Cloud Service Discovery

Cloud computing is a paradigm for delivering ubiquitous, convenient, on-demand resources based on pay-as-you-go financial model. The Cloud Service Providers (CSPs) typically publish service descriptions, pricing policies and Service Level Agreement (SLA) rules on websites in various formats. With enormous growth of the cloud services and number of cloud providers discovering cloud services is a significant challenge and time-consuming task, especially when using general search mechanisms. Clients need to browse several websites online and across multiple cloud providers to select the appropriate cloud service. This paper presents new XML-Decentralized architecture to improve the effectiveness and efficiency of cloud service discovery. This architecture is based on Crawler Search Engine to collect the data from Cloud Service Providers. This data includes syntax and semantic information about cloud services. With new architecture Cloud Service Providers don't need to register service descriptions with every Cloud Service Discovery Systems (CSDSs) and only need to publish the service descriptions publicly. On the other hand, CSDS can directly access the service descriptions of Cloud Service Providers to index them. The cloud service discovery process is expected to be easier and faster by adopting the new architecture.

With the spread of services related to cloud environment, it is tiresome and time consuming for users to look for the appropriate service that meet with their needs. Therefore, finding a valid and reliable service is essential. However, in case a single cloud service cannot fulfil every user requirements, a composition of cloud services is needed. In addition, the need to treat uncertainty in cloud service discovery and composition induces a lot of concerns in order to minimize the risk. Risk includes some sort of either loss or damage which is possible to be received by a target (i.e., the environment, cloud providers or customers). In this paper, we will focus on the uncertainty application for cloud service discovery and composition. A set of existing approaches in literature are reviewed and categorized according to the risk modeling.

With the spread of services related to cloud environment, it is tiresome and time consuming for users to look for the appropriate service that meet with their needs. Therefore, finding a valid and reliable service is essential. However, in case a single cloud service cannot fulfil every user requirements, a composition of cloud services is needed. In addition, the need to treat uncertainty in cloud service discovery and composition induces a lot of concerns in order to minimize the risk. Risk includes some sort of either loss or damage which is possible to be received by a target (i.e., the environment, cloud providers or customers). In this paper, we will focus on the uncertainty application for cloud service discovery and composition. A
set of existing approaches in literature are reviewed and categorized according to the risk modeling.