
Dynamic Content Enabled Microservice for Business Applications in Distributed Cloudlet Cloud Network
Publication year - 2021
Publication title -
international journal of emerging trends in engineering research
Language(s) - English
Resource type - Journals
ISSN - 2347-3983
DOI - 10.30534/ijeter/2021/32972021
Subject(s) - cloudlet , computer science , cloud computing , microservices , mobile cloud computing , computer network , distributed computing , mobile device , operating system
This study introduces Mob-Cloud, a mobility aware adaptiveoffloading system that incorporates a mobile device as a thick client, ad-hoc networking, cloudlet DC, and remote cloud to improve the performance and availability of microservices services. These cloudlet cloud has emerged as a popular model for bringingthe benefits of cloud computing to the proximity of mobile devices. the microservices preliminary goal is to improve service availability as well as performance and mobility features. The impact of dynamic changes in mobile content (e.g., network status, bandwidth, latency, and location) on the task offloading model is observed by proposing a mobility aware adaptive task offloading algorithm aware microservices, which makes a task offloading decision at runtime on selecting optimal wireless network channels and suitable offloading resources. The decision problem, which is well-known as an NP-hard issue, is the subject of this work. However, for the entire proposed microservices system has the following phases: I adaptive offloading decision based on real-time information, (ii) workflow task scheduling phase, (iii) mobility model phase to motivate end-users to invoke cloud services seamlessly while roaming, and (iv) faulttolerant phase to deal with failure (either network or node). We conduct real-world experiments on the built instruments to assess the online algorithm's overall performance. Compared to baseline task offloading solutions, the evaluation findings show that online algorithm incorporates dynamic adjustments on offloading decision during run-timeand achieves a massive reduction in overall response time with better service availability.