Journal Information
The Journal of Systems Architecture: Embedded Software Design (JSA)
Impact Factor:

Call For Papers
The Journal of Systems Architecture: Embedded Software Design (JSA) is a journal covering all design and architectural aspects related to embedded systems and software. It ranges from the microarchitecture level via the system software level up to the application-specific architecture level. Aspects such as real-time systems, operating systems, FPGA programming, programming languages, communications (limited to analysis and the software stack), mobile systems, parallel and distributed architectures as well as additional subjects in the computer and system architecture area will fall within the scope of this journal. Technology will not be a main focus, but its use and relevance to particular designs will be.

Types of Paper
The journal welcomes the following types of contributions:
• Original research articles
• Review articles, providing a comprehensive review on a scientific topic
• Fast Communications: Short, self-contained articles on ongoing research, or reporting interesting, possibly tentative, ideas, or comments on previously published research
Last updated by Dou Sun in 2019-11-24
Special Issues
Special Issue on Security and Privacy in Fog Computing-based Critical Infrastructures
Submission Date: 2021-01-31

The increasing integration of information and communication technologies has undoubtedly boosted the efficiency of Critical Infrastructures (CI). However, the first wave of IoT devices, together with the management of enormous amount of data generated by modern CIs, has created serious architectural issues. Fog computing has emerged as a viable solution for many large-scale latency-sensitive CI-based applications. Usually, the concept of fog computing is useful for various mission critical applications that require real-time data processing. Despite the concept of fog computing offering several notable features (e.g., low latency, dynamic per user optimization, etc.), many issues remain for it to be an efficient computing paradigm. Especially, some issues related to performance and security urgently need to be considered. Given the importance of security considerations for IoT environments and the growing interest in fog computing and its associated technologies, this special issue is focused on security and privacy issues in fog computing-based critical Infrastructures (like smart-grid, IoT-based e-healthcare system, Vehicle-to-grid network, etc) Here we welcome high quality research from both academia and industry, with particular emphasis on novel ideas and techniques. Only technical papers describing previously unpublished, original, state-of-the-art research, and not currently under review by a conference or a journal will be considered. We will recommend submission of multimedia with each paper as this significantly increases the visibility, downloads, and citations of articles. Selection and Evaluation Criteria Relevance to the topics of this special issue Research novelty (e.g., new techniques) and potential impact Readability Potential topics include, but are not limited to: Authentication for fog computing- based critical Infrastructures Privacy for fog computing-based critical Infrastructures Accountability for fog computing-based critical infrastructures Block-chain security for fog-enabled critical infrastructures Hardware security of devices in fog-enabled critical infrastructures Safety issues in fog-enabled critical infrastructures Access control and key-management for fog-enabled critical infrastructures Theories, methods and applications in machine learning addressing security issues and solutions for fog-enabled critical infrastructures Trust management for fog computing Test-bed, prototype implementation and fog-based security applications New paradigms facilitating fog-enabled critical infrastructures Data security in fog-enabled critical infrastructures Deception Technologies for securing critical infrastructures
Last updated by Dou Sun in 2020-07-04
Special Issue on Safe and Intelligent Embedded Software and Systems
Submission Date: 2021-02-01

With the constraint of limited resources, embedded systems demand novel security techniques to protect their critical operations. For robustness, various resource-efficient fault tolerance techniques for reliable operations are also needed. On the other hand, Artificial Intelligence/Machine Learning (AI/ML) has become the key enabling technology for many applications, from recommendation systems to facial recogintion. However, the Deep Learning and Deep Reinforcement Learning, as the most effective AI/ML techniques, are generally quite complex where the model training are very computation-intensive and are typically performed offline and in the cloud. Even the runtime model inference may demand significant computing power from the computing platform, which may be a heterogeneous mixture of multicore CPUs, GPUs, DSPs, FPGAs and ASICs. Such complex requirements on safety, security, reliability and intelligence call for innovative security, fault tolerance, and AI/ML techniques for resource-constained embedded systems, such as Internet of Things (IoTs), where many challenging research issues of performance, efficiency, power-consumption, reliability, dependability and security need to be addressed. This special section aims to present a collection of papers on the following topics in the context of safe and intelligent embedded software and systems: Novel secure designs for embedded software and systems Innovative fault tolerance techniques for embedded software and systems Power efficient fault tolerance approaches embedded software and systems Intelligent algorithms and architectures for resource-constrained platforms AI/ML techniques for specialized heteorgenos platforms with GPUs/DSPs/FPGAs Performance optimization for safe and intelligent embedded systems
Last updated by Dou Sun in 2020-07-04
Special Issue on Ubiquitous Edge Computing for Next Generation IoT and 6G: Architecture, Modelling and Systems (VSI:UECNx-IoT)
Submission Date: 2021-03-15

