This paper directly addresses a long-standing issue that affects the development of many1 complex distributed software systems: how to establish quickly, cheaply, and reliably whether2 they can deliver their intended performance before expending significant time, effort and money on3 detailed design and implementation. We describe ∆QSD, a novel metrics-based and quality-centric4 paradigm that uses formalised outcome diagrams to explore the performance consequences of design5 decisions, as a performance blueprint of the system. The distinctive feature of outcome diagrams is6 that they capture the essential observational properties of the system, independent of the details of7 system structure and behaviour. The ∆QSD paradigm derives bounds on performance expressed as8 probability distributions encompassing all possible executions of the system. The ∆QSD paradigm9 is both effective and generic: it allows values from various sources to be combined in a rigorous10 way, so that approximate results can be obtained quickly and subsequently refined. ∆QSD has been11 successfully used by Predictable Network Solutions for consultancy on large-scale applications in a12 number of industries, including telecommunications, avionics, and space and defence, resulting in13 cumulative savings worth billions of US dollars. The paper outlines the ∆QSD paradigm, describes14 its formal underpinnings, and illustrates its use via a topical real-world example taken from the15 blockchain/cryptocurrency domain. ∆QSD has enabled challenging throughput targets to be met for16 a globally distributed blockchain operating on the public internet.
This paper directly addresses a critical issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply and reliably whether they will deliver their intended performance before expending significant time, effort and money on detailed design and implementation. We describe ΔQSD, a novel metrics-based and quality-centric paradigm that uses formalised outcome diagrams to explore the performance consequences of design decisions, as a performance blueprint of the system. The ΔQSD paradigm is both effective and generic: it allows values from various sources to be combined in a rigorous way, so that approximate results can be obtained quickly and subsequently refined. ΔQSD has been successfully used by Predictable Network Solutions for consultancy on large-scale applications in a number of industries, including telecommunications, avionics, and space and defence, resulting in cumulative savings of $Bs. The paper outlines the ΔQSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain, where application of this approach enabled an advanced distributed proof-of-stake system to meet challenging throughput targets.
This paper directly addresses a critical issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply and reliably whether they will deliver their intended performance before expending significant time, effort and money on detailed design and implementation. We describe ΔQSD, a novel metrics-based and quality-centric paradigm that uses formalised outcome diagrams to explore the performance consequences of design decisions, as a performance blueprint of the system. The ΔQSD paradigm is both effective and generic: it allows values from various sources to be combined in a rigorous way, so that approximate results can be obtained quickly and subsequently refined. ΔQSD has been successfully used by Predictable Network Solutions for consultancy on large-scale applications in a number of industries, including telecommunications, avionics, and space and defence, resulting in cumulative savings of $Bs. The paper outlines the ΔQSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain, where application of this approach enabled an advanced distributed proof-of-stake system to meet challenging throughput targets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.