The evolution of distributed computing systems: from fundamental to new frontiers

被引:0
作者
Dominic Lindsay
Sukhpal Singh Gill
Daria Smirnova
Peter Garraghan
机构
[1] Lancaster University,School of Computing and Communication
[2] Queen Mary University of London,School of Electronic Engineering and Computer Science
来源
Computing | 2021年 / 103卷
关键词
Distributed computing; Computing systems; Evolution; Green computing; 68M14; 68U35; 86A08; 01-02;
D O I
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中图分类号
学科分类号
摘要
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.
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页码:1859 / 1878
页数:19
相关论文
共 114 条
  • [1] Lamport L(1978)Time, clocks, and the ordering of events in a distributed system Commun ACM 21 558-565
  • [2] Chow Y-C(1979)Models for dynamic load balancing in a heterogeneous multiple processor system IEEE Trans Comput 10 354-361
  • [3] Botta A(2016)Integration of cloud computing and internet of things: a survey Future Gen Comput Syst 56 684-700
  • [4] De Donato W(1983)The LOCUS distributed operating system ACM SIGOPS Oper Syst Rev 17 49-70
  • [5] Persico V(1982)Grapevine: an exercise in distributed computing Commun. ACM 25 260-274
  • [6] Pescap A(2011)Mesos: a platform for fine-grained resource sharing in the data center NSDI 11 22-22
  • [7] Walker Bruce TG(2003)Web services orchestration and choreography IEEE Internet Comput 36 46-52
  • [8] Popek G(2018)Holistic virtual machine scheduling in cloud datacenters towards minimizing total energy IEEE Trans Parallel Distrib Syst 29 1317-1331
  • [9] English R(2016)Borg, omega, and kubernetes Commun. ACM 59 50-57
  • [10] Kline C(1978)What is a distributed data processing system? Computer 11 13-21