  While the concept of Artificial Intelligent Internet of Things\ (AIoT) is
booming, computation and/or communication-intensive tasks accompanied by
several sub-tasks are slowly moving from centralized deployment to edge-side
deployment. The idea of edge computing also makes intelligent services sink
locally. But in actual scenarios like dynamic edge computing networks (DECN),
due to fluctuations in available computing resources of intermediate servers
and changes in bandwidth during data transmission, service reliability becomes
difficult to guarantee. Coupled with changes in the amount of data in a
service, the above three problems all make the existing reliability evaluation
methods no longer accurate. To study the effect of distributed service
deployment strategies under such a background, this paper proposes a
reliability evaluation method (REMR) based on lower boundary rule under time
constraint to study the degree of the rationality of a service deployment plan
combined with DECN. In this scenario, time delay is the main concern which
would be affected by three quantitative factors: data packet storing and
sending time, data transmission time and the calculation time of executing
sub-tasks on the node devices, specially while the last two are in dynamic
scenarios. In actual calculation, based on the idea of the minimal paths, the
solution set would to be found that can meet requirements in the current
deployment. Then the reliability of the service supported by the solution sets
would be found out based on the principle of inclusion-exclusion combined with
the distribution of available data transmission bandwidth and the distribution
of node available computing resources. Besides a illustrative example was
provided, to verify the calculated reliability of the designed service
deployment plan, the NS3 is utilized along with Google cluster data set for
simulation.
