TAFS: A Truthful Auction for IoT Application Offloading in Fog Computing Networks

Lijun Sun, Guoliang Xue, Ruozhou Yu

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Emerging as an alternative to cloud computing, fog computing is expected to provide low-latency, high-throughput, reliable services for ever-growing Internet of Things (IoT) applications, especially real-time applications with strict responsiveness requirements. By offloading time-critical and computation-intensive applications to proximal fog nodes (FNs), both application response time and network congestion can be markedly reduced. However, the FNs commonly suffer from limited resources compared to cloud computing nodes and, hence, may not serve all application users with guaranteed performance. The dynamic and heterogeneous nature of FNs also brings difficulty and overhead to fog computing resource management. These issues are addressed in the present study with the design of a double auction mechanism, namely, truthful auction for the fog system (TAFS), which provides incentives for FNs to satisfy as many application demands as possible with guaranteed performance. TAFS takes into account the latency tolerance of application users during the FN assignment and resource allocation to satisfy real-time requirements. We theoretically prove that TAFS satisfies several desired economic properties, including truthfulness, individual rationality, and budget balance. The performance of TAFS is evaluated through simulation experiments.

Original languageEnglish (US)
Pages (from-to)3252-3263
Number of pages12
JournalIEEE Internet of Things Journal
Issue number4
StatePublished - Feb 15 2023


  • Application offloading
  • double auction
  • edge computing
  • fog computing
  • incentive mechanism

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


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