Mobile edge computing (MEC) offers cloud capabilities and service environment for Internet-of-Things (IoT) applications at the edge of the mobile network. New services for a specific set of IoT application programming interfaces (APIs) of diversified industry verticals can efficiently be deployed. As the set of APIs based on the IoT continues to thrive, reliance on the underlying cloud computing to deliver real-time and context-based services is also prominent in MEC. Due to the increased level of mutual interference of IoT APIs, the complexities are also multiplied. The set of IoT APIs competes for available resources within heterogeneous clouds (HCs). It is further aggravated by the unprecedented number of connected devices. We are presenting a cognitive agent (CA)-oriented approach to proactively subordinate IoT APIs with HCs. This paper contributes to establish an empirical multi-agent cognitive architecture framework (MCAF) for continuous transition of IoT APIs. We identified an adaptable composition method and a classification technique for CAs during this research effort. It introduces rationalization of CA creation, migration, and control. The approach achieves transparency in the heterogeneity and distribution of IoT APIs. It provides dynamism of cloud computing environments. The paper also illustrates the architecture impact analysis with the indicative capabilities of auto-scaling, predictability in HCs’ resource use, and responsiveness and attainment of IoT APIs.
Annals of Telecommunications – Springer Journals
Published: Jun 2, 2018
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