Статті в журналах: "Cloud service discovery"

1

Khan, Gitosree, Anirban Sarkar, and Sabnam Sengupta. "HBSD." International Journal of Information Technology and Web Engineering 14, no. 3 (July 2019): 37–63. http://dx.doi.org/10.4018/ijitwe.2019070103.

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Enterprise cloud bus (ECBS) is a multi-agent-based abstraction layer framework, responsible for publishing and discovery of services in an Inter-cloud environment. Our work focuses on the service discovery model (HBSD) using Hadoop that leads to the challenges of automatic web service discovery patterns. It has been observed that the RDBMS can handle only data sizes up to a few Terabytes but fails to scale beyond that, so Apache Hadoop can be used for parallel processing of massive datasets. This article provides a novel Hadoop based Service Discovery (HBSD) approach that can handle vast amount of datasets generated from heterogeneous cloud services. The novelty of the proposed architecture coordinates cloud participants, automate service registration pattern, reconfigure discover services and focus on aggregating heterogeneous services from Inter-cloud environments. Moreover, this particle states a novel and efficient algorithm (HBSDMCA) for finding the appropriate service as per user's requirements that can provide higher QoS to the user request for web services.

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2

Zhang, Jie, Li Wen He, Fei Yi Huang, and Bin Liu. "Service Discovery Architecture Applied in Cloud Computing Environments." Applied Mechanics and Materials 241-244 (December 2012): 3177–83. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.3177.

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This paper proposed a service discovery architecture (SDA) that can be applied in cloud computing environments. This architecture supports common service discovery capabilities to achieve cloud service discovery function in cloud computing environments. The main idea is that, cloud services can be divided into different cloud service domains (CSD) according to the characteristics of the functions of cloud services, each CSD has a sub-service directory, and there is also a root service directory above all sub-service directories. Setting of two-level service directories can achieve the most suitable massive cloud services quickly. Finally, through mathematical modeling, theoretical analyses, and numerical simulations, the performance analyses of the architecture are studied. The results show the validity and advantages of the SDA.

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3

Wan, Zhitao, Ping Wang, Lihua Duan, Fan Jing Meng, and Jing Min Xu. "Graph Similarity based Cloud Migration Service Composition Pattern Discovery." International Journal of Web Services Research 12, no. 2 (April 2015): 26–46. http://dx.doi.org/10.4018/ijwsr.2015040102.

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The demands of migrating on-premises complex enterprise applications to cloud dramatically increase with the wide adoption of cloud computing. A recent research validates the possibility of combining multiple proprietary migration services offered by different vendors together to complete cloud migration. Pattern based service composition has been proven as an appealing approach to accelerate the service composition and ensure the qualities in the Service Oriented Architecture (SOA) domain and can be applied to the cloud migration service composition theoretically. However, current pattern discovery approaches are not applicable for the cloud migration due to lack of either existing cloud migration business process knowledge or execution logs. This paper proposes a novel approach to discover cloud migration patterns from a set of service composition solutions. The authors formalize the pattern discovery as a special graph similarity matching problem and present an algorithm to calculate the similarities of these service composition solutions. Patterns are chosen out of the solutions by similarity under designed criteria. The benchmark results and quantitative analysis show that our proposed approach is effective and efficient in pattern discovery for cloud migration service composition.

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4

Mohammed, Fathey, Abdullah Marish Ali, Abdullah Saad Al-Malaise Al-Ghamdi, Fawaz Alsolami, Siti Mariyam Shamsuddin, and Fathy E. Eassa. "Cloud Computing Services: Taxonomy of Discovery Approaches and Extraction Solutions." Symmetry 12, no. 8 (August 13, 2020): 1354. http://dx.doi.org/10.3390/sym12081354.

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Cloud computing offers new features of sharing resources and applications to meet users’ computing requirements. It is a model by which the users can access computing resources as services offered on the Internet (cloud services). Cloud service providers offer a highly diverse range of asymmetric cloud services with heterogeneous features, which makes it difficult for the users to find the best service that fits his needs. Many research studies have been done on cloud service discovery, and several models and solutions that applied different techniques have been proposed. This paper aims at presenting the state of the art in the area of cloud services discovery by exploring the current approaches, techniques, and models. Furthermore, it proposes a taxonomy of cloud service discovery approaches. An integrative review approach was used to explore the related literature. Then, by analyzing the existing cloud service discovery solutions, a taxonomy of discovery approaches was suggested based on several perspectives including the discovery environment and the discovery process methods. The proposed taxonomy allows easily classifying and comparing cloud services discovery solutions. Moreover, it may reveal issues and gaps for further research and expose new insights for more innovative and effective cloud services discovery solutions.

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5

Singh, Gagan, Nimrat Kaur, and Manpreet Kaur. "Toward a Unified Ontology of Cloud Computing." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 2 (October 30, 2012): 271–74. http://dx.doi.org/10.24297/ijct.v3i2b.2874.

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The emergences of cloud computing deals in various internet applications developers for hosting various applications which users are in need in this day to day life.the idea is cloud ontology for easy Selection, Publication and Discovery in cloud services. Query Processing Agent, Ontological Similarities.In this paper, purposal is an cloud service discovery system with ontological model, in order to solve,for example: A job site, Itâ€™s not an ordinary jobsite but focusing and specializing in matching the users or clients queries related to jobs and displaying the information even by giving options of updating their information which is needed for this Job Domain. This paper implements the cloud ontology technique to make cloud service discovery system efficient for user query in job site. The aim of this paper is to determine how the CSDS with the Cloud ontology achieved better performance than the CSDS without the Cloud ontology. By consulting a Cloud ontology to reason and to rating about the relations among Cloud services, the CSDS is more successful in locating Cloud services and more likely to discover Cloud services that meet consumersâ€Ÿ requirements.

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6

S, Dhanasekaran, and Vasudevan V. "The supreme agent strategy for efficient searching and manifesting vital cloud services." International Journal of Engineering & Technology 7, no. 1.9 (March 1, 2018): 182. http://dx.doi.org/10.14419/ijet.v7i1.9.9816.

