Root cause and liability analysis in the microservices architecture for edge IoT services

In this work, we present a liability analysis framework for root cause analysis (RCA) in the microservices architecture with IoT-oriented containerized network services. We keep track of the performance metrics of microservices, such as service response time, memory usage and availability, to detect anomalies. By injecting faults in the services, we construct a Causal Bayesian Network (CBN) which represents the relation between service faults and metrics. Service Level Agreement (SLA) data obtained from a descriptor named TRAILS (sTakeholder Responsibility, AccountabIlity and Liability deScriptor) is also used to flag service providers which have failed their commitments. In the case of SLA violation, the constructed CBN is used to predict the fault probability of services under given metric readings and to identify the root cause

Demonstrating liability and trust metrics for multi-actor, dynamic edge and cloud microservices

Transitioning edge and cloud computing in 5G networks towards service-based architecture increases their complexity as they become even more dynamic and intertwine more actors or delegation levels. In this paper, we demonstrate the Liability-aware security manager Analysis Service (LAS), a framework that uses machine learning techniques to compute liability and trust indicators for service-based architectures such as cloud microservices. Based on the commitments of Service Providers (SPs) and real-time observations collected by a Root Cause Analysis (RCA) tool GRALAF, the LAS computes three categories of liability and trust indicators, specifically, a Commitment Trust Score, Financial Exposure, and Commitment Trends

The owner, the provider and the subcontractors : how to handle accountability and liability management for 5G end to end service

The adoption of 5G services depends on the capacity to provide high-value services. In addition to enhanced performance, the capacity to deliver Security Service Level Agreements (SSLAs) and demonstrate their fulfillment would be a great incentive for the adoption of 5G services for critical 5G Verticals (e.g., service suppliers like Energy or Intelligent Transportation Systems) subject to specific industrial safety, security or service level rules and regulations (e.g., NIS or SEVESO Directives). Yet, responsibilities may be difficult to track and demonstrate because 5G infrastructures are interconnected and complex, which is a challenge anticipated to be exacerbated in future 6G networks. This paper describes a demonstrator and a use case that shows how 5G Service Providers can deliver SSLAs to their customers (Service Owners) by leveraging a set of network enablers developed in the INSPIRE-5Gplus project to manage their accountability, liability and trust placed in subcomponents of a service (subcontractors). The elaborated enablers are in particular a novel sTakeholder Responsibility, AccountabIity and Liability deScriptor (TRAILS), a Liability-Aware Service Management Referencing Service (LASM-RS), an anomaly detection tool (IoT-MMT), a Root Cause Analysis tool (IoT-RCA), two Remote Attestation mechanisms (Systemic and Deep Attestation), and two Security-by-Orchestration enablers (one for the 5G Core and one for the MEC)

Energy-aware Service Level Agreements in 5G NFV architecture

International audienceWith the emergence of new network paradigms, network operators are able to provide slices (multiple simultaneous logical networks) thanks to Network Function Virtualization (NFV) and Software-defined networking (SDN) technologies. Currently, network operators do not have the means to commit on energy consumption, although it is a growing request from their customers. Indeed, given that energy consumption does not appear in slice Service Level Agreements (SLA) nor in Virtual Network Function Descriptors (VNFD), slice automated management systems cannot take this criterion into account. This paper addresses this issue with two contributions. First, we extend VNFD to include energy consumption. Second, we propose an SLA template for slices which includes energy based commitments. This template is complemented by some metrics in order to detect any deviation. Both contributions are illustrated by a use case. Our aim is to allow the entity in charge of referencing and placement of the virtual network functions (VNFs) for network service-composition purpose, to take into account energy consumption in addition to other preexisting aspects. This will help the network provider to commit on energy consumption with his customers through enhanced SLAs

TRAILS: Extending TOSCA NFV profiles for liability management in the Cloud-to-IoT continuum

International audienceTo address the growing amount of data generated by the Internet of Things (IoT), Network Functions Virtualization (NFV), 5G, Fog and Edge computing converge to form a Cloudto-IoT continuum. This complex multi-layer architecture involves several actors among which responsibilities may be blurred. Existing profiles mostly describe deployment aspects and elude responsibility, accountability or liability characteristics. Moreover, the multiplicity of component profiles prevents uniform service management. This paper proposes TRAILS (sTakeholder Responsibility, AccountabIity and Liability deScriptor), an extension of the TOSCA NFV profile that merges the existing profiles and adds a description of the responsibilities and accountabilities of supply chain actors. This allows a uniform and liability-aware management of services involving IoT devices, fog, edge and cloud nodes. To show the usability of our model, we discuss the ecosystem around the generation of the proposed extension as well as its application in an ontology-based referencing module of a liability-aware service manager that we designed