Efficient adaptive QoS-based service selection

TY - JOUR

T1 - Efficient adaptive QoS-based service selection

AU - Barakat, Lina

AU - Miles, Simon

AU - Luck, Michael

PY - 2014/12

Y1 - 2014/12

N2 - Distributed service-based systems are becoming increasingly common, with a vast range of resources and functionalities being exposed as services over open networks (e.g. the web and Grid systems). Due to the distribution, participant autonomy and lack of local control, such systems operate in highly dynamic and uncertain environments, in which services can be added, removed or change their characteristics, at any time. Thus, adaptation to change during service composition is essential to meet user needs. Yet, even when service changes occur at an early stage (e.g. at selection time), current adaptive composition approaches delay their detection until after the quality violating or unavailable service is invoked, resulting in a costly recovery during execution and, in some cases, permanently unachievable goals. In response, this paper presents a novel reactive selection algorithm, which adapts to service changes efficiently while performing the selection, ensuring an executable, satisfactory and optimal solution prior to execution. The effectiveness of the algorithm is demonstrated analytically and empirically through a case study evaluation applied in the framework of learning object composition.

AB - Distributed service-based systems are becoming increasingly common, with a vast range of resources and functionalities being exposed as services over open networks (e.g. the web and Grid systems). Due to the distribution, participant autonomy and lack of local control, such systems operate in highly dynamic and uncertain environments, in which services can be added, removed or change their characteristics, at any time. Thus, adaptation to change during service composition is essential to meet user needs. Yet, even when service changes occur at an early stage (e.g. at selection time), current adaptive composition approaches delay their detection until after the quality violating or unavailable service is invoked, resulting in a costly recovery during execution and, in some cases, permanently unachievable goals. In response, this paper presents a novel reactive selection algorithm, which adapts to service changes efficiently while performing the selection, ensuring an executable, satisfactory and optimal solution prior to execution. The effectiveness of the algorithm is demonstrated analytically and empirically through a case study evaluation applied in the framework of learning object composition.

KW - Quality of service

KW - Reactive service selection

KW - Request-based dominance

KW - Service composition

UR - http://www.scopus.com/inward/record.url?scp=84889239508&partnerID=8YFLogxK

U2 - 10.1007/s11761-013-0149-z

DO - 10.1007/s11761-013-0149-z

M3 - Article

SN - 1863-2386

VL - 8

SP - 261

EP - 276

JO - Service Oriented Computing and Applications

JF - Service Oriented Computing and Applications

IS - 4

ER -