Vol. 5, No. 11 November 2014 ISSN Journal of Emerging Trends in Computing and Information Sciences

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1 An Ontological Framework for Controlling Service Responses in Hybrid Cloud Amr Tolba Riyadh Community College, King Saud University, Riyadh 11437, Saudi Arabia Faculty of Science, Menoufia University, Egypt ABSTRACT The hybrid cloud computing has recently gained a high prominent place in the different areas of focus of research, in spite of the existence of a lot of questionable points related to integrations, communications of services among private and public clouds. It is worth mentioning that the heterogeneity of terms used by vendors, number of standards and the structure of the different cloud environments are considered an integrated part of the said questionable technical points. However, this paper positively dealt with such questionable points via using an Ontology-based framework as a middleware solution to control service responses in hybrid cloud. In the framework a number of layers were exploited: layer one for cloud service providers, layer two for public clouds, layer three for brokerage services core which represents a middleware layer, layer four for ontology cloud services, and layer five for enterprise private cloud users. The intended contribution of this paper is to use reasoning mechanism based on ontology concepts to interpret the user s need of services and control responses by using AI reasoning techniques in the brokerage services core and cloud ontology layer. Moreover, this middleware layer controls the connection and migration of services between private and public clouds. Keywords: Hybrid cloud, cloud computing, Service integration, cloud ontology, cloud brokerage 1. INTRODUCTION Cloud computing represents a new way to give IT users a set of network enabled services that is capable of providing scalable, customized and inexpensive computing infrastructures on demand, which could be accessed. Effective usage of cloud computing services allow small and medium enterprises to avoid the substantial investment of building their own data centers. Large-sized enterprises can enhance resource utilization at a reduced cost. Private users and common people mainly experience the benefits of the cloud in data storage, networking, accessing s, exploiting web services and others. Furthermore, cloud computing is a way to facilitate distributed computing and store different data since services are always shared online in an unrestricted manner for everyone [6]. A hybrid cloud is a cloud computing environment in which an organization provides some services existing in its own private cloud and have others being get accessed to them through public cloud. The hybrid approach permits a business to require advantage of the scalability and cost-effectiveness that a public cloud computing environment offers without exposing missioncritical applications and data to third-party vulnerabilities. This type of hybrid cloud environment is also called hybrid IT [2, 12]. In the hybrid cloud computing environment knowledge transfer from one cloud to different, one needs an excellent ontology method in which knowledge from one cloud to other gets migrated through a protocol service within of which 3 layers only are needed as a minimum level. The primary layer can involve the primary data center from wherever the information should be migrated, the second layer would be the intermediator platform wherever the information would be first migrated and therefore the third layer would be the layer wherever the information would be migrated [3,14]. Ontology can be defined as a set of concepts that provide a formal conceptualization of a particular domain that is shared by a group of users. Thus, in the context of cloud computing environment, ontologies describe the domain of services that introduced by cloud providers and needed by users [10]. In this paper, an ontology-based framework for controlling Service Responses in hybrid cloud is proposed. The framework exploits a number of layers, layer one for cloud service providers, layer two for public clouds, layer three is for brokerage services core, layer four for ontology cloud services, and layer five for enterprise private cloud users. The rest of the paper is organized as follow: In Section 2 some related works are illustrated. Section 3, the proposed framework is described in details. Finally, In Section 4, conclusions and discussions for future work plans. 2. RELATED WORK Guenane, Fouad, et al. [5] proposed a hybrid framework to increase the power of computation of the physical firewall with low cost using the dynamic features of hybrid cloud model. In such framework, concentration has been placed on the security issue in hybrid cloud environment with introducing the concept of security as a service model (SECaaS) that can be provided by cloud. The research conducted by Rafique, Ansar, et al.[11] focused on portability and interoperability of middleware in hybrid cloud. They proposed a middleware framework 871

