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ACM Transactions on Modeling and Performance Evaluation of Computing Systems | 2024 Impact Factor: 1.6 | Cite Score:2.9 | Q2

ACM Transactions on Modeling and Performance Evaluation of Computing Systems Journal With Cite Score

Cite Score and Journal Rank of ACM Transactions on Modeling and Performance Evaluation of Computing Systems

  • About: ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) is a peer-reviewed journal that publishes high-quality research on the modeling, analysis, and performance evaluation of computing systems. It covers a wide range of topics including theoretical aspects, practical methodologies, and empirical studies related to the performance of computer systems and networks. The journal aims to provide a platform for significant advances in the modeling and evaluation of computing systems, contributing to the optimization and enhancement of their performance.
  • Objective:
    The primary objective of TOMPECS is to advance the field of computing systems performance evaluation by disseminating cutting-edge research findings and innovative methodologies. The journal seeks to provide a comprehensive resource for researchers, practitioners, and educators to share their work on performance modeling, evaluation techniques, and optimization strategies. TOMPECS aims to support the development of efficient and high-performing computing systems through rigorous academic research and practical applications.
  • Interdisciplinary Approach:
    TOMPECS embraces an interdisciplinary approach, encouraging contributions from diverse fields such as computer science, electrical engineering, operations research, and applied mathematics. This approach ensures a holistic exploration of computing systems performance, integrating diverse perspectives and methodologies. By promoting interdisciplinary research, the journal aims to address complex challenges in computing systems and develop integrated solutions that advance the state of knowledge in performance modeling and evaluation.
  • Impact:
    The journal has a significant impact on both academic research and practical applications in the field of computing systems performance evaluation. It is widely cited by researchers, practitioners, and industry professionals interested in the latest developments in performance modeling and analysis. The research published in TOMPECS contributes to the development of new models, evaluation techniques, and optimization methods that enhance the performance and efficiency of computing systems. The journal serves as a valuable resource for professionals involved in the design, analysis, and optimization of computing systems and networks.
  • Significance:
    TOMPECS plays a crucial role in advancing the study and practice of computing systems performance evaluation by providing a platform for high-quality research and practical insights. Its contributions support the development of innovative techniques and methodologies that address current and future challenges in the performance of computing systems. The journals commitment to excellence and interdisciplinary focus make it an essential resource for anyone involved in research, development, and application in the field of computing systems performance evaluation. Through its rigorous scholarship and broad coverage, TOMPECS helps shape the future of computing systems, driving progress in performance modeling and evaluation.

  • Editor-in-Chief:  Leana Golubchik

  • Scope: The ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) focuses on the development and application of models, simulations, and analytical techniques to evaluate the performance of computing and communication systems. Its scope includes, but is not limited to:
  • Performance Modeling: Research on the creation of mathematical and simulation models to predict the performance of computing systems, including networks, distributed systems, and parallel computing environments.
  • Analytical Techniques: Studies on analytical methods for evaluating system performance, including queuing theory, stochastic modeling, and deterministic models.
  • Simulation: Exploration of simulation techniques for performance evaluation, including discrete-event simulation, continuous simulation, and hybrid simulation approaches.
  • System Design and Optimization: Research on the design and optimization of computing systems for improved performance, including resource allocation, scheduling algorithms, and load balancing techniques.
  • Network Performance: Studies on the performance of communication networks, including wired, wireless, and mobile networks, as well as protocols and algorithms for network optimization.
  • Cloud and Edge Computing: Research on the performance evaluation of cloud computing infrastructures, edge computing, and fog computing, including scalability, latency, and resource management.
  • High-Performance Computing (HPC): Exploration of performance issues in high-performance computing environments, including supercomputers, clusters, and grid computing.
  • Data Centers: Studies on the performance and efficiency of data centers, including energy consumption, cooling, and workload management.
  • Distributed Systems: Research on the performance of distributed systems, including fault tolerance, consistency models, and distributed algorithms.
  • Real-Time Systems: Exploration of performance evaluation techniques for real-time systems, including deadline scheduling, predictability, and latency analysis.
  • Cyber-Physical Systems: Studies on the performance of cyber-physical systems, integrating computing and physical processes, including control systems and IoT (Internet of Things) devices.
  • Security and Reliability: Research on the impact of security mechanisms on system performance, as well as techniques for enhancing the reliability and availability of computing systems.
  • Benchmarking and Experimental Evaluation: Studies on benchmarking methodologies and experimental evaluations of computing systems, including the development of standard benchmarks and performance metrics.
  • Software Performance: Exploration of performance issues related to software systems, including software optimization, compiler techniques, and runtime environments.
  • Energy Efficiency: Research on energy-efficient computing, including techniques for reducing power consumption and improving the energy efficiency of computing systems.
  • Big Data and Analytics: Studies on the performance evaluation of big data systems, including data processing frameworks, storage systems, and analytics platforms.
  • Emerging Technologies: Exploration of performance evaluation techniques for emerging technologies, including quantum computing, neuromorphic computing, and other advanced computing paradigms.
  • Theoretical Foundations: Research on the theoretical aspects of performance modeling and evaluation, including complexity analysis, approximation algorithms, and performance bounds.
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  • Print ISSN:  23763639

    Electronic ISSN:   23763647

  • Abstracting and Indexing:  Scopus

  • Imapct Factor 2024:  1.6

  • Subject Area and Category:   Computer Science, Computer Networks and Communications, Computer Science (miscellaneous), Hardware and Architecture, Information Systems, Software, Engineering, Media Technology, Safety, Risk, Reliability and Quality

  • Publication Frequency:  

  • H Index:  16

  • Best Quartile:

    Q1:  

    Q2:  Computer Networks and Communications

    Q3:  

    Q4:  

  • Cite Score:  2.9

  • SNIP:  0.846

  • Journal Rank(SJR):  0.365