Standards for Autonomic Computing

Tewari, Vijay

doi:10.1535/itj.1004.03

Cited by 14 publications

(6 citation statements)

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“…The desired end state is a server that, right out of the box, and once plugged into the data center network infrastructure, without any manual intervention whatsoever, becomes a full active participant (an "infrastructure as a service") of the data center resource management layer, capable of interacting with data center management components in a vendor independent fashion, using standard management/automation technologies [33] such as the Distributed Management Task Force's (DMTF) Common Information Model (CIM) [10], CIM-XML [13] or WSManagement [9], and the Service Location Protocol (SLP) [14] over reliable communication protocols like TCP.…”

Section: Problem Statementmentioning

confidence: 99%

Enabling dynamic data centers with a smart bare-metal server platform

et al. 2010

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Ever increasing data center complexity poses a significant burden on IT administrators. This burden can become unbearable without the help of self-managed systems that monitor themselves and automatically modify their state in order to carry out business processes according to high level objectives set by service level agreements (SLA) and policies. Among the key IT management tasks that must be automated and enhanced to realize the idea of an autonomic and highly dynamic data center, are discovery, configuration, and provisioning of new servers. In this direction, this paper describes pre-boot capabilities endowing the bare metal server with the ability to be discovered, queried, configured, and provisioned at time zero using industry standards like Common Information Model (CIM), CIM-XML, and Service Location Protocol (SLP). The capabilities are implemented as a payload of an Intel® Extensible Firmware Interface (EFI)-compliant BIOS, the Intel® Rapid Boot Toolkit (IRBT), allowing a resource manager to discover a new server during pre-boot, possibly in a baremetal state, and then perform an asset inventory, configure

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Section: Problem Statementmentioning

confidence: 99%

Enabling dynamic data centers with a smart bare-metal server platform

et al. 2010

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“…As a consequence, AM S will be informed of the decision as it will receive a proposal for a new application graph with the extra node n w 5 and the related new arcs (n e , n w 5 ), (n w 5 , n c ). The node will have associated some metadata stating where it will be placed 13 . Two cases arise: either the metadata already includes the kind of node (secure, non-secure), or the AM S will be able to determine such information from the metadata and from the other information it already has (or it can derive by monitoring).…”

Section: Sample Case Studymentioning

confidence: 99%

“…It is mostly likely that the AM W will conclude the consensus phase with a NACK and this will be handled with the techniques described above in the context of a NACK coming from AM S . However, in this case alternative 13 generated by the query to the resource manager hidden in the f indN ewResource action strategies can be implemented. In fact, unlike the security concern, the power saving concern is not a binary issue.…”

Section: Sample Case Studymentioning

confidence: 99%

“…Wikipedia gives a slightly different definition of this: In general, functional requirements define what a system is supposed to do whereas non-functional requirements define how a system is supposed to be. (http://en.wikipedia.org/wiki/Non-functional_requirement)2 http://gridcomp.ercim.org/content/view/26/34/ 3 quoting[13]: In larger systems with a hierarchical architecture, managers must be able to interact with each other.…”

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confidence: 99%

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Autonomic management of multiple non-functional concerns in behavioural skeletons

Aldinucci,

Danelutto,

Kilpatrick

2009

Preprint

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We introduce and address the problem of concurrent autonomic management of different non-functional concerns in parallel applications build as a hierarchical composition of behavioural skeletons. We first define the problems arising when multiple concerns are dealt with by independent managers, then we propose a methodology supporting coordinated management, and finally we discuss how autonomic management of multiple concerns may be implemented in a typical use case. The paper concludes with an outline of the challenges involved in realizing the proposed methodology on distributed target architectures such as clusters and grids. Being based on the behavioural skeleton concept proposed in the CoreGRID GCM, it is anticipated that the methodology will be readily integrated into the current reference implementation of GCM based on Java ProActive and running on top of major grid middleware systems.

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“…OOB interfaces are commonly independent of the host operating environment, which could be an OS or a Virtual Machine Monitor (VMM) with one or more OSs. In the article "Standards for Autonomic Computing" [12], in this issue of the Intel Technology Journal, a more detailed overview is given of the importance of standardization in autonomic computing and the benefits of using Web services as external interfaces.…”

Section: Standard Out-of-band External Interfacesmentioning

confidence: 99%

Platform Support of Autonomic Computing: an Evolution of Manageability Architecture

Durham¹

2006

ITJ

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Autonomic Computing (AC) is maturing from a design philosophy to an emerging set of technologies and products that addresses the complexity of managing today's heterogeneous data centers and computing environments. This overview paper explains our motivation and outlines our technologies that provide platform support for AC. Specifically, we are developing platforms with sufficient support and on-board intelligence to enable autonomic capabilities, such as selfhealing and self-protecting, as well as features such as discovery and asset tracking, even when the host Operating System (OS) is inactive. To achieve these ends we are dedicating select platform resources and firmware, both exposed via well-defined standard interfaces, to implement a set of management and autonomic capabilities, and in the future, we hope to extend these platform autonomic capabilities, with appropriate management policies, to groups of platforms and eventually to the entire data center. Such interconnected autonomic platforms will provide the infrastructure and fabric to support service-oriented, grid, and utility computing. This paper also expounds on the Intel ® Active Management Technology † (Intel AMT) which is the first product incarnation of a framework and dedicated platform execution environment for AC. We also discuss how manageability architectures need to evolve to support autonomic behavior at a group level, such as defining interactions among platforms within a group to collectively deliver on specific goals and implement group-level policies. We cite examples related to malware detection and power management that illustrate how this new approach to managing IT infrastructure works. INFORMATION TECHNOLOGY OVERVIEW Today, Information Technology (IT) departments are plagued by increasing complexity, poor utilization of assets, space, and high power consumption. Further, system management in such environments is fragmented and labor-intensive requiring considerable human involvement for mundane functions such as configuration and provisioning. Such common inefficiencies in data centers force IT managers to provision their data centers for peak loads resulting in low average resource utilization and availability in the range of 99.99% or possibly less. Current data center deployments tend to have strong and static binding between servers and applications, as well as between servers and administrators, due mainly to a lack of technology to deploy otherwise. To improve the efficiency of assets, space, and power, IT managers turned to virtualization, which provides the ability to consolidate multiple applications onto a single server (a server could be stand-alone, rack-mounted or bladed). These servers may include advanced technologies that support multiple logical and physical partitions within each physical machine such as virtualization, partitioning hooks, and multiple cores. These advanced technologies have increased the cost and complexity of platforms and require that management solutions adapt to deal with them. Unfortunat...

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Standards for Autonomic Computing

Cited by 14 publications

References 0 publications

Enabling dynamic data centers with a smart bare-metal server platform

Enabling dynamic data centers with a smart bare-metal server platform

Autonomic management of multiple non-functional concerns in behavioural skeletons

Platform Support of Autonomic Computing: an Evolution of Manageability Architecture

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