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The supreme agent technique deals with devise and magnification of software agents for effectively discovery appropriate cloud services, cloud service agreement and cloud service assortment. This research work establishing an agent based strategy for composing variety of relevant cloud services and provides unified virtualized service to the cloud customers in a effective manner. The contribution of research work includes developing cloud service search engine for efficient cloud service discovery, and dealing both provider and consumer by means of supreme agent strategy. This supreme agent scheme uses an enhanced fuzzy based ranking algorithm. This supreme agent system works on behalf of cloud user and provider to list out various cloud providers with necessary information to enable the user to choose relevant cloud service in a reasonable time period. Cloud agreement mechanism facilitates the agreement activities among client agent & intermediate agent also among intermediate agent & supplier agent. Cloud service assortment facilitate the agent vigorously choose the Cloud services and records the display the available cloud services.

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7

Ben bezziane, Mohamed, Ahmed Korichi, Chaker Abdelaziz Kerrache, and Mohamed el Amine Fekair. "RCVC: RSU-Aided Cluster-Based Vehicular Clouds Architecture for Urban Areas." Electronics 10, no. 2 (January 15, 2021): 193. http://dx.doi.org/10.3390/electronics10020193.

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As a promising topic of research, Vehicular Cloud (VC) incorporates cloud computing and ad-hoc vehicular network (VANET). In VC, supplier vehicles provide their services to consumer vehicles in real-time. These services have a significant impact on the applications of internet access, storage and data. Due to the high-speed mobility of vehicles, users in consumer vehicles need a mechanism to discover services in their vicinity. Besides this, quality of service varies from one supplier vehicle to another; thus, consumer vehicles attempt to pick out the most appropriate services. In this paper, we propose a novel protocol named RSU-aided Cluster-based Vehicular Clouds protocol (RCVC), which constructs the VC using the Road Side Unit (RSU) directory and Cluster Head (CH) directory to make the resources of supplier vehicles more visible. While clusters of vehicles that move on the same road form a mobile cloud, the remaining vehicles form a different cloud on the road side unit. Furthermore, the consumption operation is achieved via the service selection method, which is managed by the CHs and RSUs based on a mathematical model to select the best services. Simulation results prove the effectiveness of our protocol in terms of service discovery and end-to-end delay, where we achieved service discovery and end-to-end delay of 3 × 10−3 s and 13 × 10−2 s, respectively. Moreover, we carried out an experimental comparison, revealing that the proposed method outperformed several states of the art protocols.

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8

Zhu, Huamin, Lifa Wu, Kangyu Huang, and Zhenji Zhou. "Research on Methods for Discovering and Selecting Cloud Infrastructure Services Based on Feature Modeling." Mathematical Problems in Engineering 2016 (2016): 1–19. http://dx.doi.org/10.1155/2016/8194832.

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Nowadays more and more cloud infrastructure service providers are providing large numbers of service instances which are a combination of diversified resources, such as computing, storage, and network. However, for cloud infrastructure services, the lack of a description standard and the inadequate research of systematic discovery and selection methods have exposed difficulties in discovering and choosing services for users. First, considering the highly configurable properties of a cloud infrastructure service, the feature model method is used to describe such a service. Second, based on the description of the cloud infrastructure service, a systematic discovery and selection method for cloud infrastructure services are proposed. The automatic analysis techniques of the feature model are introduced to verify the model’s validity and to perform the matching of the service and demand models. Finally, we determine the critical decision metrics and their corresponding measurement methods for cloud infrastructure services, where the subjective and objective weighting results are combined to determine the weights of the decision metrics. The best matching instances from various providers are then ranked by their comprehensive evaluations. Experimental results show that the proposed methods can effectively improve the accuracy and efficiency of cloud infrastructure service discovery and selection.

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9

Lei, Yu, and Duan Yucong. "Trusted Service Provider Discovery Based on Data, Information, Knowledge, and Wisdom." International Journal of Software Engineering and Knowledge Engineering 31, no. 01 (January 2021): 3–19. http://dx.doi.org/10.1142/s0218194021400015.

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Data, information, knowledge, and wisdom forms a progressive relationship. Information is formed by data collation. Knowledge is filtered, refined, and processed from relevant information. Wisdom is based on knowledge and is accumulated through experience. This paper uses the progressive relationship of service data, information, knowledge, and wisdom to explain the expression of service knowledge graph. It is an increasingly challenging demand to discover trusted Cloud service providers with service data, information, and knowledge. We propose an efficient method of trusted service provider discovery based on service knowledge graphs, called PDG (Provider Discovery based on Graphs), to ensure that each service instance of composite services in Cloud systems is trustworthy. PDG evaluates the outputs of service providers in service classes with the help of additional service information. According to the additional service information, service knowledge is generated and trusted service providers can be found easily. PDG improves the accuracy of processing results by automatically replacing data provided by untrusted service providers with results provided by trusted service providers.

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10

Al-Sayed, Mustafa M., Hesham A. Hassan, and Fatma A. Omara. "An intelligent cloud service discovery framework." Future Generation Computer Systems 106 (May 2020): 438–66. http://dx.doi.org/10.1016/j.future.2019.12.027.

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11

Heidari, Arash, and Nima Jafari Navimipour. "A new SLA-aware method for discovering the cloud services using an improved nature-inspired optimization algorithm." PeerJ Computer Science 7 (May 10, 2021): e539. http://dx.doi.org/10.7717/peerj-cs.539.

