  With the worldwide growth of IoT industry, the need for a strong security
level for IoT networks has also increased, leading to blockchain-based IoT
(BC-IoT) networks. While blockchain technology is leveraged to ensure data
integrity in a distributed manner, Hyperledger Fabric (HLF) attracts attention
with its distinctive strong point without requiring the power-consuming
consensus protocol, that is, proof-of-work (PoW). However, even though such
security concerns can be mitigated using HLF, the additional processing time
spent in HLF may emerge as another issue because most IoT devices handle
real-time and latency critical jobs. This problem still remains unresolved
because of the absence of a HLF latency model and a parameter setup guideline
to reducing the mean latency. In this paper, therefore, we develop a HLF
latency model for HLF-based IoT networks based on probability distribution
fitting, by which mean latency prediction is facilitated once probable
configuration environments are determined, in terms of the block size,
block-generation timeout, and transaction generation rate parameters.
Furthermore, we conclude by analyzing the impacts of influential HLF parameters
on the mean latency, in order to provide insights not only on optimizing the
mean latency, but also on coping with long mean latency.
