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|Title: ||Commodity single board computer clusters and their applications|
|Authors: ||Johnston, Steven J.|
Basford, Philip J.
Perkins, Colin S.
Tso, Fung Po
Pezaros, Dimitrios P.
Mullins, Robert D.
Cox, Simon J.
|Keywords: ||Raspberry Pi|
Networks cloud computing
Distributed computing methodologies
|Issue Date: ||2018|
|Publisher: ||© the Authors. Published by Elsevier|
|Citation: ||JOHNSTON, S.J. ... et al., 2018. Commodity single board computer clusters and their applications. Future Generation Computer Systems, 89, pp. 201-212.|
|Abstract: ||© 2018 Current commodity Single Board Computers (SBCs) are sufficiently powerful to run mainstream operating systems and workloads. Many of these boards may be linked together, to create small, low-cost clusters that replicate some features of large data center clusters. The Raspberry Pi Foundation produces a series of SBCs with a price/performance ratio that makes SBC clusters viable, perhaps even expendable. These clusters are an enabler for Edge/Fog Compute, where processing is pushed out towards data sources, reducing bandwidth requirements and decentralizing the architecture. In this paper we investigate use cases driving the growth of SBC clusters, we examine the trends in future hardware developments, and discuss the potential of SBC clusters as a disruptive technology. Compared to traditional clusters, SBC clusters have a reduced footprint, are low-cost, and have low power requirements. This enables different models of deployment—particularly outside traditional data center environments. We discuss the applicability of existing software and management infrastructure to support exotic deployment scenarios and anticipate the next generation of SBC. We conclude that the SBC cluster is a new and distinct computational deployment paradigm, which is applicable to a wider range of scenarios than current clusters. It facilitates Internet of Things and Smart City systems and is potentially a game changer in pushing application logic out towards the network edge.|
|Description: ||This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/|
|Sponsor: ||This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/P004024/1.|
|Publisher Link: ||https://doi.org/10.1016/j.future.2018.06.048|
|Appears in Collections:||Published Articles (Computer Science)|
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