Metadata Schema for Data-Aware Multi-Cloud Computing

Cloud computing has been recognized as the most prominent way for hosting and delivering services over the Internet. A plethora of cloud service offerings are currently available and are being rapidly adopted by small and medium enterprises but also by larger organisations based on their many superiorities to traditional computing models. However, at the same time the computing requirements of the modern cloud application has been exponentially increased due to the available big data for processing. Nowadays, we discuss the emerging data-intensive applications that necessitate the wide adoption of multi-cloud deployment models, in order to use all the advantages of cloud computing without any restrictions with respect to who is providing infrastructural services. In this paper, we discuss a Metadata Schema for data-aware multi-cloud computing which aspires to form the appropriate background vocabulary that will aid the big data-aware application deployment for distributed and loosely-coupled multi-cloud applications.

I. Introduction

Over the last years, there is a struggle to auspiciously exploit the plethora of cloud service offerings from a vastly increasing number of cloud providers. Up to a certain extent this has been successfully addressed with respect to making selection decisions on software or platform-as-a-service offerings from different providers [1]. Nevertheless, the use of multi-cloud offerings especially at the level of infrastructure in order to cope with the needs of big data applications still remains a goal. Such applications have to efficiently deal with the volume, variety, velocity, and veracity of the data, using any resources available in a cost-effective and efficient way. In this respect, there is an increasing need for data-intensive computing in highly distributed and federated cloud environments. A generic challenge is to overcome scalability, resiliency, and security issues faced by big data and data-intensive applications on distributed platforms by using transparent and optimized multi-cloud resource provisioning. One of the critical issues towards tackling the generic challenge mentioned is to design and develop the appropriate methods and tools for adequately describing placement preferences, constraints, and optimisation goals.