scholarly journals An Intelligent Cloud Service Composition Optimization Using Spider Monkey and Multistage Forward Search Algorithms

Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 82
Author(s):  
Hassan Tarawneh ◽  
Issam Alhadid ◽  
Sufian Khwaldeh ◽  
Suha Afaneh

Web service composition allows developers to create and deploy applications that take advantage of the capabilities of service-oriented computing. Such applications provide the developers with reusability opportunities as well as seamless access to a wide range of services that provide simple and complex tasks to meet the clients’ requests in accordance with the service-level agreement (SLA) requirements. Web service composition issues have been addressed as a significant area of research to select the right web services that provide the expected quality of service (QoS) and attain the clients’ SLA. The proposed model enhances the processes of web service selection and composition by minimizing the number of integrated Web Services, using the Multistage Forward Search (MSF). In addition, the proposed model uses the Spider Monkey Optimization (SMO) algorithm, which improves the services provided with regards to fundamentals of service composition methods symmetry and variations. It achieves that by minimizing the response time of the service compositions by employing the Load Balancer to distribute the workload. It finds the right balance between the Virtual Machines (VM) resources, processing capacity, and the services composition capabilities. Furthermore, it enhances the resource utilization of Web Services and optimizes the resources’ reusability effectively and efficiently. The experimental results will be compared with the composition results of the Smart Multistage Forward Search (SMFS) technique to prove the superiority, robustness, and effectiveness of the proposed model. The experimental results show that the proposed SMO model decreases the service composition construction time by 40.4%, compared to the composition time required by the SMFS technique. The experimental results also show that SMO increases the number of integrated ted web services in the service composition by 11.7%, in comparison with the results of the SMFS technique. In addition, the dynamic behavior of the SMO improves the proposed model’s throughput where the average number of the requests that the service compositions processed successfully increased by 1.25% compared to the throughput of the SMFS technique. Furthermore, the proposed model decreases the service compositions’ response time by 0.25 s, 0.69 s, and 5.35 s for the Excellent, Good, and Poor classes respectively compared to the results of the SMFS Service composition response times related to the same classes.

2021 ◽  
Author(s):  
◽  
Yang Yu

<p>Web service composition has become a promising technique to build powerful enterprise applications by making use of distributed services with different functions. In the age of big data, more and more web services are created to deal with a large amount of data, which are called data-intensive services. Due to the explosion in the volume of data, providing efficient approaches to composing data-intensive services will become more and more important in the field of service-oriented computing. Meanwhile, as numerous web services have been emerging to offer identical or similar functionality on the Internet, web service composition is usually performed with end-to-end Quality of Service (QoS) properties which are adopted to describe the non-functional properties (e.g., response time, execution cost, reliability, etc.) of a web service. In addition, the executions of composite web services are typically coordinated by a centralized workflow engine. As a result, the centralized execution paradigm suffers from inefficient communication and a single point of failure. This is particularly problematic in the context of data-intensive processes. To that end, more decentralized and flexible execution paradigms are required for the execution of data-intensive applications.  From a computational point of view, the problems of QoS-aware data-intensive web service composition and execution can be characterised as complex, large-scale, constrained and multi-objective optimization problems. Therefore, genetic programming (GP) based solutions are presented in this thesis to address the problems. A series of simulation experiments are provided to demonstrate the performance of the proposed approaches, and the empirical observations are also described in this thesis.  Firstly, we propose a hybrid approach that integrates the local search procedure of tabu search into the global search process of GP to solving the problem of QoS-aware data-intensive web service composition. A mathematical model is developed for considering the mass data transmission across different component services in a data-intensive service composition. The experimental results show that our proposed approach can provide better performance than the standard GP approach and two traditional optimization methods.  Next, a many-objective evolutionary approach is proposed for tackling the QoS-aware data-intensive service composition problem having more than three competing quality objectives. In this approach, the original search space of the problem is reduced before a recently developed many-objective optimization algorithm, NSGA-III, is adopted to solve the many-objective optimization problem. The experimental results demonstrate the effectiveness of our approach, as well as its superiority than existing single-objective and multi-objective approaches.  Finally, a GP-based approach to partitioning a composite data-intensive service for decentralized execution is put forth in this thesis. Similar to the first problem, a mathematical model is developed for estimating the communication overhead inside a partition and across the partitions. The data and control dependencies in the original composite web service can be properly preserved in the deployment topology generated by our approach. Compared with two existing heuristic algorithms, the proposed approach exhibits better scalability and it is more suitable for large-scale partitioning problems.</p>