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Cloud computing is one of the most important computing patterns that use a pay-as-you-go manner to process data and execute applications. Therefore, numerous enterprises are migrating their applications to cloud environments. Not only do intensive applications deal with enormous quantities of data, but they also demonstrate compute-intensive properties very frequently. The dynamicity, coupled with the ambiguity between marketed resources and resource requirement queries from users, remains important issues that hamper efficient discovery in a cloud environment. Cloud service discovery becomes a complex problem because of the increase in network size and complexity. Complexity and network size keep increasing dynamically, making it a complex NP-hard problem that requires effective service discovery approaches. One of the most famous cloud service discovery methods is the Ant Colony Optimization (ACO) algorithm; however, it suffers from a load balancing problem among the discovered nodes. If the workload balance is inefficient, it limits the use of resources. This paper solved this problem by applying an Inverted Ant Colony Optimization (IACO) algorithm for load-aware service discovery in cloud computing. The IACO considers the pheromones’ repulsion instead of attraction. We design a model for service discovery in the cloud environment to overcome the traditional shortcomings. Numerical results demonstrate that the proposed mechanism can obtain an efficient service discovery method. The algorithm is simulated using a CloudSim simulator, and the result shows better performance. Reducing energy consumption, mitigate response time, and better Service Level Agreement (SLA) violation in the cloud environments are the advantages of the proposed method.

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12

Ali, Abdullah Marish, Siti Mariyam Shamsuddin, Fathy E. Eassa, Faisal Saeed, Madini O. Alassafi, Tawfik Al-Hadhrami, and Ahmed M. Elmisery. "Towards an Intelligent Framework for Cloud Service Discovery." International Journal of Cloud Applications and Computing 11, no. 3 (July 2021): 33–57. http://dx.doi.org/10.4018/ijcac.2021070103.

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The variety of cloud services (CSs) that are described, their non-uniform naming conventions, and their heterogeneous types and features make cloud service discovery a difficult problem. Therefore, an intelligent cloud service discovery framework (CSDF) is needed for discovering the appropriate services that meet the user's requirements. This study proposes a CSDF for extracting cloud service attributes (CSAs) based on classification, ontology, and agents. Multiple-phase classification with topic modeling has been implemented using different machine learning techniques to increase the efficiency of CSA extraction. CSAs that are represented in different formats have been extracted and represented in a comprehensive ontology to enhance the efficiency and effectiveness of the framework. The experimental results showed that the multiple-phase classification methods with topic modeling for CSs using a support vector machine (SVM) obtained a high accuracy (87.90%) compared to other methods. In addition, the results of extracting CSAs showed high values for precision, recall, and f-measure of 99.24%, 99.24%, and 99.24%, respectively, for Java script object notation(JSON) format, followed by 99.05%, 97.20%, and 98.11% for table formats, and with lower accuracy for text format (90.63%, 86.57%, and 88.55%).

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13

Yang, Chen, and Zhong Jie Wang. "Research on the Cloud Manufacturing Service Discovery for Industry Manufacturing System Based on Ontology." Advanced Materials Research 712-715 (June 2013): 2639–43. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.2639.

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With the development of manufacturing globalization, cloud manufacturing is becoming a hotspot of network manufacturing. In cloud manufacturing, how to response to users services demands fast and accurately is an important indicator to evaluate the performance of this system. To achieve a cloud manufacturing platform for industry manufacturing system, this paper proposes service-oriented platform architecture based on semantic. Also, to realize the manufacturing resource data virtualization, the semantic description of manufacturing cloud and the combined manufacturing ontology is established. To fulfill the requirements of providing the fit cloud service or service combination, a cloud manufacturing service discovery model is investigated on focus, the organic decomposition and combination of manufacturing cloud is completed by ontology reasoning, and intelligent search and automatic matching of manufacturing cloud is realized.

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14

Arun, Siddharth, Aakash Chandrasekaran, and Prakash P. "CSIS: Cloud Service Identification System." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (February 1, 2017): 513. http://dx.doi.org/10.11591/ijece.v7i1.pp513-520.

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To meet the need of the computational power, most of the users may go for a cloud based services for its scalability, flexibility and reliability. Cloud services have become an integral part of IT and analytical enterprises. Owing to increase in necessity of commercial cloud products being readily available, it has become extremely difficult for users to identify suitable cloud services. This paper proposes the recommender system precisely designed for the discovery of cloud services. Though there is an exponential increase in demand for cloud services, the amount of research done in this particular field is abysmal. Cloud Service Identification System (CSIS) crawls through Internet, identifies cloud services and stores them in a database. The user’s search query is processed and recommends cloud services accurately.

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15

Hu, Guang Chang, Bu Dan Wu, and Jun Liang Chen. "Service Discovery Based on Self-Evolution of Domain Ontology and Cloud Migration of Web Service." Applied Mechanics and Materials 543-547 (March 2014): 2915–19. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2915.

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To meet the demand of the higher precision ratio and recall ratio of service search, a method of Web service discovery is proposed based on ontology evolution and Web service migration. According to the developed cloud service platform and the existed service repository and domain ontology list, a service migration process is proposed which migrate to the cloud platform and implement unified management for Web service. This process effectively achieves that Web services migrate in and out of the cloud platform. In order to realize the self-evolution of domain ontology, an ontology alignment mechanism is designed to automatic extend and replace of ontology concept. This mechanism achieves the integration of different keywords with the same meaning and ensures the consistency of ontology concept. In this paper, the method not only enables efficient service discovery and dynamic service management, but also can achieve high concurrency support of services and supply or billing on demand. The experiments show that the proposed method solves the search problem of low efficiency based on keyword, and it effectively improves the precision ratio and recall ratio of service discovery.

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Elgazzar, Khalid, Hossam S. Hassanein, and Patrick Martin. "DaaS: Cloud-based mobile Web service discovery." Pervasive and Mobile Computing 13 (August 2014): 67–84. http://dx.doi.org/10.1016/j.pmcj.2013.10.015.

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17

Kang, Jaeyong, and Kwang Mong Sim. "Ontology-enhanced agent-based cloud service discovery." International Journal of Cloud Computing 5, no. 1/2 (2016): 144. http://dx.doi.org/10.1504/ijcc.2016.075125.

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Liu, Jin, Jing Zhou, Junfeng Wang, Feng Zhang, and Fei Liu. "Irregular community discovery for cloud service improvement." Journal of Supercomputing 61, no. 2 (June 10, 2010): 317–36. http://dx.doi.org/10.1007/s11227-010-0446-7.