2 that offers enhanced support for hybrid cloud application by using a common application program interface for link public/private cloud core environment. They applied this API in PaaS model to increase portability but, this caused some performance overhead when dealing with SaaS providers. Kapil Bakashi [8] focused on how to extend a private cloud to a single public cloud and then generalized this idea to work with multiple public clouds. The author uses a broker module to help in the decision making to execute this extension. The work conducted in this paper has followed a given idea but with different focuses. In their research paper, Reiter, Gerdet al. [1] introduced a novel framework for managing and controlling service integration on hybrid cloud. The key feature of this framework is the construction of integrated platforms that allow deployment of functions and enhance the ability to control integrations through using different protocols. On the other hand, a lot of previous work about using ontology concept in the field of cloud computing exist. Yousef, Lamia et al. [13] proposed the use of ontology inside the cloud by constitute a knowledge domain in the field of cloud computing. They present cloud ontology as a stack of layers, discussing the points of strengths of each layer with neglecting the issue of integration & communication among each other. Karie, Nickson M. et al. [9]focused on and describing the components of an ontological framework that provides a structure of different cloud environments. This work doesn t address the heterogeneity of terms used by vendors, number of standards, and a structure of the different cloud environments. Fortis, T-Fet al [4] presented the concept of ontology in the cloud services. They introduced mosaic as a middleware to facilitate the communication among various cloud providers. They suggested the use of ontology to facilitate the selection, execution and discovery of resources and services in addition to introducing a comprehensive model of cloud ontology that can work only for public clouds. In their research paper Han, Taekgyeonget al [7] presented a Cloud Service Discovery System (CSDS) based on ontology. They used ontology to enhance performance of the system together with software agent to consult ontology when selecting information retrieved from a public cloud. To the best of our knowledge, none of the earlier researches have presented an ontology- based framework for controlling services responses in hybrid cloud computing environment in the way that dealt with and handled in this paper. 3. PROPOSED FRAMEWORK In this section, the full structure of suggested framework has been introduced. The framework is composed mainly of five layers, as portrayed in Figure 1. The full description of each component is described as follows: 3.1 Cloud Service Provider Layer (CSPL) A cloud provider is a vendor that offers some components of cloud resources typically, Platform as a Service (PaaS), Software as a Service (SaaS) or Infrastructure as a Service (IaaS) to other businesses or individuals with stronger service-level agreements (SLAs). Cost, Reliability, Quality of Services (QoS) and Security of data are core important criteria to evaluate CSP. As known CSP can offer storage or software services available via a private cloud or public cloud for customers. The main concern in the proposed framework was on the services introduced by CSP and posted on public cloud. 3.2 Public Cloud Layer (PCL) In fact, public cloud and CSP are both integrated. A public cloud is one based on the standard cloud computing model, in which a CSP makes resources, such as storage and applications, available to the public over the Internet. In the proposed framework, the brokerage services core layer is connecting to public clouds and makes some sort of synchronization with enterprise private cloud based-on ontology to retrieve services according to user s behavior. Moreover, it plays an important role to extend the private cloud to more than one public cloud or from public cloud to another one. 3.3 Brokering Services Core Layer (BSCL) Brokerage service score provides the intermediary between public cloud and private cloud that help users choosing the services and offerings that best suit their needs according to cloud ontology. It helps in deployment of applications across clouds by providing users with possible cost which include multiple competing services from a catalog. Therefore, the results are accomplished by allowing the brokering services to do the following: Virtual Services Provider (VSP) is produced, data models across cloud services are contributed, and safety and probability are allowed. Furthermore, users are allowed to select the most excellent option through elasticity to move