Introduction to Edge Computing and Cyber-physical Systems
In recent years, the rise of the Internet of Things (IoT) has transformed the way we interact with our physical environment. As the number of connected devices continues to grow exponentially, traditional cloud-based computing models have struggled to keep up with the demands of data processing, latency-sensitive applications, and the need for localized decision-making. This is where the concept of edge computing has emerged as a game-changer, promising to address the limitations of cloud computing and enable a new era of Cyber-Physical Systems (CPS).
Edge computing refers to the practice of processing data closer to the source, at the “edge” of the network, rather than relying solely on centralized cloud infrastructure. By bringing computing power, storage, and analytics closer to the devices generating data, edge computing can reduce latency, improve responsiveness, and enhance the overall efficiency of CPS applications. This is particularly crucial for time-sensitive and mission-critical systems, such as autonomous vehicles, smart manufacturing, and healthcare monitoring, where real-time decision-making and reliable performance are of the utmost importance.
Understanding the Intersection of Edge Computing and Cyber-physical Systems
As the integration of physical and digital components becomes increasingly prevalent, the need to ensure the trustworthiness of CPS has become a critical concern. Attributes such as safety, security, and predictability are essential for the successful deployment of edge-based CPS, as they directly impact the reliability and dependability of these systems. However, the introduction of edge computing introduces new challenges and considerations that must be addressed to maintain the desired level of trustworthiness.
To better understand the current state of research and the key trends in this emerging field, a team of researchers from the KTH Royal Institute of Technology in Sweden conducted a systematic mapping study on the use of edge computing for CPS. The study aimed to identify and analyze the existing research efforts, as well as to uncover the potential gaps and future research directions.
Systematic Mapping Methodology
The researchers followed a well-established systematic mapping study approach, which involves a comprehensive and rigorous literature review process. The study focused on peer-reviewed articles published between 2017 and 2020, as this period represents the recent and most active research in the intersection of edge computing and CPS.
The systematic mapping study involved the following key steps:
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Search and Selection: The researchers conducted a search across multiple electronic databases, including ACM Digital Library, IEEE Xplore, and Scopus, using a combination of relevant keywords and search strings. After an initial screening, 86 primary studies were selected for in-depth analysis.
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Data Extraction and Synthesis: The selected studies were carefully reviewed, and relevant data was extracted and organized into a structured database. This included information such as the research objectives, the proposed solutions or methods, the application domains, and the key findings or conclusions.
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Taxonomy Development: Based on the extracted data, the researchers developed a comprehensive taxonomy to categorize and analyze the various aspects of edge computing for CPS. The taxonomy covered three main perspectives: the problem definition, the solution approaches, and the assessment of the proposed solutions.
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Trend Analysis and Research Gap Identification: The researchers analyzed the trends and patterns emerging from the primary studies, focusing on the distribution of research across different application domains, the types of solutions being explored, and the extent to which trustworthiness attributes (safety, security, and predictability) were addressed.
Key Findings and Insights
The systematic mapping study yielded several important findings and insights, which are summarized as follows:
1. Predominant Application Domains
The analysis of the primary studies revealed that the majority of the research on edge computing for CPS has been focused on the domains of intelligent transportation systems and smart manufacturing. These application areas are well-suited for edge computing due to their stringent requirements for low latency, real-time decision-making, and localized data processing.
2. Emphasis on Architectural Solutions
The primary studies primarily focused on proposing architectural solutions for integrating edge computing into CPS, such as edge-cloud hierarchies, edge-fog-cloud frameworks, and edge-enabled CPS architectures. These architectural solutions aim to leverage the complementary capabilities of edge, fog, and cloud computing to address the unique requirements of CPS applications.
3. Limited Consideration of Trustworthiness Attributes
The systematic mapping study revealed that the key attributes of trustworthiness, including safety, security, and predictability, were only partially addressed in the existing research on edge-based CPS. While some studies acknowledged the importance of these attributes, the depth and breadth of the research in this area were relatively limited.
4. Potential Research Gaps
The analysis of the primary studies highlighted several potential research gaps that warrant further investigation:
a. Comprehensive Trustworthiness Evaluation: There is a need for more research that holistically addresses the various attributes of trustworthiness, including safety, security, and predictability, in the context of edge-based CPS.
b. Experimental Validation and Empirical Evaluation: The existing research often focused on theoretical or simulation-based approaches, with a lack of empirical evaluation and experimental validation of the proposed edge computing solutions for CPS.
c. Interdisciplinary Collaboration: The study found a limited degree of collaboration between the edge computing and CPS research communities, suggesting the need for stronger interdisciplinary efforts to bridge the gap and address the unique challenges at the intersection of these domains.
Implications and Future Directions
The findings of this systematic mapping study have several important implications for the future development and deployment of edge-based CPS:
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Prioritizing Trustworthiness: As edge computing becomes more prevalent in CPS applications, there is a critical need to prioritize the development of solutions that can ensure the overall trustworthiness of these systems. This will require a more comprehensive and integrated approach to addressing safety, security, and predictability concerns.
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Experimental Validation and Real-world Deployment: The research community should focus on transitioning from simulation-based studies to real-world experimental validation and empirical evaluation of edge computing solutions for CPS. This will help bridge the gap between theory and practice and provide a more robust understanding of the challenges and opportunities in this domain.
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Interdisciplinary Collaboration and Knowledge Sharing: Fostering stronger collaboration between the edge computing and CPS research communities is essential to accelerate the development of innovative and trustworthy solutions. Cross-pollination of ideas, knowledge sharing, and the establishment of interdisciplinary research programs can lead to more holistic and impactful advancements.
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Industry-Academia Partnerships: To ensure the practical relevance and widespread adoption of edge-based CPS solutions, it is crucial to establish strong partnerships between industry and academia. These collaborations can facilitate the translation of research insights into real-world applications and help address the specific challenges faced by practitioners.
Conclusion
The systematic mapping study on edge computing for Cyber-physical Systems has highlighted the significant potential of this emerging paradigm, as well as the critical need to address the challenges surrounding trustworthiness. As the integration of physical and digital systems continues to deepen, the successful deployment of edge-based CPS will require a comprehensive and interdisciplinary approach that prioritizes safety, security, and predictability.
By addressing the identified research gaps and fostering stronger collaboration between the edge computing and CPS communities, the future of edge-based CPS holds the promise of revolutionizing a wide range of industries, from transportation and manufacturing to healthcare and beyond. The insights and recommendations from this study provide a valuable roadmap for researchers, engineers, and industry stakeholders to navigate the exciting and rapidly evolving landscape of edge computing for Cyber-physical Systems.