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19

Liu, Xuan, and Wei Tan. "A Model of Competitive Hybrid Granularity Manufacturing Resource and its Unify Cloud Service Modeling." Applied Mechanics and Materials 670-671 (October 2014): 1556–61. http://dx.doi.org/10.4028/www.scientific.net/amm.670-671.1556.

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With the application of cloud computing technology in the manufacturing industry, there appear all sorts of the manufacturing cloud services on the network. Basic of manufacturing cloud service is manufacturing resource, and the business process is the business context of the manufacturing resource. In order to improve the utilization rate of cloud services, a model for the hybrid granularity manufacturing resources with strong competitiveness is put forward, including basic information, basic function, business process and quality of service of manufacturing resource, and based on which cloud manufacturing service model is construct. The service discovery experiment is designed based on the manufacturing cloud service model, and the experimental results prove that the cloud service from strong competitive hybrid granularity manufacturing resource has more competitive power and higher utilization.

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20

Qian, He, Wang Yong, Li Jia, and Cai Mengfei. "Publish/Subscribe and JXTA based Cloud Service Management with QoS." International Journal of Grid and High Performance Computing 8, no. 3 (July 2016): 24–37. http://dx.doi.org/10.4018/ijghpc.2016070102.

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How to manage cloud services efficiently is difficult for large scale of services with frequently changing Quality of Service (QoS) in cloud computing environment. A multiple-dimension publish/subscribe (pub/sub) and JXTA based cloud service management mechanism, consists of registry overlay, service publisher and subscriber, is proposed to manage cloud services with active QoS refreshing and fast subscribe capability. The registry overlay with multiple managers cooperating on JXTA, can manage large scale services discovery. The service model with QoS describes a formal model for pub/sub based service management, and a fast subscribing algorithm with filter matrix and multi-dimension index is proposed. The filter matrix helps to reduce candidate services and the multi-dimension index is used to find satisfied services fast. Based on pub/sub and JXTA, the cloud management system is realized. The experiments show that the proposed cloud service management mechanism has good publication and subscribing performance, and is faster than traditional methods for large scale cloud services.

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21

Zhou, Jiehan, Kumaripaba Athukorala, Ekaterina Gilman, Jukka Riekki, and Mika Ylianttila. "Cloud Architecture for Dynamic Service Composition." International Journal of Grid and High Performance Computing 4, no. 2 (April 2012): 17–31. http://dx.doi.org/10.4018/jghpc.2012040102.

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Service composition provides value-adding services through composing basic Web services, which may be provided by various organizations. Cloud computing presents an efficient managerial, on-demand, and scalable way to integrate computational resources (hardware, platform, and software). However, existing Cloud architecture lacks the layer of middleware to enable dynamic service composition. To enable and accelerate on-demand service composition, the authors explore the paradigm of dynamic service composition in the Cloud for Pervasive Service Computing environments and propose a Cloud-based Middleware for Dynamic Service Composition (CM4SC). In this approach, the authors introduce the CM4SC ‘Composition as a Service’ middleware layer into conventional Cloud architecture to allow automatic composition planning, service discovery and service composition. The authors implement the CM4SC middleware prototype utilizing Windows Azure Cloud platform. The prototype demonstrates the feasibility of CM4SC for accelerating dynamic service composition and that the CM4SC middleware-accelerated Cloud architecture offers a novel way for realizing dynamic service composition.

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22

Aazam, Mohammad, and Eui-Nam Huh. "Framework of Resource Management for Intercloud Computing." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/108286.

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There has been a very rapid increase in digital media content, due to which media cloud is gaining importance. Cloud computing paradigm provides management of resources and helps create extended portfolio of services. Through cloud computing, not only are services managed more efficiently, but also service discovery is made possible. To handle rapid increase in the content, media cloud plays a very vital role. But it is not possible for standalone clouds to handle everything with the increasing user demands. For scalability and better service provisioning, at times, clouds have to communicate with other clouds and share their resources. This scenario is called Intercloud computing or cloud federation. The study on Intercloud computing is still in its start. Resource management is one of the key concerns to be addressed in Intercloud computing. Already done studies discuss this issue only in a trivial and simplistic way. In this study, we present a resource management model, keeping in view different types of services, different customer types, customer characteristic, pricing, and refunding. The presented framework was implemented using Java and NetBeans 8.0 and evaluated using CloudSim 3.0.3 toolkit. Presented results and their discussion validate our model and its efficiency.

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Zeginis, Chrysostomos, Kyriakos Kritikos, and Dimitris Plexousakis. "Event Pattern Discovery in Multi-Cloud Service-Based Applications." International Journal of Systems and Service-Oriented Engineering 5, no. 4 (October 2015): 78–103. http://dx.doi.org/10.4018/ijssoe.2015100104.

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The adoption of Cloud computing in the Service Oriented Architecture (SOA) world is continuously increasing. However, as developers try to optimize their application deployment cost and performance, they may also deploy application parts redundantly on different VMs. In such heterogeneous and distributed environments, it is important to have a clear view of the system's state and its components' interrelationships. This paper aims at proposing a novel monitoring and adaptation framework for Service-based Applications (SBAs) deployed on multiple Clouds. The main functionality of this framework is the discovery of critical event patterns within monitoring event streams, leading to specific Service Level Objective (SLO) violations. Furthermore, two main meta-models are proposed for describing the SBA's components and their dependencies, and the supported adaptation actions in a specific context respectively. The proposed approach is empirically evaluated based on a real-world traffic management application.

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Fan, Xi Hui, Lian Fei Duan, Yu Mei Wang, and Dai Mei Chen. "Ontology-Based Methodology for Information Integration and Service Discovery." Applied Mechanics and Materials 513-517 (February 2014): 1241–45. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1241.