between cloud services and the solitary point of access. Therefore, emphasis has been placed on integration as the main task of brokerage through which we can maintain the data accuracy for organizations using B2B software services, IaaS, PaaS, or SaaS. In the proposed framework, another value to brokerage services layer has been added, reasoning the user s needs by consulting cloud ontology layer which helps broker to interpret the user need regarding IaaS, SaaS, and PaaS. Advice has been also provided to the user to choose relevant information according to his profile. In figure 2, UML sequence diagram is presented to show the functional behavior of BSCL Query Processing Module (QPM) The aim of this module in BSCL is to retrieve information from the public clouds according to the user requests. It employs Google as a search engine tools to 872

3 find that information. This information may be located in more than one cloud, therefore, the QPM using a filtering mechanism to filter these results and produce the most relevant information to the users. Next, it creates a Virtual Database (VDB) to store all responses. Then, Notify federation and choice module to synchronized responses among public/private clouds. Finally, send this information to RA for Ontology check and reasoning process Federation and Choice Module (FCM) This module in BSCL is responsible for connecting private cloud with leading public clouds in the hybrid cloud environment. This can be done by creating Secure Private Cloud Zones (SPCZ) for information retrieved by QPM and use this private cloud for internal development and move to a public cloud when ready to scale-out. FCMallows unifies metering for provision selfservice, and move application loads between different types of clouds since FCM can come across data center and organization boundaries, with cloud internetworking. It also connects to Control Module (CM) in BSCL for security aspects and integration of services Controlling Module (CM) This module in BSCL is responsible for developing and scaling application in the hybrid cloud environment. It consists of a set of controls to provide protection against any vulnerability and mitigate or reduce the effect of a malicious attack in hybrid cloud environment Reasoning Agent (RA) The RA is responsible for reasoning the request from user and consults with the cloud ontology to explore the relationships and impact among hybrid cloud services. It uses meta-ontology for restructuring data, using AI reasoning methods, and mapping data to its equivalent redistributed request. The behavior of RA consists of the following sequence: First, receives the filtered information retrieved using QPM, then using the meta-ontology for tokenizes the request and parses the tokenized request. If the tokenized request accommodates to the ontology, the RA will apply the associated rule to reason the request. If the parsing ontology and the application of associated rules are correct, RA restructures data according to the ontology received. Next, it updates the VDB with the new ontological responses. Finally, notifies the QPM to respond to the user required service. The pseudo-code for BSCL algorithm illustrates the brokerage services core components functions as shown in Table 1. Fig 1: An Ontology- Based Framework Architecture 873

4 Table 1: Pseudo-code algorithm for BSCL Input: User requests for services Output: Responses to required services BEGIN FOR each user request BEGIN QPM.recieve (Requirments,services) QPM.send(selected search engine(google), Request) QPM.receive(selected search engine(google), Responses) QPM.filter(Responses) QPM.store-responses (VDB) QMP.send-VDB:responses (FCM) QPM.notify-RA(VDB-Responses) END FOR FOR each response stored in VDB BEGIN FCM.connect_Private_Cloud FCM.create_SecurePrivateCloudZone FCM.store-responses (IN: VDM-Responses, OUT: SPCZ-Responses) FCM. Notify(CM) CM.send_rules (FCM) FCM.connect_Public_Cloud FCM.sync-responses (IN: Private-Responses, OUT: Public-Responses) FCM.notify-CM(Responses) CM.apply-protection(Private-cloud) CM.apply-protection(Public-cloud) CM.apply-migration(services) RA.recieve-reponse(VDB) RA.consult(response,COL) COL.check-concepts DB(Response) RA.restructure(RA-Data, RunTime) RA.uses((Reasoning-method),response) RA.mapping(COL-response, VDB-response) RA.constite- response (mapping output) RA.Update-VDB END FOR END 3.4 Cloud Ontology Layer (COL) Ontology can be defined as a set of concepts that provide a formal conceptualization of a particular domain that is shared by a group of users. Thus, in the context of cloud computing environment, ontologies describe the domain of services was introduced by cloud providers and needed by users.col contains a concepts Database that include all concepts coming from various sources in order to detect the required concepts and properties of the target ontology. COL can be used to describe properties of service demand and capabilities to enable cloud service providers to promote their services. IaaS is an instance of cloud services in which a number of computing resources like processing power, storage, networks, and other essential computing resources exist. The reason for inventing cloud ontology is to improve semantic data and allow the RA to recognize the meaning of the concept expressed by service supplier as needed by client, to comprehend semantic based services discovery. 