Adaptive Resource Allocation Control for Fair QoS Management

Harada, Fumiko; Ushio, Toshimitsu; Nakamoto, Yukikazu

doi:10.1109/tc.2007.39

Cited by 36 publications

(16 citation statements)

References 25 publications

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“…Fundamental theories in developing real-time near-optimal heuristics are discussed in [8] [9] [11] [12]. These approaches involve sorting orders in each data set and gradually assigning a portion of each shared resource r j to each service S i .…”

Section: Theoriesmentioning

confidence: 99%

“…to efficiently sort each data set based on the prioritization of each item within the data set. The real-time near-optimal heuristic algorithm takes the mapped data set and gradually assigns resources to each task in order to minimize the error between the requested QoS levels and the actual QoS levels [9]. The results from the algorithm will be transformed in the results transformation function.…”

Section: B Resource Negotiatormentioning

confidence: 99%

“…Rajkumar et al [7] [8] developed a QoS-based resource allocation model (Q-RAM), which establishes an analytical approach to distribute system resources among multiple applications while maximizing the utility function. 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.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automatic Dynamic Resource Management architecture in tactical network environments

Peng

Moen

et al. 2009

MILCOM 2009 - 2009 IEEE Military Communications Conference

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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.

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Section: Theoriesmentioning

confidence: 99%

Section: B Resource Negotiatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automatic Dynamic Resource Management architecture in tactical network environments

Peng

Moen

et al. 2009

MILCOM 2009 - 2009 IEEE Military Communications Conference

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“…레이더가 가지고 있 는 시간은 한정되어 있고, 각 임무가 처리되는 시점에 따라 표적의 탐지율과 추적 성능이 결정 되므로, 임무들이 수행될 시간과 순서를 효율적 으로 결정할 필요가 있다 [4]. 이러한 문제를 다기 능 레이더의 임무 스케줄링이라 하며, 이를 해결 하는 다양한 접근방법들이 제시되었다 [1,12,15,[17][18][19][20]. [2,4].…”

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Task Scheduling and Multiple Operation Analysis of Multi-Function Radars

정순조¹,

장대성²,

최한림³

et al. 2014

Journal of the Korean Society for Aeronautical & Space Scie

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Radar task scheduling deals with the assignment of task to efficiently enhance the radar performance on the limited resource environment. In this paper, total weighted tardiness is adopted as the objective function of task scheduling in operation of multiple multi-function radars. To take into account real-time implementability, heuristic index-based methods are presented and investigated. Numerical simulations for generic search and track scenarios are performed to evaluate the proposed methods, in particular investigating the effectiveness of multi-radar operation concepts.

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“…, [6] , 은닉 마르 코프 모델(HMM)이나 마르코프 결정 모델(MDP) 구 조 하에서 동적 프로그래밍을 통해 문제를 해결하는 방법 [7] , QoS(Quality of Service)를 목적 함수로 두는 Q-RAM 알고리즘 [8], [10] [12] .…”

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Beam Scheduling Algorithm of Multi-Function AESA Radar Based on Dispatching Rules

Roh¹,

Ahn²,

Kim³

2012

The Journal of Korean Institute of Electromagnetic Engineering

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AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability, compared with mechanically scanned array radar. AESA radar brings a new challenges, radar resource management(RRM), which is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed the several dispatching rules for radar beam scheduling, and compared the performance on the multi-function radar scenario. We also showed that the dispatching rule which differently applying SPF(Shortest Processing time First) and ERF(Earliest Request time First) according to beam processing latency is the most efficient.

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Adaptive Resource Allocation Control for Fair QoS Management

Cited by 36 publications

References 25 publications

Automatic Dynamic Resource Management architecture in tactical network environments

Automatic Dynamic Resource Management architecture in tactical network environments

Task Scheduling and Multiple Operation Analysis of Multi-Function Radars

Beam Scheduling Algorithm of Multi-Function AESA Radar Based on Dispatching Rules

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