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Finding suitable information in the open and distributed environment of current simulation information is a crucial task. One of the main challenges is to overcome semantic heterogeneity. This paper draw on the ontology, Semantic Web and cloud computing, put forward an ontology-based methodology for simulation information integration and service discovery, using XML Schema to realize the formatting description of resources, using ontology to realize the formal description of resources, using cloud computing to build an information resources pool, adopting SOA and Web services to realize the automatic discovery, match and combination of information services. Finally, an example is tested to verify the feasibility of the methodology.

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V L N Sujith, A., Dr A Rama Mohan Reddy, and Dr K Madhavi. "Evaluating the QoS Cognizance in Composition of Cloud Services: A Systematic Literature Review." International Journal of Engineering & Technology 7, no. 4.6 (September 25, 2018): 141. http://dx.doi.org/10.14419/ijet.v7i4.6.20451.

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Enterprise level computing constantly investigates novel approaches that maximize their profits and minimize their expenses. With the rapid growth of cloud computing XaaS – ‘anything as a service’, service providers are enabled with the rapid deployment of virtual services to service requestors. Because of the enormous growth in the variety of the services and based on the demand of the virtualized resources, cloud service providers are facing tough competition to facilitate the composite service requests made by the service requestors. QoS (Quality of Service) is considered to be a preliminary factor while composing a new cloud service out of heterogeneous and distributed atomic services. Therefore service composition is promising area that focuses on the design and development of the automated approaches to deal with diverse phases of service composition techniques that include service discovery, negotiation, service selection and optimization of the atomic services. This paper provides anatomy of existing studies addressing the problem of cloud service composition that enable to identify intended objectives of the technique along with diverse QoS aware problem solving approaches. Furthermore, the key areas of the improvement in cloud service composition are identified for future research.

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Ramasamy, R. Kanesaraj, Fang-Fang Chua, Su-Cheng Haw, and Chin-Kuan Ho. "Web Service Discovery for Cloud-Based Mobile Application Using Multi-Level Clustering and QoS-Based Ranking." International Journal of Software Engineering and Knowledge Engineering 26, no. 07 (September 2016): 1077–97. http://dx.doi.org/10.1142/s0218194016500376.

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Since many service providers are providing similar web services, finding an accurate web service based on user preferences is becoming a challenging task. Therefore, enhancing web service discovery (WSD) method will improve the searching performance. In this paper, we firstly discuss and review some existing web service discovery approaches and identify their limitations. Subsequently, we propose a web service discovery method for cloud-based mobile application by using multi-level clustering technique to improve performance by reducing the searching scope. Our web service discovery architecture is able to increase the discoverability of more accurate web services based on user's preferences. Meanwhile, user preference Quality of Services (QoS) attributes are also used for ranking procedure to allow user to decide the quality of the mobile application. The experimental results show that our approach is able to increase the searching performance and provide a reliable list of selection for users.

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Boudouda, Souheila, and Mahmoud Boufaida. "Efficient Discovery of Provider Services in a Cloud-Based Supply Chain." Journal of Information Technology Research 14, no. 4 (October 2021): 1–17. http://dx.doi.org/10.4018/jitr.2021100101.

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This paper proposes a framework of services selection and classification for an efficient provider's services discovery in a cloud-based supply chain. This framework combines the advantages of the web service technology and agent paradigm to select dynamically the best services among those that operated in a supply chain. It is based on two levels: the UDDI cloud level and the agent one. The UDDI cloud level allows web services, which represent providers' business functionalities, to be classified, discovered, selected, and invoked by agents that are applied to the supply chain construction. The agent level contains an agent society that manages the different steps of cooperation and negotiation between the different business entities in a supply chain, as business-to-business and business-to-customer transactions. On the basis of the characteristics of supply chain, a negotiation protocol between agents has been proposed.

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A.O, Akinwunmi, Olajubu E. A., and Aderounmu G. A. "A Trustworhty Model for Reliable Cloud Service Discovery." International Journal of Computer Applications 87, no. 16 (February 14, 2014): 23–30. http://dx.doi.org/10.5120/15293-3962.

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Zhao, Hong Wei. "A Resource Discovery Mechanism on Cloud Computing System." Applied Mechanics and Materials 220-223 (November 2012): 2941–44. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2941.

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Cloud Computing is an efficient way to resolve the resource sharing and cooperative work in distributed environments. Considering the disadvantages of traditional Scheduling method and the characteristics of Cloud Computing System, a resource discovery mechanism has been designed and implemented. Firstly, a calculation method based on each join points’ loading has been proposed, providing the Formula of method. Secondly, a comprehensive service resource distribution method has been designed and implemented in consideration of respective service resource counts, each join points’ performance and current loading distribution. Finally, the result of the experiment indicates that the scheduling system can improve the efficiency of dispatching service resource and the utilization ratio of distributed service resource on Cloud Computing System.

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Jian-Ming Chang, Han-Chieh Chao, Jiann-Liang Chen, and Chin-Feng Lai. "An Efficient Service Discovery System for Dual-Stack Cloud File Service." IEEE Systems Journal 6, no. 4 (December 2012): 584–92. http://dx.doi.org/10.1109/jsyst.2011.2177131.

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Zhao, Hong Wei. "Research on a Resource Discovery Mechanism in Cloud Computing Environment Based on Analysis of Scientific Materials." Advanced Materials Research 282-283 (July 2011): 433–36. http://dx.doi.org/10.4028/www.scientific.net/amr.282-283.433.

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Cloud computing technology is an efficient way to resolve the resource sharing and cooperative work in distributed environments. The resource discovery mechanism is a key problem in Cloud computing. In order to implement the quick discovery of service resource and the balanced distribution of resource on the Cloud computing system, a resource discovery mechanism in Cloud computing environment has been designed and implemented. Firstly, a Formula based on each node's loading has been proposed. Secondly, a comprehensive service distribution method has been designed in consideration about each node’s performance and current loading distribution. Finally, the result of the experiment indicates that the discovery mechanism can improve the efficiency of the resource and the utilization ratio of the service resource.

