With the characterizing benefits of ultra-low latency, contextual computing, and mobile scalability, mobile edge computing (MEC) is considered as a key enabler for realizing a tremendous boom in heterogeneously time-sensitive Internet-of-Things (IoT) services in the fifth-generation (5G) ecosystems. However, achieving low-latency comes at a cost of energy-efficiency reduction. To address and balance this tradeoff, this paper proposes a joint optimization of energy consumption and latency satisfaction in MEC servers, called latency-aware green (LAG) computing algorithm. To fully consider the heterogeneity of IoT services offloaded to the MEC servers, offloading traffic at the MEC servers is assumed to be unmodeled and unpredictable. Using the proposed LAG algorithm, each MEC server autonomously and dynamically calibrates its own computing frequency based on the current status of the workload buffer size and computational workload arrival rate. This dynamic calibration provides minimum energy consumption for the workload computation while maintaining the computational latency stabilized under a desired threshold. Evaluation results show that the proposed algorithm maintains stable MEC servers in an energyefficient manner. INDEX TERMS edge computing, Internet of Things, mobile offloading, unmodeled traffic VOLUME 8, 2020 This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.

Amid the recent disease outbreaks that have been spreading across the world, the education systems in every country have witnessed a dramatic transformation. In particular, the situation has promoted online learning on an unprecedented scale, with classes being held virtually on digital platforms. This vital transformation is a major challenge in developing countries where information infrastructure for remote learning is lacking. Inspired by these observations, this study first investigated the obstacles in the way of the deployment of smart education systems (SESs) in developing countries from a technical perspective. Consequently, a detachable SES framework, named vSmartEdu, is proposed. The framework is based on a hybrid online/offline web-service model, which adopts a service-based architecture (SBA) design concept to develop smart classrooms. In particular, the online mode is activated for a web-based classroom if an Internet service is available. In contrast, the offline-version of the system is available in offline mode in packaged form, and is utilized when the Internet is not available in a local classroom. Finally, a prototype was deployed to collect feedback from learners and educators at various educational levels. The trial implementation and survey results concretely validate the feasibility and advantages of the proposed solution.

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