Towards Workload Balancing in Fog Computing Empowered IoT

Qiang Fan, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

122 Scopus citations


As latency is the key performance metric for IoT applications, fog nodes co-located with cellular base stations can move the computing resources close to IoT devices. Therefore, data flows of IoT devices can be offloaded to fog nodes in their proximity, instead of the remote cloud, for processing. However, the latency of data flows in IoT devices consist of both the communications latency and computing latency. Owing to the spatial and temporal dynamics of IoT device distributions, some BSs and fog nodes are lightly loaded, while others, which may be overloaded, may incur congestion. Thus, the traffic load allocation among base stations (BSs) and computing load allocation among fog nodes affect the communications latency and computing latency of data flows, respectively. To solve this problem, we propose a workload balancing scheme in a fog network to minimize the latency of data flows in the communications and processing procedures by associating IoT devices to suitable BSs. We further prove the convergence and the optimality of the proposed workload balancing scheme. Through extensive simulations, we have compared the performance of the proposed load balancing scheme with other schemes and verified its advantages for fog networking.

Original languageEnglish (US)
Article number8403280
Pages (from-to)253-262
Number of pages10
JournalIEEE Transactions on Network Science and Engineering
Issue number1
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Networks and Communications


  • Fog node
  • internet of things (IoT)
  • user association
  • workload allocation


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