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Khan, Gitosree, Sabnam Sengupta, and Anirban Sarkar. "Dynamic service composition in enterprise cloud bus architecture." International Journal of Web Information Systems 15, no. 5 (December 2, 2019): 550–76. http://dx.doi.org/10.1108/ijwis-01-2019-0005.

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Purpose Service composition phenomenon based on non-scenario aspects are become the latest issues in enterprise software applications of the multi-cloud environment due to the phenomenal increase in a number of Web services. The traditional service composition patterns are hard to support the dynamic, flexible and autonomous service composition in the inter-cloud platform. To address this problem, this paper aims to describe a dynamic service composition framework (SCF) that is enriched with various structural and functional aspects of composition patterns in a cloud computing environment. The proposed methodology helps to integrate various heterogeneous cloud services dynamically to acquire an optimal and novel enterprise solution for delivering the service to the end-users automatically. Design/methodology/approach SCF and different composition patterns have been used to compose the services present in the inter-cloud architecture of the multi-agent-based system. Further, the proposed dynamic service composition algorithm is illustrated using a hybrid approach, where service are chosen according to various needs of quality of service parameters. Besides, a priority-based service scheduling algorithm is proposed that facilitates the automation of delivering cloud service optimally. Findings The proposed framework is capable of composing the heterogeneous service and facilitate the structural and functional aspects of service composition process in enterprise cloud-based applications in terms of flexibility, scalability, integrity and dynamicity of the cloud bus. The advantage of the proposed algorithm is that it helps to minimize the execution cost, processing time and get better success rate in delivering the service as per customer’s need. Originality/value The novelty of the proposed architecture coordinates cloud participants, automate service discovery pattern, reconfigure scheduled services and focus on aggregating a composite services in inter-cloud environments. Besides, the proposed framework supported several non-functional characteristics such as robustness, flexibility, dynamicity, scalability and reliability of the system.

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Zhan, Hang Min, and Lin Jian Zhang. "Tensor-Based Web Services Discovery Model and its Algorithm." Applied Mechanics and Materials 432 (September 2013): 559–64. http://dx.doi.org/10.4028/www.scientific.net/amm.432.559.

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The manufacturing services and resources matching are a key issue in building of the cloud manufacturing platform. This paper presents an ontology based service matching approach, which introduces QoS information to improve the accuracy of matching. The SVD method is used to recover unknown QoS data. The experimental results show that the algorithm can effectively improve the quality of service matching.

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Kashyap, Neeti, Achanta C. Kumari, and Rita Chhikara. "Service Discovery and Selection in Internet of Things - A Review." Recent Patents on Engineering 14, no. 1 (June 21, 2020): 4–11. http://dx.doi.org/10.2174/1872212113666181211095048.

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The Internet of Things (IoT) is a novel technology that has opened doors to the new level of interaction between the things. This has resulted in an enhancement in the quality of life and optimized use of various resources. IoT uses various technologies related to networking, sensing, databases and artificial intelligence to enhance the lifestyle and makes business processes simpler. In the IoT based systems, the number of devices contributing to a particular application is very large, spreading to a large geographical area at various locations. The device can be considered as a resource used by a service in the application layer. IoT service is the most important entity. The real-world things generate data by perceiving the environment in large quantity and store it in the distributed databases or cloud databases. This manuscript analytically and statistically categorizes and analyze the current research techniques on the service discovery and selection in the IoT, published between 2010 and 2018. It finds that the discovery among a huge number of services requires fast, scalable and dynamic service discovery mechanism over the Internet. Once the services are discovered, the next step is to select the most appropriate service. This paper includes a comprehensive analysis of the discovery and selection of services in IoT. A patent related to service and discovery have been also discussed which would be beneficial in identifying the research gap to make the system more efficient.

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Wei, Yi, and M. Brian Blake. "Adaptive Web Services Monitoring in Cloud Environments." International Journal of Web Portals 5, no. 1 (January 2013): 15–27. http://dx.doi.org/10.4018/jwp.2013010102.

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Cloud computing environments provide flexible infrastructures for third-party management of organizations’ information technology (IT) assets. With web services being a standard for realizing web-based business capabilities, the emergence of cloud computing will bring new challenges to different web service activities. In this paper, the authors propose an agent-based framework that employs a team of management and monitoring agents on different scopes to provides effective service management in a cloud environment. To tackle the dynamism in service operations, an adaptive monitoring algorithm is proposed. The algorithm is inspired by the congestion control approach from the TCP protocol and provides efficient, up-to-date information about service status without exhaustive monitoring. Experimental results show that the monitoring algorithm provides significant benefits when compared to the more exhaustive methods. This approach also facilitates other service activities, such as cross cloud service discovery.

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Modi, Kirit J., and Sanjay Garg. "A QoS-based approach for cloud-service matchmaking, selection and composition using the Semantic Web." Journal of Systems and Information Technology 21, no. 1 (March 11, 2019): 63–89. http://dx.doi.org/10.1108/jsit-01-2017-0006.

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PurposeCloud computing provides a dynamic, heterogeneous and elastic environment by offering accessible ‘cloud services’ to end-users. The tasks involved in making cloud services available, such as matchmaking, selection and composition, are essential and closely related to each other. Integration of these tasks is critical for optimal composition and performance of the cloud service platform. More efficient solutions could be developed by considering cloud service tasks collectively, but the research and academic community have so far only considered these tasks individually. The purpose of this paper is to propose an integrated QoS-based approach for cloud service matchmaking, selection and composition using the Semantic Web.Design/methodology/approachIn this paper, the authors propose a new approach using the Semantic Web and quality of service (QoS) model to perform cloud service matchmaking, selection and composition, to fulfil the requirements of an end user. In the Semantic Web, the authors develop cloud ontologies to provide semantic descriptions to the service provider and requester, so as to automate the cloud service tasks. This paper considers QoS parameters, such as availability, throughput, response time and cost, for quality assurance and enhanced user satisfaction.FindingsThis paper focus on the development of an integrated framework and approach for cloud service life cycle phases, such as discovery, selection and composition using QoS, to enhance user satisfaction and the Semantic Web, to achieve automation. To evaluate performance and usefulness, this paper uses a scenario based on a Healthcare Decision-Making System (HDMS). Results derived through the experiment prove that the proposed prototype performs well for the defined set of cloud-services tasks.Originality/valueAs a novel concept, our proposed integrated framework and approach for cloud service matchmaking, selection and composition based on the Semantic Web and QoS characterisitcs (availability, response time, throughput and cost), as part of the service level agreement (SLA) will help the end user to match, select and filter cloud services and integrate cloud-service providers into a multi-cloud environment.

