<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kinnebrew, John S</style></author><author><style face="normal" font="default" size="100%">Otte, William R</style></author><author><style face="normal" font="default" size="100%">Shankaran, Nishanth</style></author><author><style face="normal" font="default" size="100%">Biswas, Gautam</style></author><author><style face="normal" font="default" size="100%">Schmidt, Douglas C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Intelligent Resource Management and Dynamic Adaptation in a Distributed Real-time and Embedded Sensor Web System</style></title><secondary-title><style face="normal" font="default" size="100%">The 12th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing (ISORC)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">autonomous agent technologies</style></keyword><keyword><style  face="normal" font="default" size="100%">autonomous system adaptation</style></keyword><keyword><style  face="normal" font="default" size="100%">distributed processing</style></keyword><keyword><style  face="normal" font="default" size="100%">distributed real-time embedded systems</style></keyword><keyword><style  face="normal" font="default" size="100%">distributed real-time system</style></keyword><keyword><style  face="normal" font="default" size="100%">dynamic adaptation</style></keyword><keyword><style  face="normal" font="default" size="100%">dynamic resource management</style></keyword><keyword><style  face="normal" font="default" size="100%">embedded sensor Web system</style></keyword><keyword><style  face="normal" font="default" size="100%">embedded systems</style></keyword><keyword><style  face="normal" font="default" size="100%">intelligent resource management</style></keyword><keyword><style  face="normal" font="default" size="100%">QoS-enabled component middleware</style></keyword><keyword><style  face="normal" font="default" size="100%">quality of service</style></keyword><keyword><style  face="normal" font="default" size="100%">quality-of-service</style></keyword><keyword><style  face="normal" font="default" size="100%">resource allocation</style></keyword><keyword><style  face="normal" font="default" size="100%">SEAMONSTER project</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2009</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">https://archive.isis.vanderbilt.edu/sites/default/files/Kinnebrew et al - 2009 - ISORC -- Intell Resource Mgmt &amp; Dyn Adapt in DRE Sensor Web.pdf</style></url></related-urls></urls><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">135 -142</style></pages><abstract><style face="normal" font="default" size="100%">Sensor webs are often composed of servers connected to distributed real-time embedded (DRE) systems that operate in open environments where operating conditions, workload, resource availability, and connectivity cannot be accurately characterized a priori. The South East Alaska MOnitoring Network for Science, Telecommunications, Education, and Research (SEAMONSTER) project exhibits many common system management and dynamic operation challenges for effective, autonomous system adaptation in a representative sensor web. These challenges cover both field operation (e.g., power management through system sleep/wake cycles and reaction to local environmental changes) and server operation (e.g., system adaptation for new/modified goals, resource allocation for a changing set of applications, and configuration changes for fluctuating workload). This paper presents the results of integrating and applying quality-of-service (QoS)-enabled component middleware, dynamic resource management, and autonomous agent technologies to address these challenges in SEAMONSTER.</style></abstract></record></records></xml>