Autonomic computing for relational databases: the ten-year vision

Lightstone, Sam; Schiefer, Berni; Zilio, Daniel; Kleewein, Jim

doi:10.1109/indin.2003.1300373

Cited by 16 publications

(6 citation statements)

References 14 publications

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“…Ghosh et al [2] provide a most recent definition of self-healing systems: a self-healing system should recover from the abnormal (or unhealthy) state and return to the normative (healthy) state and function as it was prior to disruption. Therefore, it is recommended to achieve a healthy and functioning network state after recovering from a failure [15].…”

Section: Introductionmentioning

confidence: 99%

Optimized self-healing framework for software defined networks

Thorat

Raza

Nguyen

et al. 2015

Proceedings of the 9th International Conference on Ubiquitous Information Management and Communication

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Software defined network (SDN) enables network programmability and provides fine grained control for managing the complex network infrastructure. With the centralized nature of SDN it poses the requirement for failure management at the data plane, control plane and at the centralized controller side. The self-healing attribute of the autonomic network can be combined with SDN to develop a software defined self-healing resilient network. The aim of this paper is to propose a self-healing SDN framework which can optimize the recovery by applying autonomic principles. The proposed work includes a rapid recovery (RR) mechanism to perform an immediate link recovery at the switch level without overburdening the controller. Additionally, it reduces the memory requirement of the switch for storing the backup path flow rules by aggregating all the disrupted flows. We presented the analytical model for calculating the failure recovery time and the backup flow rules required for recovery. Based on the analytical model, RR scheme reduces the total number of backup flow rules for all the disrupted flows of the failed link to a single flow rule.

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Section: Introductionmentioning

confidence: 99%

Optimized self-healing framework for software defined networks

Thorat

Raza

Nguyen

et al. 2015

Proceedings of the 9th International Conference on Ubiquitous Information Management and Communication

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“…As a result of this demand, DBMSs have continued to grow in terms of their size and the functionality they provide. This growth reciprocally creates additional overhead in the associated system complexity and administration costs [18] and makes the task of manually tuning the performance of these systems virtually impossible.…”

Section: Introductionmentioning

confidence: 99%

The Psychic–Skeptic Prediction framework for effective monitoring of DBMS workloads

Elnaffar

Martin

2009

Data & Knowledge Engineering

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“…Autonomic Computing [1] has emerged as a paradigm for self managing IT systems to stem the tide of rapidly increasing administration costs in the face of rising IT system complexity [2] [3][4] [5]. The development of self managing systems posses special challenges to research and development teams.…”

Section: Introductionmentioning

confidence: 99%

Foundations of Autonomic Computing Development

Lightstone

2007

Fourth IEEE International Workshop on Engineering of Autonomic and Autonomous Systems (EASe'07)

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The complexity of modern middleware, and software solutions, is growing at an exponential rate. Only self-managing, or autonomic computing technology can reasonably stem the confusion this complexity brings to bear on human administrators. While much has been published on "architecture" and "function" for producing such systems, little has been written about the engineering of self-managing systems as a distinct paradigm. In this paper we suggest a straw-man for engineering of autonomic systems that is based on two essential tracks: a set of engineering principles that should guide the planning of autonomic systems and their interfaces and secondly a set of mathematical foundations upon which such systems can best be constructed. These foundational attributes are intended to guide the thinking of R&D organizations pursuing the development of autonomic computing capability. The role of architecture and standards is also discussed, highlighting their role in inter-component management.

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Autonomic computing for relational databases: the ten-year vision

Cited by 16 publications

References 14 publications

Optimized self-healing framework for software defined networks

Optimized self-healing framework for software defined networks

The Psychic–Skeptic Prediction framework for effective monitoring of DBMS workloads

Foundations of Autonomic Computing Development

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