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Guerfel, Rawand, Zohra Sbaï, and Rahma Ben Ayed. "On the Use of Similarity or Query Languages in Cloud Discovery Based on Ontology." International Journal of Service Science, Management, Engineering, and Technology 8, no. 3 (July 2017): 60–78. http://dx.doi.org/10.4018/ijssmet.2017070104.

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Cloud computing is increasingly used so that the number of providers offering services is rapidly increasing. Thus, a need to organize these services and to express relations between them arises. To answer this need, ontologies are used. To query these services, the authors use query languages, such as SPARQL, that return two types of results: either a list of required services, or an empty list. However, the second result is not desired. In fact, if the required service is not available, users want to be offered by a list of similar ones instead of the empty list. It is in this sense that the similarity, which provides more results ranked according to their utilities, is used. This paper first presents the Cloud ontology on which the authors' work is based. It then defines and compares between two Cloud service discovery methods which are: the discovery based on query languages and the discovery based on similarity. To show the efficiency of the search based on similarity, the authors propose a search engine that allows the users to query services using a simple to use interface.

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Spiga, Daniele, Enol Fernandez, Vincenzo Spinoso, Diego Ciangottini, Mirco Tracolli, Giacinto Donvito, Marica Antonacci, et al. "The DODAS Experience on the EGI Federated Cloud." EPJ Web of Conferences 245 (2020): 07033. http://dx.doi.org/10.1051/epjconf/202024507033.

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The EGI Cloud Compute service offers a multi-cloud IaaS federation that brings together research clouds as a scalable computing platform for research accessible with OpenID Connect Federated Identity. The federation is not limited to single sign-on, it also introduces features to facilitate the portability of applications across providers: i) a common VM image catalogue VM image replication to ensure these images will be available at providers whenever needed; ii) a GraphQL information discovery API to understand the capacities and capabilities available at each provider; and iii) integration with orchestration tools (such as Infrastructure Manager) to abstract the federation and facilitate using heterogeneous providers. EGI also monitors the correct function of every provider and collects usage information across all the infrastructure. DODAS (Dynamic On Demand Analysis Service) is an open-source Platform-as-a-Service tool, which allows to deploy software applications over heterogeneous and hybrid clouds. DODAS is one of the so-called Thematic Services of the EOSC-hub project and it instantiates on-demand container-based clusters offering a high level of abstraction to users, allowing to exploit distributed cloud infrastructures with a very limited knowledge of the underlying technologies.This work presents a comprehensive overview of DODAS integration with EGI Cloud Federation, reporting the experience of the integration with CMS Experiment submission infrastructure system.

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Adarme, Marco, and Miguel Jimeno. "QoS-Based Pattern Recognition Approach for Web Service Discovery: Ar_WSDS." Applied Sciences 11, no. 17 (August 31, 2021): 8092. http://dx.doi.org/10.3390/app11178092.

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Web service composition requires high levels of integration and reliability of the services involved in its operation, which must meet specific quality criteria to ensure their proper execution and deployment. The discovery and selection of web services currently face optimization problems. Many services might satisfy a requirement with similar quality criteria. Because of this, software developers have to choose the most appropriate services for a given composition, complicated by the rapid increase in providers and services available in the cloud. Service composition also implies coupling according to a composition flow and non-functional requirement criteria. Such requirements make selection and composition a complex task not previously solved in the literature. This paper presents Ar_WSDS, a computational approach for web services discovery and selection in cloud environments, which bases its implementation on the brain’s pattern recognition systematic functioning. This process allows classifying web services through recognition modules created dynamically based on their quality parameters, resulting in a set of web services suitable for a web service composition. This approach allows a solution to the selection problem using less complex tasks. This paper introduces an architectural and procedural definition that provides the web service description with a pattern to recognize and select services using different recognition levels. We simulated our approach and evaluated it using a dataset from the QWS project that offers a set of quality criteria collected from different providers. The web services are recognized and classified using different quality criteria for the composition and each of their services. The results demonstrate the effectiveness of the discovery and selection process compared to other approaches. Furthermore, Ar_WSDS allows us to recognize and filter out web services with ambiguity and similarity in their provider information, a process that minimizes the discovery space for services.

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Zhang, Shuiwang, and Xiaojian Hu. "Game Analysis on Logistics Cloud Service Discovery and Combination." International Journal of u- and e-Service, Science and Technology 8, no. 10 (October 31, 2015): 193–202. http://dx.doi.org/10.14257/ijunesst.2015.8.10.19.

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41

Guo, Liang, Shilong Wang, Ling Kang, and Yang Cao. "Agent-based manufacturing service discovery method for cloud manufacturing." International Journal of Advanced Manufacturing Technology 81, no. 9-12 (June 4, 2015): 2167–81. http://dx.doi.org/10.1007/s00170-015-7221-0.

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Jaswal, Shivani, and Manisha Malhotra. "MATEM." International Journal of Cloud Applications and Computing 12, no. 1 (January 1, 2022): 1–17. http://dx.doi.org/10.4018/ijcac.305213.

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The paradigms of Cloud Computing have risen at a very rapid rate. The Cloud Computing demands that a trustworthy or reliable service should be availed by its potential user. However, it is always a challenge for any cloud user to look for service that is suitable as well as reliable in every aspect. For a trustworthy discovery and delivery of cloud services, a multi-layered model i.e., Multi Agent based Trust Evaluation Model (MATEM) has been proposed. It is a multi-agent trust model that will make use of multiple agents to perform and evaluate the credibility of trust through trust evaluation system. Also, the performance validation has proven that the final calculated values of trust will be helpful in providing reliable cloud services to its users.

