Virtualised databases in containers can be deployed dynamically on a variety of infrastructures. So far, various studies related to load balancing [21; 22; 23; 24], resource allocation and management [25; 26; 27], as well as resource provisioning [28; 29; 30; 31] have provided means for selecting an optimal IaaS provider. When data from multiple sources are processed in a shared distributed computing infrastructure, it is necessary to provide QoS guarantees for each data stream. The requirements can be specified in a well-defined SLA. The SLA defines the participants and their responsibilities, terms of the contract, contract's validity period, violation types and respective penalties. In the context of cloud computing, SLA is an officially exchanged document that describes in quantitative or qualitative terms the service that is going to be delivered to the costumer [32]. Due to the lack of studies addressing SLA management for storage in the Fog, the analysis for the state of the art of SLA management is for more generic Cloud computing services. [PERSON] et al. [7] proposed an SLA management that resides on the side of the service providers. The proposed framework for self-management of Cloud resources is composed of software components that are described in few consecutive studies [33; 34; 35]. Their framework provisions and schedules cloud resources, whilst maintaining SLAs and reducing SLA violation rate. [PERSON] et al. [8] presented an algorithm for selecting optimal web services to build a service composition in geo-distributed Cloud environments. The algorithm chooses the optimal service from a set of functionally equivalent services with respect to SLA constraints and minimises the number of SLA violations. [PERSON] et al. [9] proposed a new Cloud model for SLAs and a general control-theoretic approach for QoS-oriented SLA management in which SLA specification are translated into a utility-based objective function. For the selected case studies, the SLA management is illustrated with different QoS aspects of Cloud services, such as performance, dependability and financial energetic costs. The work of [PERSON] et al. [10] deals with the implementation of SLAs for computing Clouds and assured the required QoS during complex computations, such as DNA sequencing workflows. They focused on the problem of matching the workflow functional and non-functional SLA requirements to the compute and storage services provisioned by underlying Clouds with different service cost and quality. The study provides a design of an ontological model for a semantic description of the problem and develops a novel utility-based genetic matching algorithm for selecting Cloud services with respect to the user requirements and the properties of the Clouds. The results present the effectiveness of the approach in reducing the total cost and fulfilling the requested QoS even with large-scale service compositions. [PERSON] et al. [11] proposed a business-oriented federated Cloud computing model where multiple independent infrastructure providers can cooperate seamlessly to provide scalable \begin{table}
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**Work** & **QoS Attributes** & **SLA Impl.** & **SLA Spec.** & **Type of Nodes** & **Utility** \\ \hline [PERSON] et al., 2017 [17] & Latency Usage-context & No & No & Fog & Data storage \\ \hline [PERSON] et al., 2018 [18] & Data type Usage-context & No & No & Edge & Data storage \\ \hline Proposed solution & Cost Availability Throughput & Yes & Yes & Things-to-Cloud computing continuum & Data storage and processing \\ \hline \hline \end{tabular}
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Table 1: _Cont._infrastructure and QoS-assured hosting services. The business layer in the proposed model provides an enhanced security features and can trigger the on-demand resource provisioning across multiple infrastructure providers, hence helping to maximise the customer satisfaction, business benefits and resources usage. The work of [PERSON] et al.