Multi-criteria Web Services Selection: Balancing the Quality of Design and Quality of Service

Web service composition allows developers to create applications via reusing available services that are interoperable to each other. The process of selecting relevant Web services for a composite service satisfying the developer requirements is commonly acknowledged to be hard and challenging, especially with the exponentially increasing number of available Web services on the Internet. The majority of existing approaches on Web Services Selection are merely based on the Quality of Service (QoS) as a basic criterion to guide the selection process. However, existing approaches tend to ignore the service design quality, which plays a crucial role in discovering, understanding, and reusing service functionalities. Indeed, poorly designed Web service interfaces result in service anti-patterns, which are symptoms of bad design and implementation practices. The existence of anti-pattern instances in Web service interfaces typically complicates their reuse in real-world service-based systems and may lead to several maintenance and evolution problems. To address this issue, we introduce a new approach based on the Multi-Objective and Optimization on the basis of Ratio Analysis method (MOORA) as a multi-criteria decision making (MCDM) method to select Web services based on a combination of their (1) QoS attributes and (2) QoS design. The proposed approach aims to help developers to maintain the soundness and quality of their service composite development processes. We conduct a quantitative and qualitative empirical study to evaluate our approach on a Quality of Web Service dataset. We compare our MOORA-based approach against four commonly used MCDM methods as well as a recent state-of-the-art Web service selection approach. The obtained results show that our approach outperforms state-of-the-art approaches by significantly improving the service selection quality of top- k selected services while providing the best trade-off between both service design quality and desired QoS values. Furthermore, we conducted a qualitative evaluation with developers. The obtained results provide evidence that our approach generates a good trade-off for what developers need regarding both QoS and quality of design. Our selection approach was evaluated as “relevant” from developers point of view, in improving the service selection task with an average score of 3.93, compared to an average of 2.62 for the traditional QoS-based approach.

Using Ensemble and TOPSIS with AHP for Classification and Selection of Web Services

Due to the increasing number of Web Services with the same functionality, selecting a Web Service that best serves the needs of the Web Client has become a tremendously challenging task. Present approaches use non-functional parameters of the Web Services but they do not consider any preprocessing of the set of functionally Similar Web Services. The lack of preprocessing results in increased use of computational resources due to unnecessary processing of Web Services that have a very low to no chance of satisfying the consumer’s requirements. In this paper, we propose an Ensemble classification method for preprocessing and a Web Service Selection method based on the Quality of Service (QoS) parameters. Once the most eligible Web Services are enumerated through classification, they are ranked using the Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) method with Analytic Hierarchy Process (AHP) used for weight calculation. A prototype of the method is developed, and experiments are conducted on a real-world Web Services dataset. Results demonstrate the feasibility of the proposed method.

Trusted Service Evaluation for Mobile Edge Users: Challenges and Reviews

With the increasing growth of web services shared in various mobile edge platforms, it becomes necessary to evaluate all the candidates based on their quality of services to reduce the users’ service selection cost. However, the service quality data released by service providers cannot be simply deemed as trusted due to various subjective or objective reasons, which further produce a series of serious trust-aware service evaluation problems, including service quality data sparsity and lack of feedback incentive. In view of this, we summarize the challenging issues existing in the current research field of trusted mobile edge service evaluation. Afterward, we review the current research status of the trusted service evaluation in the mobile edge environment and discuss one of the typical application scenarios based on trusted service evaluation, that is, recommender systems, as well as their diverse categories. We believe this research could be helpful in assisting a mobile edge platform to build a trusted reputation system for various smart applications hosted in the mobile edge platform.

Intelligent Service Selection in a Multi-Dimensional Environment of Cloud Providers for Internet of Things Stream Data through Cloudlets

The expansion of Internet of Things (IoT) services and the huge amount of data generated by different sensors signify the importance of cloud computing services such as Storage as a Service more than ever. IoT traffic imposes such extra constraints on the cloud storage service as sensor data preprocessing capability and load-balancing between data centers and servers in each data center. Furthermore, service allocation should be allegiant to the quality of service (QoS). In the current work, an algorithm is proposed that addresses the QoS in storage service allocation. The proposed hybrid multi-objective water cycle and grey wolf optimizer (MWG) considers different QoS objectives (e.g., energy, processing time, transmission time, and load balancing) in both the fog and cloud Layers, which were not addressed altogether. The MATLAB script is used to simulate and implement our algorithms, and services of different servers, e.g., Amazon, Dropbox, Google Drive, etc., are considered. The MWG has 7%, 13%, and 25% improvement, respectively, in comparison with multi-objective water cycle algorithm (MOWCA), k-means based GA (KGA), and non-dominated sorting genetic algorithm (NSGAII) in metric of spacing. Moreover, the MWG has 4%, 4.7%, and 7.3% optimization in metric of quality in comparison to MOWCA, KGA, and NSGAII, respectively. The new hybrid algorithm, MWG, not only yielded to the consideration of three objectives in service selection but also improved the performance compared to the works that considered one or two objective(s). The overall optimization shows that the MWG algorithm has 7.8%, 17%, and 21.6% better performance than MOWCA, KGA, and NSGAII in the obtained best result by considering different objectives, respectively.

Intelligent Government Control System Construction Based on 5G IoT

This paper presents an in-depth analysis of the construction of an intelligent government control system in the context of 5G IoT. The research has conducted performance tests and network tests on the samples of the components which debugged the problems that occurred during the tests and analyzed and improved the system. The system designed in this study is not only easy to maintain but also very reliable and safe, with a high level of accuracy, and can be used for remote “five remote” and management of switchgear and other related power equipment. Based on this model, a dual middleware PaaS service selection algorithm is proposed, and a utility evaluation strategy is used to load balance the PaaS service. The test results show that the DMPS algorithm has a high selection accuracy and load balancing capability. Combined with the experience of local government investment and financing platform financing risk management and control practices, the financing risk control system established through the study is made more feasible. From the development history of local government investment and financing platforms, we study local government investment and financing platforms from the perspective of historical development and explore the root causes of their high financing risks and possible defects in the management process of daily work. Concerning the existing laws and regulations, practical operation norms, the framework of the local government investment and financing platform system, and other objective conditions, we start to build a financing risk control system for local government investment and financing platforms from both practical and operational management aspects, to find a financing risk control system that is in line with the regulations and effective. Finally, the system will be put into practice, and the effectiveness of the system will be tested by using the simulation operation method, and the results will be adjusted in time for the shortcomings of the system. The system is expected to help local government investment and financing platforms to reduce their risks so that they can provide better services for urban infrastructure construction and become a solid link in the economic development chain.