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Considerations for a Framework for Specification and Measurement of Reserve Capacity in Software‐Intensive Systems
Author(s) -
O'Connor Trent,
Cook Stephen
Publication year - 2015
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2015.00054.x
Subject(s) - computer science , software , resource (disambiguation) , margin (machine learning) , reliability engineering , systems engineering , engineering , operating system , computer network , machine learning
For some classes of software‐intensive systems, especially long life‐cycle embedded systems with evolving requirements, the customer needs some margin of reserve data processing capacity in the delivered system. This is typically needed to assure system responsiveness and stability under transient loading conditions and to provide for future software maintenance, capability growth and changes in usage without the need for processing hardware upgrades. The specification, management and verification of reserve data processing resources so as to achieve this are challenging and there is a lack of universally agreed or standardised approaches. It is proposed to create a framework for characterising run‐time resource utilisation in a data processing system, such that effective reserve capacity can be described and measured in ways that are well defined but not design‐specific. This paper outlines the need for and desirable attributes of such a framework.