Abstract
As a playground for cloud computing and IoT networking environment, IoTcloudServe@TEIN has been established in the Trans-Eurasia Information Network (TEIN). In the IoTcloudServe@TEIN platform, a cloud orchestration for conducting the flow of IoT task demands is imperative for effectively improving performance. In this paper, we propose the model of optimal containerized task scheduling in cloud orchestration that maximizes the average payoff from completing tasks within the whole cloud system with different levels of cloud hierarchies. Based on integer linear programming, the model can take into account demand requirement and resource availability in terms of storage, computation, network, and splittable task granularity. To show the insights obtainable from the proposed model, the edge-core cluster of IoTcloudServe@TEIN and its peer-to-peer federated cloud scenario with OF@TEIN+ are numerically experimented and herein reported. To evaluate the model’s performance, payoff level and task completion time are considered by comparing with a well-known round-robin scheduling algorithm. The proposed ILP model can be a guideline for the cloud orchestration in IoTcloudserve@TEIN because of the lower task completion time and the higher payoff level especially upon the large demand growth, which is the major operation range of concerns in practice. Moreover, the proposed model illustrates mathematically the significance of implementing cloud architecture with refined splittable task granularity via the light-weighted container technology that has been used as the basis for IoTcloudServe@TEIN clustering design.
Highlights
Nowadays, cloud computing [1] is so commercially widespread, and IoT technology is considered a state-of-the-art future technology that can connect several devices into a communication system
In [11,12,13], there is no consideration on the here, we propose the theoretical model of optimal containerized task scheduling in cloud cloud hierarchy that should be focused on since cloud system is usually interconnected orchestration that maximizes the average payoff from completing tasks within the whole with several types of other cloud systems
The experimental results, solved by MATLAB R2017b, from the case studies 1–3 in the test scenarios 1 and 2 are presented via line graphs showing the proportion of the task allocated to each cluster, the task completion time, and the amount of payoff from completing tasks
Summary
Cloud computing [1] is so commercially widespread, and IoT technology is considered a state-of-the-art future technology that can connect several devices into a communication system. The linear programming has been forTo the in best knowledge, was complete work that could mulated [8]oftoour manage cloud there resources fromno green energy andininthe [9]past to solve optimal beprocesses directly applied to all cloud orchestration requirements in the IoTcloudServe@TEIN deployment on hierarchical cloud resources. Both works in [8] and [9], project. Integer Linear Programming (ILP) model formulation for maximizing the average payoff from completing tasks by considering different levels of cloud hierarchies.
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