Energy-aware task mapping combining DVFS and task duplication for multicore networked systems
Journal article, 2025

Integrating high-performance communication and computation capabilities, multicore embedded platforms have become key components to realize applications of networked systems, e.g., Cyber-Physical Systems (CPS). Such systems usually consist of multiple dependent and real-time tasks that can be executed in parallel on different cores of the nodes and have timing, energy, and reliability constraints. Designing efficient task mapping methods to transmit and process task data under multiple constraints is challenging. Existing works seldom consider the joint design problem under timing, energy, and reliability constraints, which are coupled with each other, introducing complexity in designing efficient task mapping methods. In this paper, we first formulate the joint design problem as a complex combinational optimization problem and design a linearization method to find the optimal solution. To reduce computation complexity and enhance scalability, we design a decomposition-based heuristic method. Then, a refinement method based on feedback control is added to enhance task schedulability. The results show that the optimal solution obtained by the proposed method achieves the desired system performance. Moreover, the proposed heuristic provides a feasible solution with negligible computing time (reduces (Formula presented) computation time but with (Formula presented) performance loss). Compared with the existing works, our method can optimize the usage of system resources to balance energy, timing, and reliability requirements.

Task mapping

Dependent and real-time tasks

Task reliability

Multicore embedded systems

Author

Lei Mo

Southeast University

Jingyi Zhang

Southeast University

Minyu Cui

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

University of Gothenburg

Xiaoyong Yan

Nanjing University of Posts and Telecommunications

Shuang Wang

Southeast University

Xiaojun Zhai

University of Essex

Journal of the Franklin Institute

0016-0032 (ISSN)

Vol. 362 16 108097

Areas of Advance

Information and Communication Technology

Subject Categories (SSIF 2025)

Computer Sciences

Computer Engineering

Computer Systems

DOI

10.1016/j.jfranklin.2025.108097

More information

Latest update

10/13/2025