The evolution of distributed computing systems: from fundamental to new frontiers
The evolution of distributed computing systems: from fundamental to new frontiers
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DOI：
10.1007/s00607-020-00900-y
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发表时间：
2021-01-30
期刊：
影响因子：
3.7
通讯作者：
Garraghan, Peter
中科院分区：
文献类型：
--
作者：
Lindsay, Dominic;Gill, Sukhpal Singh;Garraghan, Peter
60多年来，分布式系统一直是一个活跃的研究领域，并在计算机科学中发挥了关键作用，使支撑现代生活方方面面的互联网得以发明。通过技术进步及其在社会中不断变化的角色，分布式系统经历了一个永恒的演变，每一次变化都会导致一个新的范式的形成。每一种新的分布式系统范式-其中现代的突出之处包括云计算、雾计算和物联网(IoT)-允许新形式的商业和艺术价值，但也带来了新的研究挑战，必须解决这些挑战才能实现和增强其运营。然而，有必要准确地确定是什么因素推动了范式的形成和发展，以及与前几代系统相比，现代分布式系统中的研究挑战有多独特。这项工作的目标是研究和评估从早期的大型机、全球互联网络的开始，影响和推动分布式系统范例演变的关键因素，并介绍当代系统，如边缘计算、雾计算和物联网。我们的分析强调了驱动分布式系统的假设似乎正在发生变化，包括(1)商业利益驱动的范例加速碎片化，以及摩尔定律的终结强加的物理限制，(2)从通用体系结构和框架向日益专业化的过渡，以及(3)每个范例体系结构导致在集中化和分散化协调之间的某种形式的旋转。最后，我们讨论了分布式研究在规模上研究复杂现象方面的当前和未来挑战，以及分布式系统研究在气候变化背景下的作用。
Distributed systems have been an active field of research for over 60 years, and has played a crucial role in computer science, enabling the invention of the Internet that underpins all facets of modern life. Through technological advancements and their changing role in society, distributed systems have undergone a perpetual evolution, with each change resulting in the formation of a new paradigm. Each new distributed system paradigm-of which modern prominence include cloud computing, Fog computing, and the Internet of Things (IoT)-allows for new forms of commercial and artistic value, yet also ushers in new research challenges that must be addressed in order to realize and enhance their operation. However, it is necessary to precisely identify what factors drive the formation and growth of a paradigm, and how unique are the research challenges within modern distributed systems in comparison to prior generations of systems. The objective of this work is to study and evaluate the key factors that have influenced and driven the evolution of distributed system paradigms, from early mainframes, inception of the global inter-network, and to present contemporary systems such as edge computing, Fog computing and IoT. Our analysis highlights assumptions that have driven distributed systems appear to be changing, including (1) an accelerated fragmentation of paradigms driven by commercial interests and physical limitations imposed by the end of Moore's law, (2) a transition away from generalized architectures and frameworks towards increasing specialization, and (3) each paradigm architecture results in some form of pivoting between centralization and decentralization coordination. Finally, we discuss present day and future challenges of distributed research pertaining to studying complex phenomena at scale and the role of distributed systems research in the context of climate change.