A multi-layered resource management framework for dynamic resource management in enterprise DRE systems

Lardieri, Patrick; Balasubramanian, Jaiganesh; Schmidt, Douglas C.; Thaker, Gautam H.; Gokhale, Aniruddha; Damiano, Thomas

doi:10.1016/j.jss.2006.09.042

Cited by 24 publications

(20 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The satellite exploitation (Narula-Tam et al, 2004) is an example of such problems, where image requests are submitted dynamically. The work in (Lardieri et al, 2007) is another example where the authors propose an architecture supporting dynamic resource management with a reallocation process to optimize and reconfigure system resources at runtime and to adapt to changing mission needs and resource status. In LRA, the information is known in a specific area.…”

Section: Related Workmentioning

confidence: 99%

Generic model for resource allocation in transportation. Application to urban parking management

Zargayouna

Balbo

Ndiaye

2016

Transportation Research Part C: Emerging Technologies

View full text Add to dashboard Cite

In this paper, we define the online localized resource allocation problem, especially relevant for modeling transportation applications. The problem modeling takes into account simultaneously the geographical location of consumers and resources together with their online nondeterministic appearance. We use urban parking management as an illustration of this problem. In fact, urban parking management is an online localized resource allocation problem, where the question is how to find an efficient allocation of parking spots to drivers, while they all have dynamic geographical positions and appear nondeterministically. We define this problem and propose a multiagent system to solve it. The objective of the system is to decrease, for private vehicles drivers, the parking spots search time. The drivers are organized in communities and share information about spots availability. We have defined two cooperative models and compared them: a fully cooperative model, where agents share all the available information, and a "coopetitive" model, where drivers do not share information about the spot that they have chosen. Results show the superiority of the first model 1 .

show abstract

Section: Related Workmentioning

confidence: 99%

Generic model for resource allocation in transportation. Application to urban parking management

Zargayouna

Balbo

Ndiaye

2016

Transportation Research Part C: Emerging Technologies

View full text Add to dashboard Cite

show abstract

“…Component middleware technologies have raised the level of abstraction used to develop DRE systems, such as avionics mission computing [1] and shipboard computing systems [2]. Example component middleware technologies include the Lightweight CORBA Component Model (CCM), Boeing's PRiSM, OpenCOM, nesC's component model, and Timing Definition Language extension to Giotto.…”

Section: Overview and Challenges Of Component Middleware For Dre Systemsmentioning

confidence: 99%

Physical Assembly Mapper: A Model-Driven Optimization Tool for QoS-Enabled Component Middleware

Balasubramanian

Schmidt

2008

2008 IEEE Real-Time and Embedded Technology and Applications Symposium

Self Cite

View full text Add to dashboard Cite

This paper provides four contributions to the study of optimization techniques for component-based distributed realtime and embedded (DRE) systems. First, we describe key challenges of designing component-based DRE systems and identify key sources of overhead in a typical componentbased DRE system from the domain of shipboard computing. Second, we describe a class of optimization techniques applicable to the deployment of component-based DRE systems. Third, we describe the Physical Assembly Mapper (PAM), which is a model-driven optimization tool that implements these techniques to reduce footprint. Fourth, we evaluate the benefits of these optimization techniques empirically and analyze the results. Our results indicate that the deployment-time optimization techniques in PAM provides significant benefits, such as 45% improvement in footprint, when compared to conventional component middleware technologies.

show abstract

“…An initial step towards such an ETE QoS support in the large-scaled network is to ensure that computing resources in each edge network domain are managed efficiently and in accordance with the GIG architectural framework [3] [4]. Future computing requirements for diverse tactical missions rapidly increase the complexity of the heterogeneous tactical edge networks such as the existing Total Ship Computing Environments (TSCE), upcoming Consolidated Afloat Networks and Enterprise Services (CANES) [5], Command and Control systems (C2), and Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance systems (C4ISR) [6]. Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Harada et al [9] had proposed an adaptive resource allocation method based on control theories. In the context of shipboard computing environments, Lardieri et al [6] had developed a multi-layered resource management framework in enterprise distributed real-time and embedded (DRE) systems. They primarily focused on managing the XXX-X-XXXX-XXXX-XX/XX/$25.00 c 2009 IEEE Fig.…”

Section: Introductionmentioning

confidence: 99%

Automatic Dynamic Resource Management architecture in tactical network environments

Peng

Moen

et al. 2009

MILCOM 2009 - 2009 IEEE Military Communications Conference

View full text Add to dashboard Cite

Abstract-Automatic Dynamic Resource Management (AutoDRM) is a method to efficiently manage shared resources in the tactical network environments without human operator intervention. The AutoDRM architecture is developed as an attempt to resolve the resource contention issues and to improve the quality of service in the tactical network environments. The information herein describes the key components of the AutoDRM architecture. An experimental end-to-end network prototype test bed was also developed to host the AutoDRM system. Experimental results demonstrate improved network performance when AutoDRM is deployed.

show abstract

A multi-layered resource management framework for dynamic resource management in enterprise DRE systems

Cited by 24 publications

References 15 publications

Generic model for resource allocation in transportation. Application to urban parking management

Generic model for resource allocation in transportation. Application to urban parking management

Physical Assembly Mapper: A Model-Driven Optimization Tool for QoS-Enabled Component Middleware

Automatic Dynamic Resource Management architecture in tactical network environments

Contact Info

Product

Resources

About