The technological enhancement in the field of smart communication from daily life to industrial applications leading towards the development of more efficient and persuasive system for the emerging phenomenon of next generation IoT. The 5G and beyond technology is already making big differences for the edge computing system and services paradigm. But in the future, the sheer volume of things which will be connected to the internet for various smart embedded products or areas such as traffic safety, automated vehicles and industrial can’t be handled by these beyond technologies as it requires low latency and high speed that leads to distributed computing to save time and bandwidth. The future technology with the evolution towards 6G demands ubiquitous edge computing (UEC) and fog computing which includes the big data architectures, protocols and management along with data security and distributive ubiquitous edge applications systems. The International Telecommunication Union (ITU) has designed the protocols and architectures in 3GPP ecosystem for Industrial IoT based UEC models. The 6G technology offers advanced computational services for ambient intelligent embedded systems with the optimization and resource management models using machine learning (AI). This UEC based networking extends the system design, deployment and performance management for next generation IoT applications along with secure and green networking. The special issue will serve a platform for the academicians and industrial researchers to present their state-of-art ideas and contributions toward UEC based smart embedded protocols, architecture, modelling, simulations and systems for next generation IoT and 6G applications. The submitted work should be unpublished technical articles with substantial novel contribution towards the scope. The list of topics in scope for this issue includes, but is not limited to: Smart embedded systems for 6G Ubiquitous networking for secure next generation IoT Resource allocation and optimization in UEC AI/ML based protocols and architecture for next generation IoT Cloud virtualization and management for 6G applications Machine learning techniques for Fog computing and UEC Ambient intelligent embedded systems and architecture for 6G Intelligent architectures for distributed computing in next generation IoT Modelling, system architecture and deployment for 6G Heterogeneous resource management UEC systems Content and information centric architecture for UEC systems Modelling and simulations for 6G architecture for IIoT application Software defined networking for next generation IoT applications Load balancing architecture, systems and security in 6G applications AI based persuasive system for mobile edge computing based IIoT applications Terahertz and cell-less protocols and hardware systems for 6G applications Infrastructure management architecture and simulations for UEC systems
Last updated by Dou Sun in 2020-08-24
Special Issue on Trustworthiness and Privacy in Sensor-Cloud Systems (VSI: TPSCS)
Submission Date: 2021-03-31

Cloud Computing and Wireless Sensor Networks have received tremendous attention from both academia and industry, due to the numerous exciting applications in the Internet of Things and Cyber-Physical Systems, e.g., industrial process control, video surveillance, structural health monitoring, mobile commerce, mobile learning, and mobile gaming. Sensor-Cloud is the product of combining WSNs and Cloud Computing, allowing truly pervasive computation between the physical world and the cyber world. However, new trustworthiness and privacy challenges need to be addressed to accelerate the development of these integrated applications. First, Sensor Network Provider (SNP), Cloud Service Provider (CSP), and Cloud Service User (CSU) are included in the Sensor-Cloud system. Without trust and reputation management as well as management of CSPs and SNPs, other parties with low trust and reputation are highly likely chosen. Second, in the Sensor-Cloud system, the data is generally related to privacy while the storage space is shallow in WSNs. If massive data is stored in the cloud, it is easy to be disclosed. Third, due to sensors' weak abilities in processing and communication, it is difficult for underlying networks to afford enough computation ability for solving these new arriving trustworthiness and privacy problems. Furthermore, lots of new computing models and technologies are arising, such as fog computing, edge computing, artificial intelligence, big data, and the Internet of Things. This calls for the urgent need to consider and develop new mechanisms to fill the gap between WSNs and cloud computing. Future sensors and cloud-integrated systems need to close the trustworthiness and privacy gap in the face of challenges in different circumstances. This Special Issue is proposed to bring together researchers to exchange the state-of-art research results to tackle the trustworthiness and privacy issues of sensor-cloud systems. The topics of interest include, but are not limited to: Concepts, theory, standardization and modeling, and methodologies for sensor-cloud systems Trustworthiness model and architecture in sensor-cloud Data protection in sensor-cloud systems Security in cloud computing and pervasive/ubiquitous computing Data trustworthiness in sensor-cloud systems Trust and reputation evaluation in sensor-cloud Data protection and data integrity in sensor-cloud systems Privacy issues in sensor-cloud systems Privacy metrics and policies in sensor-cloud systems Reliability issues in sensor-cloud systems Security computing clouds for cyber-physical systems Security and applications in sensor-cloud systems Mobile sensing applications, detection, transmission and tracking in sensor-cloud systems Trustworthiness levels and relations, metrics, and measures for sensor-cloud systems Edge computing in sensor-cloud systems Intelligent algorithm and applications for sensor-cloud systems
Last updated by Dou Sun in 2020-09-07
Special Issue on Parallel, Distributed, and Network-Based Processing in Next-generation Architectures and Systems (VSI:PDP21)
Submission Date: 2021-05-10

