A novel heuristic algorithm for QoS-aware end-to-end service composition

2011 ◽  
Vol 34 (9) ◽  
pp. 1137-1144 ◽  
Author(s):  
Yuan-sheng Luo ◽  
Yong Qi ◽  
Di Hou ◽  
Lin-feng Shen ◽  
Ying Chen ◽  
...  
Keyword(s):  
Heuristic Algorithm ◽  
Service Composition ◽  
End To End

scholarly journals End-to-end QoS computation for vertical service composition in the cloud

2021 ◽  
Author(s):  
Raed Karim
Keyword(s):  
Service Composition ◽  
Cloud Service ◽  
Cloud Services ◽  
Prior History ◽  
Functional Requirements ◽  
Active System ◽  
Qos Prediction ◽  
Cloud Providers ◽  
End To End ◽  
Prediction Approach

Cloud services are designed to provide users with different computing models such as software-as-a-Services (SaaS), Infrastructure-as-a-Service (IaaS), Data-as-a-Service (DaaS), and other IT related services (denoted as XaaS). Easy, scalable and on-demand cloud services are offered by cloud providers to users. With the prevalence of different types of cloud services, the task of selecting the best cloud service solution has become more and more challenging. Cloud service solutions are offered through a collaboration of different cloud services at different cloud layers. This type of collaborations is denoted as vertical service composition. Quality of Service (QoS) properties are used as differentiating factors for selecting the best services among functionally equivalent services. In this thesis, we introduce a new service selection framework for the cloud which vertically matches services offered by different cloud providers based on users’ end-to-end QoS requirements. Functional requirements can be satisfied by the required cloud service (software service, platform service, etc) alone. However, users’ QoS requirements must be satisfied using all involved cloud services in a service composition. Therefore, in order to select the best cloud service compositions for users, QoS values of these compositions must be end-to-end. To tackle the problem of computing unknown end-to-end QoS values of vertical cloud service compositions for target users (for whom these values are computed), we propose two strategies: QoS mapping and aggregation and QoS prediction. The former deals with new cloud service compositions with no prior history. Using this strategy, we can map users’ QoS requirements onto different cloud layers and then we aggregate QoS values guaranteed by cloud providers to estimate end-to-end QoS values. The latter deals with cloud service compositions for which QoS data have been recorded in an active system. Using the QoS prediction strategy, we utilize historical QoS data of previously invoked service compositions and other service and user information to predict end-to-end QoS values. The presented experimental results demonstrate the importance of considering vertically composed cloud services when computing end-to-end QoS values as opposed to traditional prediction approaches. Our QoS prediction approach outperforms other prediction approaches in terms of the prediction accuracy by at least 20%.

scholarly journals An End-to-End Approach for QoS-Aware Service Composition

2009 ◽  
Author(s):  
Florian Rosenberg ◽  
Predrag Celikovic ◽  
Anton Michlmayr ◽  
Philipp Leitner ◽  
Schahram Dustdar
Keyword(s):  
Service Composition ◽  
End To End

Heuristic Algorithm Based Traffic Classified Routing Algorithm in Distributed Satellite Cluster Network

2015 ◽  
Vol 738-739 ◽  
pp. 1150-1159 ◽  
Author(s):  
Nan Jiang ◽  
Yuan Zhi He ◽  
Lei Guo
Keyword(s):  
Heuristic Algorithm ◽  
Routing Algorithm ◽  
Delivery Ratio ◽  
Traffic Classification ◽  
Heavy Load ◽  
Traffic Class ◽  
Cluster Network ◽  
End To End Delay ◽  
Distributed Satellite ◽  
End To End

The architecture of distributed satellite cluster network (DSCN) is presented and the characteristics of DSCN topology change are illustrated. On the basis of analyzing the acquisition method of network status and route calculation, we proposed a heuristic algorithm Ant Colony Optimization (ACO) based traffic classified routing (ATCR) algorithm for DSCN. Simulation results shows that, ATCR algorithm can balance network traffic effectively, and the end-to-end delay of every traffic class is less than TCD algorithm. The end-to-end delay of traffic class A and class B is less than ACO algorithm which does not use traffic classification. ATCR has a better performance on packet delivery ratio than ACO and TCD because ATCR reduces the number of heavy load link as well as packet loss caused by congestion.

Converged Network-Cloud Service Composition with End-to-End Performance Guarantee

2018 ◽  
Vol 6 (2) ◽  
pp. 545-557 ◽  
Author(s):  
Jun Huang ◽  
Qiang Duan ◽  
Song Guo ◽  
Yuhong Yan ◽  
Shui Yu
Keyword(s):  
Service Composition ◽  
Cloud Service ◽  
Performance Guarantee ◽  
Converged Network ◽  
End To End ◽  
Cloud Service Composition
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