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An Optimization Method for Perceived Quality of Services in Service-oriented V2X Software Environments
HyeongCheol Moon, KyeongDeok Baek, In-Young Ko
http://doi.org/10.5626/JOK.2019.46.7.664
Recent advancements in computing technologies have led to researches on large-scale Cyber Physical System (CPS) applications such as Vehicle-to-Everything (V2X) applications. Numerous researchers have attempted to apply service computing technologies to V2X environments to make them more flexible and reliable. In a service-oriented V2X environment, users receive services through the Internet of Things (IoT) devices. Most of the existing V2X environments estimate or evaluate service quality from the network point of view. Apparently, the users" perceived Quality of Service (QoS), which is affected by various factors in V2X environments, especially by the users’ mobility, cannot be guaranteed. In the present work, we investigate the mobility-related factors that affect the users’ perceived QoS with an aim to optimize the users’ perceived QoS in V2X environments and propose an algorithm that considers the effectiveness of delivering service effects and the overhead of service handover among different IoT devices. We conducted a series of experiments, and it was observed that our QoS optimization approach outperforms the existing methods that consider only the quality factors in the network"s perspective.
Dynamic Discovery of Geographically Cohesive Services in Internet of Things Environments
KyeongDeok Baek, MinHyeop Kim, InYoung Ko
In Internet of Things (IoT) environments, users are required to search for IoT devices necessary to access services for accomplishing their tasks. As IoT technologies advance, a user task will utilize various types of IoT-based services that are deployed in an IoT environment. Therefore, to accomplish a user task effectively, the services that utilize IoT devices need to be found in a certain geographical region. In addition, the service discovery needs to be accomplished in a stable manner while considering dynamically changing IoT environments. To deal with these issues, we propose two service discovery methods that consider geographic cohesiveness of services in IoT environments. We compare the effectiveness of the proposed methods against a traditional service discovery algorithm that does not consider geographic cohesiveness.
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