Abstract
Mobile Edge Computing emerges as a key technology to address the challenges of real-time data processing by extending computing capabilities to the network edge, reducing latency, and enhancing service reliability. Existing research often inadequately addresses offloading tasks with Directed Acyclic Graph structures and fails to consider the dynamic MEC environment, limiting practical applicability. This paper proposes a DAG Task Computation Offloading Algorithm based on Network Flow Theory. The core innovation lies in applying network flow theory to optimize task scheduling in dynamic environments, considering service caching and device energy constraints. We validate the algorithm’s advantages through comprehensive simulations.
L. Zeng and K. Jin—These authors contributed equally to this work.
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Acknowledgments
This work is supported by National Natural Science Foundation of China (No. 62172124)
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Zeng, L., Jin, K., Wang, Z., Zhang, C., Du, H. (2024). NFTO: DAG-Based Task Offloading and Energy Optimization Algorithm. In: Ghosh, S., Zhang, Z. (eds) Algorithmic Aspects in Information and Management. AAIM 2024. Lecture Notes in Computer Science, vol 15179. Springer, Singapore. https://doi.org/10.1007/978-981-97-7798-3_2
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DOI: https://doi.org/10.1007/978-981-97-7798-3_2
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