2021 ◽  
Author(s):  
◽  
Yang Yu

<p>Web service composition has become a promising technique to build powerful enterprise applications by making use of distributed services with different functions. In the age of big data, more and more web services are created to deal with a large amount of data, which are called data-intensive services. Due to the explosion in the volume of data, providing efficient approaches to composing data-intensive services will become more and more important in the field of service-oriented computing. Meanwhile, as numerous web services have been emerging to offer identical or similar functionality on the Internet, web service composition is usually performed with end-to-end Quality of Service (QoS) properties which are adopted to describe the non-functional properties (e.g., response time, execution cost, reliability, etc.) of a web service. In addition, the executions of composite web services are typically coordinated by a centralized workflow engine. As a result, the centralized execution paradigm suffers from inefficient communication and a single point of failure. This is particularly problematic in the context of data-intensive processes. To that end, more decentralized and flexible execution paradigms are required for the execution of data-intensive applications.  From a computational point of view, the problems of QoS-aware data-intensive web service composition and execution can be characterised as complex, large-scale, constrained and multi-objective optimization problems. Therefore, genetic programming (GP) based solutions are presented in this thesis to address the problems. A series of simulation experiments are provided to demonstrate the performance of the proposed approaches, and the empirical observations are also described in this thesis.  Firstly, we propose a hybrid approach that integrates the local search procedure of tabu search into the global search process of GP to solving the problem of QoS-aware data-intensive web service composition. A mathematical model is developed for considering the mass data transmission across different component services in a data-intensive service composition. The experimental results show that our proposed approach can provide better performance than the standard GP approach and two traditional optimization methods.  Next, a many-objective evolutionary approach is proposed for tackling the QoS-aware data-intensive service composition problem having more than three competing quality objectives. In this approach, the original search space of the problem is reduced before a recently developed many-objective optimization algorithm, NSGA-III, is adopted to solve the many-objective optimization problem. The experimental results demonstrate the effectiveness of our approach, as well as its superiority than existing single-objective and multi-objective approaches.  Finally, a GP-based approach to partitioning a composite data-intensive service for decentralized execution is put forth in this thesis. Similar to the first problem, a mathematical model is developed for estimating the communication overhead inside a partition and across the partitions. The data and control dependencies in the original composite web service can be properly preserved in the deployment topology generated by our approach. Compared with two existing heuristic algorithms, the proposed approach exhibits better scalability and it is more suitable for large-scale partitioning problems.</p>


2010 ◽  
Vol 7 (3) ◽  
pp. 73-92
Author(s):  
Puwei Wang ◽  
Zhi Jin ◽  
Lin Liu ◽  
Budan Wu

Precise capability specification is the key for identifying and composing the right Web services. This paper specifies service capabilities in terms of the environment entities from the application domain and the effects imposed by the Web service on these entities. An environment ontology for Web services is adopted to provide formal sharable representations of the domain-specific environment entities. A hierarchical state machine is constructed for each environment entity to describe its behaviors, and the effects imposed by a Web service are described as the state transitions traces of environment entities, which define the capability of the Web service. Web service composition that satisfies a set of requested effects is then conducted by reasoning on the effects of services. The proposed approach emphasizes the external manifestation of Web services and service composition based on the effect reasoning. An example of online travel service illustrates the proposed approach.


Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2023
Author(s):  
Issam Alhadid ◽  
Sufian Khwaldeh ◽  
Mohammad Al Rawajbeh ◽  
Evon Abu-Taieh ◽  
Ra’ed Masa’deh ◽  
...  

Service-oriented architecture (SOA) has emerged as a flexible software design style. SOA focuses on the development, use, and reuse of small, self-contained, independent blocks of code called web services that communicate over the network to perform a certain set of simple tasks. Web services are integrated as composite services to offer complex tasks and to provide the expected services and behavior in addition to fulfilling the clients’ requests according to the service-level agreement (SLA). Web service selection and composition problems have been a significant area of research to provide the expected quality of service (QoS) and to meet the clients’ expectations. This research paper presents a hybrid web service composition model to solve web service selection and composition problems and to optimize web services’ resource utilization using k-means clustering and knapsack algorithms. The proposed model aims to maximize the service compositions’ QoS and minimize the number of web services integrated within the service composition using the knapsack algorithm. Additionally, this paper aims to track the service compositions’ QoS attributes by evaluating and tracking the web services’ QoS using the reward function and, accordingly, use the k-means algorithm to decide to which cluster the web service belongs. The experimental results on a real dataset show the superiority and effectiveness of the proposed algorithm in comparison with the results of the state–action–reward–state–action (SARSA) and multistage forward search (MFS) algorithms. The experimental results show that the proposed model reduces the average time of the web service selection and composition processes to 37.02 s in comparison to 47.03 s for the SARSA algorithm and 42.72 s for the MFS algorithm. Furthermore, the average of web services’ resource utilization results increased by 4.68% using the proposed model in comparison to the resource utilization by the SARSA and MFS algorithms. In addition, the experimental results showed that the average number of service compositions using the proposed model improved by 26.04% compared with the SARSA and MFS algorithms.


