Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.
Sensors (Basel). 2023 Apr 15;23(8):4008. doi: 10.3390/s23084008.
Edge computing is a viable approach to improve service delivery and performance parameters by extending the cloud with resources placed closer to a given service environment. Numerous research papers in the literature have already identified the key benefits of this architectural approach. However, most results are based on simulations performed in closed network environments. This paper aims to analyze the existing implementations of processing environments containing edge resources, taking into account the targeted quality of service (QoS) parameters and the utilized orchestration platforms. Based on this analysis, the most popular edge orchestration platforms are evaluated in terms of their workflow that allows the inclusion of remote devices in the processing environment and their ability to adapt the logic of the scheduling algorithms to improve the targeted QoS attributes. The experimental results compare the performance of the platforms and show the current state of their readiness for edge computing in real network and execution environments. These findings suggest that Kubernetes and its distributions have the potential to provide effective scheduling across the resources on the network's edge. However, some challenges still have to be addressed to completely adapt these tools for such a dynamic and distributed execution environment as edge computing implies.
边缘计算是一种通过将资源扩展到更接近给定服务环境的位置来提高服务交付和性能参数的可行方法。文献中有许多研究论文已经确定了这种架构方法的关键优势。然而，大多数结果都是基于在封闭网络环境中进行的模拟。本文旨在分析包含边缘资源的处理环境的现有实现，同时考虑目标服务质量 (QoS) 参数和所使用的编排平台。在此基础上，评估了最受欢迎的边缘编排平台在允许远程设备纳入处理环境的工作流程方面的表现，以及它们根据需要调整调度算法逻辑以改善目标 QoS 属性的能力。实验结果比较了这些平台的性能，并展示了它们在真实网络和执行环境中为边缘计算做好准备的当前状态。这些发现表明，Kubernetes 及其发行版有潜力在网络边缘的资源上提供有效的调度。然而，为了使这些工具完全适应边缘计算这种动态分布式执行环境，仍然需要解决一些挑战。
