Emerging use-cases like smart manufacturing and smart cities pose challenges in terms of latency, which cannot be satisfied by traditional centralized networks. Edge networks, which bring computational capacity closer to the users/clients, are a promising solution for supporting these critical low latency services. Different from traditional centralized networks, the edge is distributed by nature and is usually equipped with limited connectivity and compute capacity. This creates a complex network to handle, subject to failures of different natures, that requires novel solutions to work in practice. To reduce complexity, more lightweight solutions are needed for containerization as well as smart monitoring strategies with reduced overhead. Orchestration strategies should provide reliable resource slicing with limited resources, and intelligent scaling while preserving data privacy in a distributed fashion. Power management is also critical, as providing and managing a large amount of power at the edge is unprecedented.
翻译:智能制造和智能城市等新兴使用案例在隐蔽性方面构成挑战,传统中央化网络无法满足这种挑战。使计算能力更接近用户/客户的边缘网络是支持这些至关重要的低隐隐隐隐性服务的一个大有希望的解决办法。不同于传统的中央化网络,边缘是自然分布的,通常具有有限的连通性和计算能力。这造成了一个复杂的网络,在遇到不同性质的失败时,需要新的实际操作解决方案。为了降低复杂性,需要更轻量级的解决方案来进行集装箱化,还需要更聪明的监测战略来减少间接费用。 交织战略应该以有限的资源提供可靠的资源残渣,明智地扩大规模,同时以分布方式保护数据隐私。 电力管理也至关重要,因为边缘提供和管理大量电力是前所未有的。