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A Hybrid Reliability Metric for SLA Predictive Monitoring

Modern SLA management includes SLA prediction based on data collected during service operations. Besides overall accuracy of a prediction model, decision makers should be able to measure the reliability of individual predictions before taking important decisions, such as whether to renegotiate an SLA. Measures of reliability of individual predictions provided by machine learning techniques tend to depend strictly on the technique chosen and to neglect the features of the system generating the data used to learn a model, i.e., the service provisioning landscape in this case. In this paper, we define a hybrid measure of reliability of an individual SLA prediction for classification models, which accounts for both the reliability of the chosen prediction technique, if available, and features capturing the variability of the service provisioning scenario. The metric is evaluated empirically using SLAs and event logs of a real world case.

This paper was presented in ACM Symposium on Applied Computing (SAC) in April 2019 (GGS Class 2).

A characterisation of reliability tools for Software Defined Networks (Trabajo original)

Software Defined Network (SDN) is a new paradigm in networking that introduces great flexibility, allowing the dynamic configuration of parts of the network through centralised programming. SDN has been successfully applied in field networks, and is now being applied to wireless and mobile networks, generating Software Defined Mobile/Wireless networks (SDWNs). SDN can be also combined with Network Function Virtualization (NFV) producing a software network in which the specific hardware is replaced by general purpose computing equipment running SDN and NFV software solutions. This highly programmable and flexible network introduces many challenges from the point of view of reliability (or robustness), and operators need to ensure the same level of confidence as in previous, less flexible deployments. This paper provides a first study of the current tools used to analyse the reliability of SDNs before deployment and/or during the exploitation of the network. Most of these tools offer some kind of automatic verification, supported by algorithms based on formal methods, but they do not differentiate between fixed and mobile/wireless networks. In the paper we provide a number of classifications of the tools to make this selection easier for potential users, and we also identify promising research areas where more effort needs to be made.