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REMR: A Reliability Evaluation Method for Dynamic Edge Computing Network Under Time Constraint
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AI
DOI：10.1109/JIOT.2022.3216056.png)
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Abstract
En 中文
Computation and/or communication-intensive collaborative services accompanied by several distributed tasks/components, such as the services in Internet of Things, can be anywhere nowadays. These services are usually used by users at the Internet edge, making cloud computing struggles with the high end-to-end latency. Thanks to edge computing which pushes resources to the edge, the goals with lower latency can be well satisfied. However, in actual scenarios especially under dynamic edge computing networks, changes exist in resources, including computing, bandwidth, and nodes. Meanwhile, data packets (or flow) among collaborative tasks/components of a service can also not be conserved. These characteristics lead the service reliability hard to be guaranteed and make existing reliability evaluation methods no longer accurate. To study the effect of distributed and collaborative service deployment strategies under such background, we propose a reliability evaluation method (REMR). We first look for the solution set which can meet the time constraints. Then, we calculate the reliability of service supported by the solution set based on the principle of inclusion-exclusion with distributions of available transmission bandwidth and computing resources. Finally, we provide an illustrative example with several real-world data sets to make REMR easy to follow. To make REMR more reliable, we also propose and implement a Monte Carlo simulation method. Experiments prove that the reliability calculated by REMR is nearly the same as the simulation results and both the latencies and the jitters are also at a lower level.
Keywords:
Reliability
Task analysis
Collaboration
Computational modeling
Edge computing
Computer network reliability
Dynamic scheduling
Distributed services
dynamic networks
edge computing
reliability
sequential task
Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W
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