of SASs is software shaping the behavior of related industries.
According to various world’s leading advisors on business strategy, e.g., McKinsey, Boston Consulting Group, and Roland Berger, billions of dollars will be spent worldwide on SASs in years to come and software will be the linchpin. In the future, using machine vision, motion sensors, image and voice recognition, artificial intelligence, and advanced software, SASs will be able to handle increasingly intelligent work, including interacting with and continuously learning from their environment, and especially from people. Where these estimates provide a glimpse of potential of such systems, they also show many challenges–challenges that may take longer to surmount than enthusiastic early projections suggest.
This theme issue invites papers covering any aspect related to SASs including, but not limited to:
- Modeling and analysis
- Software architecture designs and decisions
- Software specification, verification, validation, and testing
- Artificial intelligence and deep-learning approaches
- Human, societal, and environmental aspects
- Man-machine interaction and machine-to-machine communication (e.g., OPC UA)
- Regulation and certification
- Case studies, experience reports, benchmarking, best practices, etc.
- Healthcare, transportation, aerospace, energy, robotics, finance, business, etc.
Submissions should follow the IEEE template and should consist of the following:
- A manuscript of maximum 6,000 words: A PDF of the complete manuscript layout with figures, tables placed within the text. Each figure and table is counted as 300 words.
- A source file in the Word or Latex format.
- High-resolution photos and graphics such as JPEG files are required for the final submission. Articles which have been previously published at a conference need to have significant new material (e.g., >70%), which need to be described in the cover letter. The manuscripts need to be submitted online at https://mc.manuscriptcentral.com/cs-ieee. Select “Special Section: Smart Autonomous Systems” in Step 1 of the submission process to ensure that the article is reviewed for this special issue.
Contact the guest editors at email@example.com