Performance Evaluation
Volume 4 • Issue 4
- ISSN: 0166-5316
Editor-In-Chief: G. Casale
- 5 Year impact factor: 1.1
- Impact factor: 1
Performance Evaluation is a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims t… Read more
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Request a sales quotePerformance Evaluation is a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims to present a balanced and complete view of the entire field of performance evaluation. The journal audience encompasses academics, industrial researchers, and professional figures such as performance engineers, network managers, and computer system designers.
The journal solicits from its audience papers that focus on one or more of the following dimensions:
Define new performance evaluation tools, including measurement and monitoring tools as well as modeling and analytic techniques
Provide new insights into the performance of computing and communication systems
Present novel control and learning methods for performance management
Introduce new application areas where performance evaluation tools and methods can play an important role
Contributions to the journal often focus on theoretical, methodological, or applied aspects of:
Resource allocation (e.g., routing and flow control, bandwidth allocation, load-balancing, deployment,...
System tuning, sizing and optimal configuration
System reliability and dependability
Energy efficiency and energy harvesting
System architecture design and implementation
Application areas of interest include, but are not limited to, the following:
Computer and communication networks (e.g., software-defined, wireless, cognitive radio, ad-hoc, quantum,...
Data centers
Cloud, IoT, edge, and cyber-physical systems
Social networks, social media, metaverse
AI-based services
Big data and storage systems
Blockchain and distributed ledgers
Autonomous and self-organizing systems
Embedded systems
Commonly featured performance evaluation methods and techniques include:
Stochastic models (e.g., queueing theory, mean-field models, stochastic geometry,...
Data-driven methods (e.g., AI/machine learning, inference, statistical analysis, ...)
Scheduling and load balancing theory
Simulation methods
Game theory and pricing
Measurement techniques (e.g. software and hardware monitors) and workload characterization
Note that the above lists are not all inclusive or restrictive and submissions with creative applications of performance evaluation tools outside of those above and/or applications outside of those above are also welcome.
A variety of types of submissions are possible, primarily original work, tutorials & surveys.
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- ISSN: 0166-5316
- Volume 4
- Issue 4
- 5 Year impact factor: 1.1
- Impact factor: 1