Parallel, Distributed, and Network-Based Processing has undergone impressive change over recent years. New architectures and applications have rapidly become the central focus of the discipline. These changes are often a result of cross-fertilisation of parallel and distributed technologies with other rapidly evolving technologies. It is of paramount importance to review and assess these new developments in comparison with recent research achievements in the well-established areas of parallel and distributed computing, from industry and the scientific community. This special issue of the Journal of Systems Architecture (JSA) journal will include selected high-quality papers from the 29th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing. The topics of interest include, but are not limited to: Parallel Computing on massively parallel machines; embedded parallel and distributed systems; multi- and many-core systems; GPU and FPGA based parallel systems; parallel I/O; memory organisation. Distributed and Network-based Computing: Cluster, Grid, Web and Cloud computing; mobile computing; interconnection networks. Novel systems and architectures; high data throughput architectures; service-oriented architectures; heterogeneous systems; shared-memory and message-passing systems; middleware and distributed operating systems; dependability and survivability; resource management. Programming models and Tools: programming languages and environments; runtime support systems; performance prediction and analysis; simulation of parallel and distributed systems.
Last updated by Dou Sun in 2020-11-03
Special Issue on Dependability in IoT Systems/Tools/Apps and Applications (VSI:DependSys-IoT21)
Submission Date: 2021-06-30

The impressive future influence of the Internet of Things (IoT) in society, industry, and commerce is already widely recognized. The connected things around us can make our lives and our work simpler, safer, and more convenient—and the IoT can help us tackle big problems like environmental sustainability, chronic disease management, monitoring tasks. Though IoT plays an increasing role in the world, ensuring its dependability should be more essential. Dependability is defined as the quality of being able to be relied upon on the IoT systems, its tools/apps, which can be a measure of the reliability, availability, integrity, safety, security, privacy, and maintainability of IoT systems/apps/tools (SAT). Looking into the IoT SAT more deeply, the “dependability” can be in terms of ultra-high data trust, data quality, QoS, data privacy risk, cross-border data flow, data retention, service trust, connectivity, fault-tolerance, low latency, and so on, which are still early stage in research. As there is a significant increase in IoT device divergency, data communication, data scale, veracity, and complexity, the “dependability” concerns increase. Despite recent research innovations, integration of dependability aspects into the design and development of IoT SAT and applications are still missing. Therefore, this SI solicits papers covering the design and development of IoT systems/tools/apps (SAT) and applications with dependability support to provide steady operations, cost-efficient, and high-quality results in the IoT. The scope and interests for the special issue include but are not limited to the following list: Dependability in the design and development of IoT SAT Dependability in machines, tools, apps, and techniques used for IoT Dependability in sensor software and hardware designs for IoT Dependability in IoT software services and open source software Dependability in predictive maintenance, equipment, and process monitoring Dependability through fault-tolerance and recovery in IoT SAT Dependability of IoT Software as a Service (SaaS) Dependability of IoT software dealing with big data Dependability in holistic co-design of wireless and control of IoT Dependability in IoT software security, privacy, and trust Dependability in IoT application software (e.g., healthcare, plants, SHM, robotics) Dependability in cloud/edge/fog assisted IoT SAT Dependability assessment, metrics, evaluation, and prediction for IoT SAT
Last updated by Dou Sun in 2021-01-01
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