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Alshudukhi, Jalawi Sulaiman. "Pattern-based solution for architecting cloud-enabled software." International Journal of ADVANCED AND APPLIED SCIENCES 8, no. 8 (August 2021): 9–19. http://dx.doi.org/10.21833/ijaas.2021.08.002.

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Cloud computing exploits the software as a service model with distributed and interoperable services for the composition of software systems. Cloud-enabled systems that demand elasticity, scalability, and composition of services, etc., there is a need to capitalize on reusable solutions exploiting patterns and styles to architect cloud-based software. The objective of this research is to build and exploit a catalog of patterns that support reusable design knowledge to develop cloud-based architectures. We propose a three-step process with (i) pattern discovery, (ii) pattern documentation (building the catalog), and finally, (iii) pattern application (exploiting the catalog) to enable pattern-based architecting of cloud systems. We discovered seven patterns as generic and reusable solutions and demonstrate the pattern-driven architecture of the ECMC case study. Results suggest that pattern-based architecting enables the reuse of generic design decisions but lacks fine-grained architectural design. The solution is the first attempt towards establishing the catalog as a repository of patterns for architecture-based development of cloud systems.

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Viji Rajendran, V., and S. Swamynathan. "SD-CSR: Semantic-Based Distributed Cloud Service Registry in Unstructured P2P Networks for Augmenting Cloud Service Discovery." Journal of Network and Systems Management 27, no. 3 (November 13, 2018): 625–46. http://dx.doi.org/10.1007/s10922-018-9479-7.

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45

Alkalbani, Asma Musabah, Walayat Hussain, and Jung Yoon Kim. "A Centralised Cloud Services Repository (CCSR) Framework for Optimal Cloud Service Advertisement Discovery From Heterogenous Web Portals." IEEE Access 7 (2019): 128213–23. http://dx.doi.org/10.1109/access.2019.2939543.

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46

Azouzi, Sameh, Jalel eddine Hajlaoui, Zaki Brahmi, and Sonia Ayachi Ghannouchi. "Collaborative E-Learning Process Discovery in Multi-tenant Cloud." International Journal of Intelligent Systems and Applications 13, no. 2 (April 8, 2021): 21–37. http://dx.doi.org/10.5815/ijisa.2021.02.02.

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With the appearance of the COVID-19 pandemic, the practice of e-learning in the cloud makes it possible to:avoid the problem of overloading the institutions infrastructure resources, manage a large number of learners and improve collaboration and synchronous learning. In this paper, we propose a new e-leaning process management approach in cloud named CLP-in-Cloud (for Collaborative Learning Process in Cloud). CLP-in-Cloud is composed of two steps: i) design general, configurable and multi-tenant e-Learning Process as a Service (LPaaS) that meets different needs of institutions. ii) to fulfill the user needs, developpe a functional and non-functional awareness LPaaS discovery module. For functional needs, we adopt the algorithm A* and for non-functional needs we adopt a linear programming algorithm. Our developed system allows learners to discover and search their preferred configurable learning process in a multi-tenancy Cloud architecture. In order to help to discover interesting process, we come up with a recommendation module. Experimentations proved that our system is effective in reducing the execution time and in finding appropriate results for the user request.

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Zhao, Zhuofeng, Dongju Yang, and Weida Zhang. "IoT service distributed management architecture and service discovery method for edge-cloud federation." International Journal of Grid and Utility Computing 13, no. 4 (2022): 376. http://dx.doi.org/10.1504/ijguc.2022.10050014.

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Yang, Dongju, Weida Zhang, and Zhuofeng Zhao. "IoT service distributed management architecture and service discovery method for edge-cloud federation." International Journal of Grid and Utility Computing 13, no. 4 (2022): 376. http://dx.doi.org/10.1504/ijguc.2022.125137.

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Zhang, Zhen Nan, and Pei Si Zhong. "Key Issues for Cloud Manufacturing Platform." Advanced Materials Research 472-475 (February 2012): 2621–25. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.2621.

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In order to realize sharing and collaboration of manufacturing resource and manufacturing capability based on knowledge and to realize added value of manufacturing resource and manufacturing capability. In this paper, we propose an ontology-based architecture for cloud manufacturing platform. Meanwhile, several key issues for cloud manufacturing platform including semantic description of manufacturing resource and manufacturing capability, manufacturing cloud service advertisement, manufacturing cloud service discovery and manufacturing cloud service composition are studied in particular. Thus, the research provides foundation for the future research, development, implementation and application of cloud manufacturing platform.

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Chivukula, Sreerama Prabhu, Rajasekhar Krovvidi, and Aneesh Sreevallabh Chivukula. "Eucalyptus Cloud to Remotely Provision e-Governance Applications." Journal of Computer Networks and Communications 2011 (2011): 1–15. http://dx.doi.org/10.1155/2011/268987.

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Remote rural areas are constrained by lack of reliable power supply, essential for setting up advanced IT infrastructure as servers or storage; therefore, cloud computing comprising an Infrastructure-as-a-Service (IaaS) is well suited to provide such IT infrastructure in remote rural areas. Additional cloud layers of Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) can be added above IaaS. Cluster-based IaaS cloud can be set up by using open-source middleware Eucalyptus in data centres of NIC. Data centres of the central and state governments can be integrated with State Wide Area Networks and NICNET together to form the e-governance grid of India. Web service repositories at centre, state, and district level can be built over the national e-governance grid of India. Using Globus Toolkit, we can achieve stateful web services with speed and security. Adding the cloud layer over the e-governance grid will make a grid-cloud environment possible through Globus Nimbus. Service delivery can be in terms of web services delivery through heterogeneous client devices. Data mining using Weka4WS and DataMiningGrid can produce meaningful knowledge discovery from data. In this paper, a plan of action is provided for the implementation of the above proposed architecture.

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