| dc.description.abstract | In the era of informatization, cloud computing suffers from the network bandwidth and the geographical distance and thus is hard to fulfill the demand of specific IoT service, such as self-driving car and smart city. Due to its features of decentralization and distribution, edge computing is believed to solve the problem of cloud computing. Compare to cloud computing, edge computing has multiple advantages, it can optimize its response time to service requests and reduce latency as well. Furthermore, it can decrease the usage of network bandwidth and the waste of power and transmission cost. However, current development of edge computing lacks a measurement of service quality under edge computing scenario is still needed. As a result, this research proposed an edge computing service quality framework, EdgeQual, and focused on the services operating on machines. EdgeQual includes five dimensions: reliability, responsiveness, availability, elasticity, and mobility. Service quality of edge computing can be evaluated with the integration of EdgeQual’s five dimensions and service quality gap theory. According to the framework proposed, we implemented a distributed smart robot car system prototype to operate a service, and collect all the data produced by the service, then presented the results on the website. Moreover, to validate the EdgeQual and the system feasibility, we change the experimental condition to test if these changes of environment will affect the service quality. The result showed that if the experimental environment in a bad condition will have a negative impact on service quality. At last, we will discuss the research restriction and the possible way of future research. | en_US |