Automated Multi-graceful Degradation: A Case Study

Lin, Yiyan; Kulkarni, Sandeep S.

doi:10.1109/srds.2013.17

Cited by 5 publications

(5 citation statements)

References 18 publications

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“…Graceful degradation is often defined in association with technology only, such as "an ideal gracefully degrading system is partitioned so that failures in non-critical subsystems do not affect critical subsystems" [8, p156]. Other definitions refer to graceful degradation specifically within the context of fault tolerant technologies [17]. For the purposes of the current literature review however, a wider definition of graceful degradation as a system-wide outcome is adopted, including elements of technology and human operators, such as the definition by [18] "to gracefully degrade, the system must maintain safety performance requirements in the presence of faults or failures while and until demand is reduced to performance levels commensurate with the degraded capabilities" [p5].…”

Section: Resilience and Graceful Degradationmentioning

confidence: 99%

Towards Designing Graceful Degradation into Trajectory Based Operations: A Human-Machine System Integration Approach

Edwards

Lee

2017

17th AIAA Aviation Technology, Integration, and Operations Conference

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One of the most fundamental changes to the air traffic management system in NextGen is the concept of trajectory based operations (TBO). With the introduction of fundamental change, system safety and resilience is a critical concern, in particular, the ability of systems to 'degrade gracefully'. In order to design graceful degradation into a TBO envrionment, knowledge of the potential causes of degradation and appropriate solutions is required. Previous research has predominantly explored the technological contribution to graceful degradation, frequently neglecting to consider the role of the human operators in an environment in which humans, especially air traffic controllers, play a safety critical role. In addition, the environmental context in which the technological or human breakdowns occur also play a critical role in how well the system can degrade gracefully, which is also neglected in the literature. These oversights are out of step with real-world operations, and potentially limit an ecologically valid understanding of achieving graceful degradation in an air traffic control environment. Therefore, an integration approach to the human-machine system must be applied in order to achieve graceful degradation. The following literature review aims to identify and summarize the literature to date on the potential causes of degradation in air traffic control and the solutions that may be applied within a TBO context, with a specific focus on the contribution of the air traffic controller. A framework of graceful degradation, developed from the literature, is presented. The framework encompasses the potential impact of technology or human operator breakdown, as well as the complexity of the air traffic environment at the time of the breakdown, and categorizes them into different phases of detection and recovery. The aim of the framework is to develop research questions and design solutions to develop a resilient TBO system and procedures using a holistic view of human-machine system integration.

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Section: Resilience and Graceful Degradationmentioning

confidence: 99%

Towards Designing Graceful Degradation into Trajectory Based Operations: A Human-Machine System Integration Approach

Edwards

Lee

2017

17th AIAA Aviation Technology, Integration, and Operations Conference

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“…Changes are unpredictable, they can be dramatic, and they can include malfunctioning [23], slow down [12], failures [18], and much more. Graceful degradation [31] is then introduced into the runtime system, to handle these changes and guarantee performance in the presence of uncertainty. This paper shows that graceful degradation and load-balancing can interfere with one another.…”

Section: B Experimental Resultsmentioning

confidence: 99%

Cloud Application Predictability through Integrated Load-Balancing and Service Time Control

Nylander

Andrén

Årzén

et al. 2018

2018 IEEE International Conference on Autonomic Computing (ICAC)

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Cloud computing provides the illusion of infinite capacity to application developers. However, data center provisioning is complex and it is still necessary to handle the risk of capacity shortages. To handle capacity shortages, graceful degradation techniques sacrifice user experience for predictability. In all these cases, the decision making policy that determines the degradation interferes with other decisions happening at the infrastructure level, like load-balancing choices. Here, we reconcile the two approaches, developing a load-balancing strategy that also handles capacity shortages and graceful degradation when necessary. The proposal is based on a sound control-theoretical approach. The design of the approach avoids the pitfalls of interfering control decisions. We describe the technique and provide evidence that it allows us to achieve higher performance in terms of emergency management and user experience.

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“…RELATED WORK The challenge of building reliable distributed systems consists in providing various safety and liveness guarantees while the system is subject to certain classes of failures. Our contribution closely relates to multi-graceful degradation [32], in which the requirements that the service guarantees vary depending on the magnitude of the failure. However, due to the conflicting nature of requirements -maintaining maximum response time and maximizing optional content served, in the presence of noisy request servicing times -brownout does not provide formal guarantees.…”

Section: Discussionmentioning

confidence: 99%

Improving Cloud Service Resilience Using Brownout-Aware Load-Balancing

Klein

Papadopoulos

Dellkrantz

et al. 2014

2014 IEEE 33rd International Symposium on Reliable Distributed Systems

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We focus on improving resilience of cloud services (e.g., e-commerce website), when correlated or cascading failures lead to computing capacity shortage. We study how to extend the classical cloud service architecture composed of a loadbalancer and replicas with a recently proposed self-adaptive paradigm called brownout. Such services are able to reduce their capacity requirements by degrading user experience (e.g., disabling recommendations).Combining resilience with the brownout paradigm is to date an open practical problem. The issue is to ensure that replica self-adaptivity would not confuse the load-balancing algorithm, overloading replicas that are already struggling with capacity shortage. For example, load-balancing strategies based on response times are not able to decide which replicas should be selected, since the response times are already controlled by the brownout paradigm.In this paper we propose two novel brownout-aware loadbalancing algorithms. To test their practical applicability, we extended the popular lighttpd web server and load-balancer, thus obtaining a production-ready implementation. Experimental evaluation shows that the approach enables cloud services to remain responsive despite cascading failures. Moreover, when compared to Shortest Queue First (SQF), believed to be nearoptimal in the non-adaptive case, our algorithms improve user experience by 5%, with high statistical significance, while preserving response time predictability.

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Automated Multi-graceful Degradation: A Case Study

Cited by 5 publications

References 18 publications

Towards Designing Graceful Degradation into Trajectory Based Operations: A Human-Machine System Integration Approach

Towards Designing Graceful Degradation into Trajectory Based Operations: A Human-Machine System Integration Approach

Cloud Application Predictability through Integrated Load-Balancing and Service Time Control

Improving Cloud Service Resilience Using Brownout-Aware Load-Balancing

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