ACM Transactions on Embedded Computing Systems

Scope & Guideline

Fostering breakthroughs in hardware and software integration.

Introduction

Welcome to the ACM Transactions on Embedded Computing Systems information hub, where our guidelines provide a wealth of knowledge about the journal’s focus and academic contributions. This page includes an extensive look at the aims and scope of ACM Transactions on Embedded Computing Systems, highlighting trending and emerging areas of study. We also examine declining topics to offer insight into academic interest shifts. Our curated list of highly cited topics and recent publications is part of our effort to guide scholars, using these guidelines to stay ahead in their research endeavors.
LanguageEnglish
ISSN1539-9087
PublisherASSOC COMPUTING MACHINERY
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2002 to 2024
AbbreviationACM T EMBED COMPUT S / ACM Trans. Embed. Comput. Syst.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address1601 Broadway, 10th Floor, NEW YORK, NY 10019-7434

Aims and Scopes

ACM Transactions on Embedded Computing Systems (TECS) focuses on the intersection of embedded systems and computing technologies, targeting innovations and research that enhance the efficiency, reliability, and security of embedded systems. Its primary aims encompass a variety of methodologies and core areas related to embedded computing.
  1. Embedded System Design and Optimization:
    Research in this area focuses on methodologies for designing and optimizing embedded systems, including hardware-software co-design, energy-efficient architectures, and real-time scheduling.
  2. Machine Learning and AI in Embedded Systems:
    This scope encompasses the integration of machine learning and artificial intelligence techniques into embedded systems for applications such as edge computing, IoT, and smart devices.
  3. Security and Privacy in Embedded Computing:
    The journal emphasizes research on security protocols, hardware security mechanisms, and privacy-preserving techniques tailored for embedded systems.
  4. Resource Management and Scheduling:
    Papers in this area cover dynamic resource allocation, scheduling algorithms, and management frameworks for real-time and mixed-criticality systems.
  5. Fault Tolerance and Reliability:
    This focus includes methodologies for ensuring reliability in embedded systems, such as fault detection, recovery mechanisms, and system resilience.
  6. Networking and Communication Protocols:
    Research on communication protocols, network-on-chip designs, and efficient data transfer methods for embedded systems is also a significant aspect of the journal.
  7. Energy Efficiency and Sustainability:
    The journal promotes research aimed at enhancing energy efficiency in embedded systems, including low-power design techniques and sustainable computing practices.
Recent publications in ACM TECS indicate several emerging themes that reflect the current trends and future directions in embedded computing research, showcasing a shift towards more advanced technologies and methodologies.
  1. Integration of AI and Machine Learning:
    There is a significant increase in research integrating AI and machine learning into embedded systems, focusing on applications like real-time inference, adaptive learning, and intelligent decision-making.
  2. Energy-efficient Computing:
    Research on energy-efficient designs, particularly for edge computing and IoT applications, is gaining traction as the demand for sustainable technologies grows.
  3. Post-Quantum Cryptography:
    As concerns about the security of existing cryptographic methods grow, there is an emerging focus on post-quantum cryptographic techniques specifically tailored for embedded systems.
  4. Tiny Machine Learning (TinyML):
    The trend towards TinyML highlights the development of machine learning algorithms that can run on resource-constrained devices, enabling real-time data processing and decision-making.
  5. Cyber-Physical Systems (CPS) and Internet of Things (IoT):
    Research on CPS and IoT continues to grow, emphasizing the need for reliable, secure, and efficient systems that can operate in interconnected environments.
  6. Real-time Processing and Edge Computing:
    The emergence of edge computing paradigms is reflected in the growing research on real-time processing capabilities for embedded systems, allowing for low-latency applications.
  7. Advanced Security Techniques:
    There is a noticeable trend towards more sophisticated security techniques that address vulnerabilities in embedded systems, including hardware-based security measures and secure communication protocols.

Declining or Waning

While ACM TECS continues to explore a wide range of topics, certain areas have seen a decline in focus over recent years, possibly due to evolving technology trends and research priorities.
  1. Traditional Embedded Systems without AI Integration:
    Research focusing solely on conventional embedded systems without the integration of AI or machine learning techniques is becoming less prevalent as the field shifts towards smart and adaptive systems.
  2. Legacy Communication Protocols:
    Papers centered on older or less efficient communication protocols are decreasing, as newer protocols that offer better performance and security are taking precedence.
  3. Hardware-centric Designs without Software Considerations:
    There is a noticeable decrease in research that purely focuses on hardware designs without considering the software implications, as the trend moves towards more holistic approaches that integrate both aspects.
  4. Static Resource Management Techniques:
    Static resource management strategies are being overshadowed by dynamic and adaptive approaches that better address the needs of modern, heterogeneous embedded systems.
  5. Low-complexity Security Approaches:
    Simple security measures that do not scale well with the increasing complexity of systems are being phased out in favor of more robust and scalable security frameworks.

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