Network-Aware Availability Modeling of an End-to-End NFV-Enabled Service

Tola, Besmir; Nencioni, Gianfranco; Helvik, Bjarne E.

doi:10.1109/tnsm.2019.2948725

Cited by 31 publications

(11 citation statements)

References 22 publications

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“…In summary, the optimization problem ( 22) contains elements both from availability and queueing models, where the latter allows to estimate the latency introduced by a chain. Indeed, the first step consists in computing the steady-state availability of chains, defined in terms of latency (see (21)), and in building the set of configurations L c guaranteeing the given availability constraint. The second step consists in identifying the configuration(s) minimizing the cost (20) represented by the solution(s) of (22).…”

Section: Redundancy Optimization Of the Service Chainmentioning

confidence: 99%

A Latency-Driven Availability Assessment for Multi-Tenant Service Chains

Simone¹,

Mauro

Natella

et al. 2023

IEEE Trans. Serv. Comput.

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Nowadays, most telecommunication services adhere to the Service Function Chain (SFC) paradigm, where network functions are implemented via software. In particular, container virtualization is becoming a popular approach to deploy network functions and to enable resource slicing among several tenants. The resulting infrastructure is a complex system composed by a huge amount of containers implementing different SFC functionalities, along with different tenants sharing the same chain. The complexity of such a scenario lead us to evaluate two critical metrics: the steady-state availability (the probability that a system is functioning in long runs) and the latency (the time between a service request and the pertinent response). Consequently, we propose a latency-driven availability assessment for multi-tenant service chains implemented via Containerized Network Functions (CNFs). We adopt a multi-state system to model single CNFs and the queueing formalism to characterize the service latency. To efficiently compute the availability, we develop a modified version of the Multidimensional Universal Generating Function (MUGF) technique. Finally, we solve an optimization problem to minimize the SFC cost under an availability constraint. As a relevant example of SFC, we consider a containerized version of IP Multimedia Subsystem, whose parameters have been estimated through fault injection techniques and load tests.

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Section: Redundancy Optimization Of the Service Chainmentioning

confidence: 99%

A Latency-Driven Availability Assessment for Multi-Tenant Service Chains

Simone¹,

Mauro

Natella

et al. 2023

IEEE Trans. Serv. Comput.

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show abstract

“…Experimental evaluations confirm the ability of the model to detect bottlenecks and quantify performance degradations. Tola et al describe, in [28] an approach to estimate the end-to-end NFV-deployed service availability, and present a quantitative assessment of the network factors that affect the availability of the service provided by an NFV architecture. The proposed approach considers a two-level availability model where (i) the low level considers the network topology structure and NFV connectivity requirements through the definition of the system structure function based on minimal-cut sets and (ii) the higher level examines dynamics and failure modes of network and NFV elements through stochastic activity networks.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Performance Analysis in IoT Platforms

Ouedraogo

Medjiah

Sulhadi

et al. 2022

IEEE Trans. Netw. Serv. Manage.

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In this paper, we consider the problem of identifying multiple bottlenecks (a.k.a bottleneck analysis) in IoT Service Platforms. For QoS-constrained applications, IoT Platforms have grown in complexity with non-stationary workloads and intertask dependencies created by data flows crossing the platform's nodes. These factors create multiple simultaneous "bottlenecks" (a bottleneck expresses overload in terms of request processing time on a given node, and contributes to QoS degradation). Multi-bottlenecks are non-trivial to analyze since they may escape typical assumptions made in classic performance analysis, such as analysis based on queuing theory models. Solving this analysis problem requires real-time collection and analysis of data that can be massive, and as a result, induce negative impacts on the performance of the NFV-based IoT Platform (NIP) (e.g., use of bandwidth, computing resource, and storage resource). Therefore, it needs to be adapted to the strict minimum allowing effective analysis. We build an adaptive performance analysis method that optimizes bottlenecks' identification for a monitoring overhead budget associated with the different available metrics. Instead of systematically collecting all the NIP metrics, the proposed process determines the best subset of metrics to consider for the efficiency of the performance analysis. The conducted experiments on a practical use case show that the proposed method exhibited high performances of the bottleneck analysis process, in the presence of different bottleneck types and durations, with very few false positives and false negatives.

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“…3) General challenges: a) Dependability modelling: A first way of evaluating the dependability of a new system is to realize dependability models. For example, this approach has been used to evaluate the availability of SDN [151] and NFV [152]. A dependability model can allow to evaluate the impact of the elements composing the MEC system and identify the critical issues.…”

Section: User App Lcm Proxy -N/amentioning

confidence: 99%

5G Multi-access Edge Computing: Security, Dependability, and Performance

Nencioni,

Garroppo,

Olimid

2021

Preprint

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The main innovation of the Fifth Generation (5G) of mobile networks is the ability to provide novel services with new and stricter requirements. One of the technologies that enable the new 5G services is the Multi-access Edge Computing (MEC). MEC is a system composed of multiple devices with computing and storage capabilities that are deployed at the edge of the network, i.e., close to the end users. MEC reduces latency and enables contextual information and real-time awareness of the local environment. MEC also allows cloud offloading and the reduction of traffic congestion. Performance is not the only requirement that the new 5G services have. New missioncritical applications also require high security and dependability. These three aspects (security, dependability, and performance) are rarely addressed together. This survey fills this gap and presents 5G MEC by addressing all these three aspects. First, we overview the background knowledge on MEC by referring to the current standardization efforts. Second, we individually present each aspect by introducing the related taxonomy (important for the not expert on the aspect), the state of the art, and the challenges on 5G MEC. Finally, we discuss the challenges of jointly addressing the three aspects.

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Network-Aware Availability Modeling of an End-to-End NFV-Enabled Service

Cited by 31 publications

References 22 publications

A Latency-Driven Availability Assessment for Multi-Tenant Service Chains

A Latency-Driven Availability Assessment for Multi-Tenant Service Chains

Adaptive Performance Analysis in IoT Platforms

5G Multi-access Edge Computing: Security, Dependability, and Performance

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