3.5 Enterprise Private Cloud Layer (EPCL) The enterprises have initiated introducing the internal clouds to fully take advantage of its existing IT infrastructure. A number of concepts of cloud computing are applied to resources totally owned by the enterprise consuming the service through the internal cloud. The internal cloud can offer economies features and capabilities to deal with current and novel web-based applications by improving the current infrastructure with cloud computing abilities while offering safety and regulatory obedience. 874

5 Fig 2: UML Sequence Diagram for BSCL 4. CONCLUSION AND FUTURE WORK This paper has presented an ontology-based framework to control services responses in hybrid cloud environment. It introduced the Brokerage Service Core Layer (BSCL) as a middleware to facilitate the communications among clouds in the hybrid environment. The structure and the business processes simulation of the proposed framework were designed. Moreover, the sequence diagram and implemented pseudo code as algorithmic environment of the framework was illustrated. In the future work, Cloud Sim will be used as a simulation application to implement the component of the proposed framework to ensure its applicability and consistency. REFERENCES [1] Breiter, Gerd, and Vijay K. Naik. "A Framework for Controlling and Managing Hybrid Cloud Service Integration" IEEE International Conference on Cloud Engineering (IC2E), IEEE, [2] Chiang, Johannes K., Eric Yen, and Yu-Long Lin. "On Interoperation of Hybrid Cloud." International Symposium on Biometrics and Security Technologies (ISBAST), IEEE, [3] Fan, Chih-Tien, Wei-Jen Wang, and Yue-Shan Chang. "Agent-based service migration framework in hybrid cloud" IEEE 13th International Conference on High Performance Computing and Communications (HPCC), IEEE, [4] Fortis, T-F., Victor Ion Munteanu, and Viorel Negru. "Towards ontology for cloud services." 2012 Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), IEEE, [5] Fouad Guenane, Hajer Boujezza, Michele Nogueira, Guy Pujolle "An Architecture to Manage Performance and Reliability on Hybrid Cloud- Based Firewalling."Network Operations and Management Symposium (NOMS), IEEE, [6] Gupta, Abhishek, Kale, Laxmikant V., Gioachin, Filippo, March, Verdi, Suen, Chun Hui,Lee, Bu- Sung; Faraboschi, Paolo, Kaufmann, Richard, and Milojicic, Dejan "The Who, What, Why, and How of High Performance Computing in the Cloud." IEEE 5th International Conference on Cloud Computing Technology and Science (CloudCom), Vol. 1., IEEE, [7] Han, Taekgyeong, and Kwang Mong Sim. "An ontology-enhanced cloud service discovery system." Proceedings of the International Multi Conference of Engineers and Computer Scientists. Vol

6 [8] Kapil Bakashi Secure Hybrid Cloud Computing: Approaches and Use Cases Aerospace Conference, IEEE, [9] Karie, Nickson M., and Hein S. Venter. "An Ontological Framework for a Cloud Forensic Environment." Proceedings of the European Information Security Multi-Conference (EISMC 2013). [10] Liu, L., Yao, X., Qin, L., & Zhang, M. Ontologybased service matching in cloud computing. IEEE International Conference on Fuzzy Systems (FUZZ- IEEE), pp ,IEEE, [11] Rafique, Ansar, Walraven, StefanLagaisse, BertDesair, TomJoosen, Wouter" Towards portability and interoperability support in middleware for hybrid clouds." IEEE INFOCOM Workshop on Cross-Cloud System, IEEE, [12] Uchibayashi, Toshihiro, Bernady O. Apduhan, and Norio Shiratori. "A framework of an agent-based support system for IaaS service discovery." 13th International Conference on Computational Science and Its Applications (ICCSA), IEEE, [13] Youseff, Lamia, Maria Butrico, and Dilma Da Silva. "Toward a unified ontology of cloud computing." Grid Computing Environments Workshop, 2008.GCE'08. IEEE, [14] Zou, Caifeng, Huifang Deng, and Qunye Qiu. "Design and Implementation of Hybrid Cloud Computing Architecture Based on Cloud Bus." IEEE Ninth International Conference on Mobile Ad-hoc and Sensor Networks (MSN), IEEE, AUTHOR PROFILE Dr. Amr Tolba received his M.Sc. and Ph.D. degrees in computer science from Menoufia University, Egypt in the area of databases and Multi-Agent systems, in 2002 and 2006 respectively. He joined King Saud University (KSU) in August 2006 as an assistant professor at the department of computer science. His research interests include internet of things, intelligent systems, mobile social networks, recommender systems, e- learning and cloud computing. 876