Author(s):  
Puwei Wang ◽  
Zhi Jin ◽  
Lin Liu ◽  
Budan Wu

Precise capability specification is the key for identifying and composing the right Web services. This paper specifies service capabilities in terms of the environment entities from the application domain and the effects imposed by the Web service on these entities. An environment ontology for Web services is adopted to provide formal sharable representations of the domain-specific environment entities. A hierarchical state machine is constructed for each environment entity to describe its behaviors, and the effects imposed by a Web service are described as the state transitions traces of environment entities, which define the capability of the Web service. Web service composition that satisfies a set of requested effects is then conducted by reasoning on the effects of services. The proposed approach emphasizes the external manifestation of Web services and service composition based on the effect reasoning. An example of online travel service illustrates the proposed approach.


2021 ◽  
Vol 9 (2) ◽  
pp. 65-70
Author(s):  
Laishram Jenny Chanu ◽  
◽  
Arnab Paul ◽  

Lots of Web Services are available which differ in their QoS values but can perform a similar task. Discovery mechanism selects the best Web Service according to their QoS values and functional attributes. Cases arise, where the discovery mechanism fails, as a user’s complex query cannot be satisfied by a single Web Service. This can be solved by Web Service composition where multiple Web Services are combined to give a composite Web Service which meet user’s complex query. Our work is mainly focused on composition of Web Services that efficiently meets the user’s query. Different algorithms have been discussed and used by different researchers in this field. One of the most blooming topics is the use of evolutionary algorithms in optimization problems. In our work, we have chosen Particle Swarm Optimization Algorithm approach to discover the best efficient composition. Then, Weight Improved Particle Swarm Optimization Algorithm is used to improve the results which were found to be quite satisfying and efficient.


Author(s):  
Manuel Palomo-Duarte

Web services are changing software development thanks to their loosely coupled nature and simple adoption. They can be easily composed to create new more powerful services, allowing for large programming systems. Verification and validation techniques try to find defects in a program to minimize losses that its malfunction could cause. Although many different approaches have been developed for “traditional” program testing, none of them have proven definitive. The problem is even more challenging for new paradigms like web services and web service compositions, because of their dynamic nature and uncommon web service-specific instructions. This chapter surveys the different approaches to web service and web service composition verification and validation, paying special attention to automation. When no tools are available for a given technique, academic efforts are discussed, and challenges are presented.


2011 ◽  
pp. 739-758 ◽  
Author(s):  
Seog-Chan Oh ◽  
Dongwon Lee

In this article, a novel benchmark toolkit, WSBen, for testing web services discovery and composition algorithms is presented. The WSBen includes: (1) a collection of synthetically generated web services files in WSDL format with diverse data and model characteristics; (2) queries for testing discovery and composition algorithms; (3) auxiliary files to do statistical analysis on the WSDL test sets; (4) converted WSDL test sets that conventional AI planners can read; and (5) a graphical interface to control all these behaviors. Users can finetune the generated WSDL test files by varying underlying network models. To illustrate the application of the WSBen, in addition, we present case studies from three domains: (1) web service composition; (2) AI planning; and (3) the laws of networks in Physics community. It is our hope that WSBen will provide useful insights in evaluating the performance of web services discovery and composition algorithms. The WSBen toolkit is available at: http://pike.psu.edu/sw/wsben/.


Author(s):  
Arion de Campos Jr. ◽  
Aurora T. R. Pozo ◽  
Silvia R. Vergilio

The Web service composition refers to the aggregation of Web services to meet customers' needs in the construction of complex applications. The selection among a large number of Web services that provide the desired functionalities for the composition is generally driven by QoS (Quality of Service) attributes, and formulated as a constrained multi-objective optimization problem. However, many equally important QoS attributes exist and in this situation the performance of the multi-objective algorithms can be degraded. To deal properly with this problem we investigate in this chapter a solution based in many-objective optimization algorithms. We conduct an empirical analysis to measure the performance of the proposed solution with the following preference relations: Controlling the Dominance Area of Solutions, Maximum Ranking and Average Ranking. These preference relations are implemented with NSGA-II using five objectives. A set of performance measures is used to investigate how these techniques affect convergence and diversity of the search in the WSC context.


2014 ◽  
Vol 11 (2) ◽  
pp. 67-84 ◽  
Author(s):  
Tanveer Ahmed ◽  
Abhishek Srivastava

Service oriented architecture has revolutionized the way a traditional business process is executed. The success of this architecture is Indue to the composition of multiple heterogeneous services at runtime. Web service composition is a mechanism where several web services are combined at runtime to build a complex application for a user. It is one of the most sought after processes in the context of semantic web. But, composition of web services at runtime is a difficult task owing to the availability of multiple service providers offering the same functionality. The process if exasperated by due conflicting preferences of a service consumer. In this paper, the authors address the issue of selecting a service based on Quality of Service (QoS) attributes. They utilize concepts customized from physics to create an environment that facilitates the selection of a best service from the set of similar services. The technique not only facilitates the selection of the service with the best QoS attributes, but distributes the load among expeditiously. Here in this paper, the authors concentrate on minimizing and equitably balancing the waiting time for a user. They conduct in silico experiments on multiple workflows to demonstrate the efficacy of the proposed technique to balance load efficiently among similar service offerings.


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