Fruit Fly Optimization Algorithm for Network-Aware Web Service Composition in the Cloud

Abstract

Service Oriented Computing (SOC) provides a framework for the realization of loosely coupled service oriented applications. Web services are central to the concept of SOC. Currently, research into how web services can be composed to yield QoS optimal composite service has gathered significant attention. However, the number and spread of web services across the cloud data centers has increased, thereby increasing the impact of the network on composite service performance experienced by the user. Recently, QoS-based web service composition techniques focus on optimizing web service QoS attributes such as cost, response time, execution time, etc. In doing so, existing approaches do not separate QoS of the network from web service QoS during service composition. In this paper, we propose a network-aware service composition approach which separates QoS of the network from QoS of web services in the Cloud. Consequently, our approach searches for composite services that are not only QoS-optimal but also have optimal QoS of the network. Our approach consists of a network model which estimates the QoS of the network in the form of network latency between services on the cloud. It also consists of a service composition technique based on fruit fly optimization algorithm which leverages the network model to search for low latency compositions without compromising service QoS levels. The approach is discussed and the results of evaluation are presented. The results indicate that the proposed approach is competitive in finding QoS optimal and low latency solutions when compared to recent techniques.

Authors and Affiliations

Umar SHEHU, Ghazanfar SAFDAR, Gregory EPIPHANIOU

Keywords

Related Articles

Missing Values Imputation using Similarity Matching Method for Brainprint Authentication

This paper proposes a similarity matching imputation method to deal with the missing values in electroencephalogram (EEG) signals. EEG signals with rather high amplitude can be considered as noise, normally they will be...

Adaptive Cache Replacement:A Novel Approach

Cache replacement policies are developed to help insure optimal use of limited resources. Varieties of such algorithms exist with relatively few that dynamically adapt to traffic patterns. Algorithms that are tunable typ...

An Effective Identification of Species from DNA Sequence: A Classification Technique by Integrating DM and ANN

Species classification from DNA sequences remains as an open challenge in the area of bioinformatics, which deals with the collection, processing and analysis of DNA and proteomic sequence. Though incorporation of data m...

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs). In such an environment, reducing the in-network communication and distributing the load evenly over the network can...

Designing a Markov Model for the Analysis of 2-tier Cognitive Radio Network

Cognitive Radio Network (CRN) aims to reduce spectrum congestion by allowing secondary users to utilize idle spectrum bands in the absence of primary users. However, the overall user capacity and hence, the system throug...

Download PDF file
  • EP ID EP117716
  • DOI 10.14569/IJACSA.2016.070201
  • Views 128
  • Downloads 0

How To Cite

Umar SHEHU, Ghazanfar SAFDAR, Gregory EPIPHANIOU (2016). Fruit Fly Optimization Algorithm for Network-Aware Web Service Composition in the Cloud. International Journal of Advanced Computer Science & Applications, 7(2), 1-11. https://europub.co.uk/articles/-A-117716