A GA-Based Approach to Resource Scheduling Supporting Flexible Quality Management of Ubiquitous Services

M. Horng, Yen-Ching Chan, Y. Kuo, Chia-Ming Yang, Jang-Pong Hsu
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引用次数: 1

Abstract

In ubiquitous services, concurrent requests from various services for limited service resources such as network bandwidth, easily lead to a problem of resource insufficiency. The resource scheduling for ubiquitous services is the key to improve the tradeoff between request admittance, resource utilization and service quality. In this paper, a GA-based approach to resource scheduling to enable a flexible quality management of ubiquitous services is proposed to solve the problem mentioned above. First, the relationships between service of quality and resource requirements are explored. There are four different types of relations including (1) linear with saturation (LWS), (2) linear with dead zone and saturation (LWDS), (3) shifted step (SS), and (4) exponential (EX). Based on the derivation of the resource-quality model with the four relations, we define the maximum and minimum of resource requirement and regard the scope as the negotiation criterion for quality guarantee in genetic algorithm. Experimental results show that the proposed approach definitely benefits quality guarantee of service and the increasing of service request admittance ratio.
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支持泛在服务柔性质量管理的基于遗传算法的资源调度方法
在泛在服务中,各种业务对有限的业务资源(如网络带宽)进行并发请求,容易导致资源不足的问题。泛在服务的资源调度是实现请求准入、资源利用率和服务质量之间平衡的关键。为了解决上述问题,本文提出了一种基于遗传算法的资源调度方法,以实现对泛在服务的灵活质量管理。首先,探讨了服务质量与资源需求之间的关系。有四种不同类型的关系,包括(1)线性与饱和(LWS),(2)线性与死区和饱和(LWDS),(3)移阶(SS)和(4)指数(EX)。在推导具有这四种关系的资源质量模型的基础上,定义了资源需求的最大值和最小值,并将其范围作为遗传算法质量保证的协商准则。实验结果表明,该方法对保证服务质量和提高服务请求准入率有明显的好处。
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