Online Density Grid Pattern Analysis to Classify Anomalies in Cloud and NFV Systems

Acker, Alexander; Schmidt, Florian; Gulenko, Anton; Kao, Odej

doi:10.1109/cloudcom2018.2018.00063

Cited by 6 publications

(5 citation statements)

References 15 publications

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“…Papers [4,6] only focus on the abnormal resource consumption event of the job. Paper [5] only focus on job scheduling failure events, papers [7][8][9][10] only focus on the abnormal consumption of container resources, and paper [11] only focus on instance authorization failure and Instantiate abnormal event. They all assume that each event is independent of other events, pay attention to the abnormal of events in terms of resources and scheduling, but ignore the abnormal caused by the dependency between events.…”

Section: Cloud Service Eventsmentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Cloud Service Events and Their Connections

Hu¹,

Zhang²,

Qin³

et al. 2022

Natural Language Processing (NLP) Trends

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Any unexpected service interruption or failure may cause customer dissatisfaction or economic losses. To distinguish the rights and interests or security disputes between cloud service providers and customers, explore the essence and rules of cloud service events and their various connections, such as: Normal contact of service scheduling, normal contact of service dependence, abnormal contact of resource competition, abnormal contact of service delay, abnormal contact of service dependence, etc., as well as their rules in time, resources, scheduling and other aspects, and the form of the rules; The purpose is to provide the above abnormal connections, as well as the rule and presentation form in terms of time, resources and load, for the study of violation determination and failure tracing in the cloud service accountability mechanism.

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Section: Cloud Service Eventsmentioning

confidence: 99%

“…According to the papers [2][3][4][5][6][7][8][9][10][11][27][28][29][30][31], it is summarized that there are normal events, unknown events and abnormal events in cloud service events, this article focuses on abnormal events. The cloud service events classification diagram is shown in Figure 1.…”

Section: Cloud Service Events Classificationmentioning

confidence: 99%

A Survey of Cloud Service Events and Their Connections

Hu¹,

Zhang²,

Qin³

et al. 2022

Natural Language Processing (NLP) Trends

View full text Add to dashboard Cite

show abstract

“…Lastly, the decision engine gathers events of root cause components with additional information about the anomalies and applies density grid pattern matching [16] to recommend appropriate remediation action selection. These actions are assumed to be provided beforehand by experts, but can be extended over time through reinforcement learning.…”

Section: B Data Analysismentioning

confidence: 99%

Towards AIOps in Edge Computing Environments

Becker,

Schmidt,

Gulenko

et al. 2021

Preprint

Self Cite

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Edge computing was introduced as a technical enabler for the demanding requirements of new network technologies like 5G. It aims to overcome challenges related to centralized cloud computing environments by distributing computational resources to the edge of the network towards the customers. The complexity of the emerging infrastructures increases significantly, together with the ramifications of outages on critical use cases such as self-driving cars or health care. Artificial Intelligence for IT Operations (AIOps) aims to support human operators in managing complex infrastructures by using machine learning methods. This paper describes the system design of an AIOps platform which is applicable in heterogeneous, distributed environments. The overhead of a high-frequency monitoring solution on edge devices is evaluated and performance experiments regarding the applicability of three anomaly detection algorithms on edge devices are conducted. The results show, that it is feasible to collect metrics with a high frequency and simultaneously run specific anomaly detection algorithms directly on edge devices with a reasonable overhead on the resource utilization.

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“…Moreover, in reference [22], it is shown that deep learning can be used to identify anomaly events from NFV system logs reliably. A technique using a supervised machine learning method for online classification of anomaly states based on similarities between anomaly type-specific density grid patterns is presented in reference [23]. The detection is done by analysing CPU, memory and network usage; the procedure used, the density grid mapping, is inherited from the theory of grid-based clustering.…”

Section: Related Workmentioning

confidence: 99%

The Next Generation Platform as A Service: Composition and Deployment of Platforms and Services

et al. 2019

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The emergence of widespread cloudification and virtualisation promises increased flexibility, scalability, and programmability for the deployment of services by Vertical Service Providers (VSPs). This cloudification also improves service and network management, reducing the Capital and Operational Expenses (CAPEX, OPEX). A truly cloud-native approach is essential, since 5G will provide a diverse range of services - many requiring stringent performance guarantees while maximising flexibility and agility despite the technological diversity. This paper proposes a workflow based on the principles of build-to-order, Build-Ship-Run, and automation; following the Next Generation Platform as a Service (NGPaaS) vision. Through the concept of Reusable Functional Blocks (RFBs), an enhancement to Virtual Network Functions, this methodology allows a VSP to deploy and manage platforms and services, agnostic to the underlying technologies, protocols, and APIs. To validate the proposed workflow, a use case is also presented herein, which illustrates both the deployment of the underlying platform by the Telco operator and of the services that run on top of it. In this use case, the NGPaaS operator facilitates a VSP to provide Virtual Network Function as a Service (VNFaaS) capabilities for its end customers.

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Online Density Grid Pattern Analysis to Classify Anomalies in Cloud and NFV Systems

Cited by 6 publications

References 15 publications

A Survey of Cloud Service Events and Their Connections

A Survey of Cloud Service Events and Their Connections

Towards AIOps in Edge Computing Environments

The Next Generation Platform as A Service: Composition and Deployment of Platforms and Services

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