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Concern Separation for Adaptive QoS Modeling in Distrbuted Real-Time Embedded Systems
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Author(s): Jeff Gray (University of Alabama at Birmingham, USA), Sandeep Neema (Vanderbilt University, USA), Jing Zhang (Motorola Research, USA), Yuehua Lin (Honda Manufacturing of Alabama, USA), Ted Bapty (Vanderbilt University, USA), Aniruddha Gokhale (Vanderbilt University, USA)and Douglas C. Schmidt (Vanderbilt University, USA)
Copyright: 2010
Pages: 29
Source title:
Behavioral Modeling for Embedded Systems and Technologies: Applications for Design and Implementation
Source Author(s)/Editor(s): Luís Gomes (Universidade Nova de Lisboa, Portugal)and João M. Fernandes (Universidade do Minho, Portugal)
DOI: 10.4018/978-1-60566-750-8.ch004
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Abstract
The development of distributed real-time and embedded (DRE) systems is often challenging due to conflicting quality-of-service (QoS) constraints that must be explored as trade-offs among a series of alternative design decisions. The ability to model a set of possible design alternatives—and to analyze and simulate the execution of the representative model—helps derive the correct set of QoS parameters needed to satisfy DRE system requirements. QoS adaptation is accomplished via rules that specify how to modify application or middleware behavior in response to changes in resource availability. This chapter presents a model-driven approach for generating QoS adaptation rules in DRE systems. This approach creates high-level graphical models representing QoS adaptation policies. The models are constructed using a domain-specific modeling language—the adaptive quality modeling language (AQML)—which assists in separating common concerns of a DRE system via different modeling views. The chapter motivates the need for model transformations to address crosscutting and scalability concerns within models. In addition, a case study is presented based on bandwidth adaptation in video streaming of unmanned aerial vehicles.
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