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Controlling quality‐of‐service in distributed real‐time and embedded systems via adaptive middleware
Author(s) -
Schantz Richard E.,
Loyall Joseph P.,
Rodrigues Craig,
Schmidt Douglas C.
Publication year - 2006
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.761
Subject(s) - middleware (distributed applications) , quality of service , computer science , control reconfiguration , adaptation (eye) , distributed computing , resource (disambiguation) , service (business) , embedded system , quality (philosophy) , computer network , philosophy , physics , economy , epistemology , optics , economics
Computing systems are increasingly distributed, real‐time, and embedded (DRE) and must operate under highly unpredictable and changeable conditions. A challenging problem for DRE systems is adaptation of behavior and reconfiguration of resources to maintain the best application performance in the face of changes in system load and available resources. To provide predictable mission‐critical quality of service (QoS) end‐to‐end, QoS‐enabled middleware services and mechanisms have begun to emerge, but they lack support for applications with stringent QoS requirements in changing, dynamic environments. This paper presents two contributions to research on adaptive and reconfigurable DRE systems. First, we describe the structure and functionality of an advanced middleware platform for developing applications that apply various techniques to adapt themselves to changes in resource availability to meet real‐time QoS requirements. Second, we present results of a case study of a multimedia application for Unmanned Aerial Vehicle (UAV) video distribution we developed using this middleware platform in conjunction with QoS‐enabledoperating systems and networking protocols. We describe the design of the multimedia application using our middleware platform and report empirical results showing how adaptive behavior and end‐to‐end resource management techniques are used to reconfigure the system dynamically to meet timeliness requirements. Copyright © 2006 John Wiley & Sons, Ltd.