Benchmarking autonomic capabilities: promises and pitfalls

Brown, Alexander L.; Hellerstein, Joseph L.; Hogstrom, Matt; Lau, T.C.; Lightstone, Sam; Shum, P.; Yost, M.P.

doi:10.1109/icac.2004.1301372

Cited by 27 publications

(17 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The DBench project aimed at defining a conceptual framework and an experimental environment for dependability benchmarking [32]. The IBM Autonomic Computing benchmark focuses on the resiliency of the system against various disturbance [33,34].…”

Section: Dependability Benchmark Robustness Testing Toolsmentioning

confidence: 99%

A Brief Program Robustness Survey

Abdalla¹,

Abdallah²,

Salah³

2017

IJSEA

View full text Add to dashboard Cite

show abstract

Section: Dependability Benchmark Robustness Testing Toolsmentioning

confidence: 99%

A Brief Program Robustness Survey

Abdalla¹,

Abdallah²,

Salah³

2017

IJSEA

View full text Add to dashboard Cite

show abstract

“…Additionally, the metric is related to the confidence or trust in autonomic system operation. For the practical assessment of an implemented system we use a series of benchmarks [65] that represent situations by the environment for the system. Based on the complexity of the benchmark, we derive the level of autonomicity.…”

Section: Assessment Of Cognitive Systemsmentioning

confidence: 99%

The E3 architecture: enabling future cellular networks with cognitive and self‐x capabilities

et al. 2010

View full text Add to dashboard Cite

SUMMARYFuture mobile networks are expected to be complex heterogeneous systems. On the one hand this will enable users to take advantage of a number of different access technologies. On the other hand it will seriously affect network management procedures since more extensive operations and decisions will have to be dealt with. To tackle these challenges a number of new dynamic mechanisms need to be designed. It is imperative that certain network management tasks have to be performed without human intervention to reduce the OPEX costs and achieve faster responses in different events. To achieve this goal, the introduction of self-x functionalities, combined with cognitive mechanisms and the ability to reconfigure network entities and terminals, is required. Moreover, the introduction of a new pilot channel needs to be considered to assist the terminals in selecting the most suitable radio access technology according to their requirements. We present the functional architecture of an evolved network that was designed in the context of the EU-funded IP project 'E 3 : End-to-End Efficiency'. This architecture aims to enhance existing procedures usually performed in traditional operation and maintenance systems (e.g. spectrum management, network planning, configuration actions). We explain the rationale of our design and provide specific examples to illustrate the role of the different functional entities and their interfaces. A considerable part of this architecture has recently been approved as a feasibility study by the ETSI Committee Reconfigurable Radio System.

show abstract

“…It is crucial to fill this gap. Recent notable efforts in this space include the development of dependability benchmarks [33] as well as incipient autonomic benchmarks for self-configuration and self-healing [12,13].…”

Section: Autonomic System Sciencementioning

confidence: 99%

Research challenges of autonomic computing

Kephart

2005

Proceedings of the 27th International Conference on Software Engineering - ICSE '05

143

View full text Add to dashboard Cite

Autonomic computing is a grand-challenge vision of the future in which computing systems will manage themselves in accordance with high-level objectives specified by humans. The IT industry recognizes that meeting this challenge is imperative; otherwise, IT systems will soon become virtually impossible to administer. But meeting this challenge is also extremely difficult, and will require a worldwide collaboration among the best minds of academia and industry. In the hope of motivating researchers in relevant areas to apply their expertise to this vitally important problem, I outline some of the main scientific and engineering challenges that collectively make up the grand challenge of autonomic computing, and provide pointers to initial efforts to address these challenges.

show abstract

Benchmarking autonomic capabilities: promises and pitfalls

Cited by 27 publications

References 1 publication

A Brief Program Robustness Survey

A Brief Program Robustness Survey

The E3 architecture: enabling future cellular networks with cognitive and self‐x capabilities

Research challenges of autonomic computing

Contact Info

Product

Resources

About