Distance-Guided GA-Based Approach to Distributed Data-Intensive Web Service Composition

Sadeghiram, Soheila; Ma, Hui; Chen, Gang

doi:10.48550/arxiv.1901.05564

Cited by 2 publications

(11 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relative distances of Web services, which is a key criterion for communication cost and time, will be utilised to identify where to insert these extra services in the solution's chromosome. That is to say, we will use domain knowledge of DWSC to produce more flexible local search operator and propose an effective and efficient MA algorithm, compared to the stateof-the-art local search technique [10], [16], for the distributed DWSC problem.…”

Section: Memetic Algorithm For Dwscmentioning

confidence: 99%

“…Many EC algorithms, such as Genetic Algorithm (GA) [15], have been used for fully-automated WSC, achieving promising results [2], [8]- [11], [16]. To further enhance the effectiveness of GA, researchers have developed hybridised GA enhanced with some local search techniques.…”

mentioning

confidence: 99%

“…On the other hand, emphasising the synergy between exploration and exploitation, MA can exploit the neighbourhood area of an individual well and obtain sufficient precision with the help of local search at the expense of execution time. In the literature, MAs have been shown to be extremely effective for WSC [2], [8], [10], [16], [23]. An MA based on GraphEvol [7] method has been suggested for WSC problem [23], in which, two move operators are designed for locally modifying an individual on the graph while keeping its feasibility.…”

mentioning

confidence: 99%

“…However, most of existing WSC approaches assume a centralised service repository for the composition, which is unrealistic for WSC and even more unsuitable for DWSC where the location of data and Web services is a fundamental element. Only a small number approaches have addressed the composition problem considering the distributed nature of Web services [2], [16]. Indirect representation was successfully applied to distributed DWSC [2], and the initial population of GA has been created with the help of clustering, where Web services have been grouped into clusters based on their relative geographical distances.…”

mentioning

confidence: 99%

“…Additionally, the effectiveness of considering distance in distributed DWSC has been verified in [2], where the distance between services has been applied as a heuristic in creating the initial population for GA with fixed-length chromosomes. In another research, the distance between services has been applied to design crossover and local search operators for MA [16].…”

mentioning

confidence: 99%

See 4 more Smart Citations

Composing Distributed Data-intensive Web Services Using a Flexible Memetic Algorithm

Sadeghiram

Chen

2019

2019 IEEE Congress on Evolutionary Computation (CEC)

Self Cite

View full text Add to dashboard Cite

Web Service Composition (WSC) is a particularly promising application of Web services, where multiple individual services with specific functionalities are composed to accomplish a more complex task, which must fulfil functional requirements and optimise Quality of Service (QoS) attributes, simultaneously. Additionally, large quantities of data, produced by technological advances, need to be exchanged between services. Data-intensive Web services, which manipulate and deal with those data, are of great interest to implement data-intensive processes, such as distributed Data-intensive Web Service Composition (DWSC). Researchers have proposed Evolutionary Computing (EC) fullyautomated WSC techniques that meet all the above factors. Some of these works employed Memetic Algorithms (MAs) to enhance the performance of EC through increasing its exploitation ability of in searching neighbourhood area of a solution. However, those works are not efficient or effective. This paper proposes an MA-based approach to solving the problem of distributed DWSC in an effective and efficient manner. In particular, we develop an MA that hybridises EC with a flexible local search technique incorporating distance of services. An evaluation using benchmark datasets is carried out, comparing existing state-ofthe-art methods. Results show that our proposed method has the highest quality and an acceptable execution time overall.

show abstract

Section: Memetic Algorithm For Dwscmentioning

confidence: 99%

mentioning

confidence: 99%