7,309 research outputs found
Federated and autonomic management of multimedia services
Over the years, the Internet has significantly evolved in size and complexity. Additionally, the modern multimedia services it offers have considerably more stringent Quality of Service (QoS) requirements than traditional static services. These factors contribute to the ever-increasing complexity and cost to manage the Internet and its services. In the dissertation, a novel network management architecture is proposed to overcome these problems. It supports QoS-guarantees of multimedia services across the Internet, by setting up end-to-end network federations. A network federation is defined as a persistent cross-organizational agreement that enables the cooperating networks to share capabilities. Additionally, the architecture incorporates aspects from autonomic network management to tackle the ever-growing management complexity of modern communications networks. Specifically, a hierarchical approach is presented, which guarantees scalable collaboration of huge amounts of self-governing autonomic management components
Autonomic computing meets SCADA security
© 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security
Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements
Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)
Autonomic Cloud Computing: Open Challenges and Architectural Elements
As Clouds are complex, large-scale, and heterogeneous distributed systems,
management of their resources is a challenging task. They need automated and
integrated intelligent strategies for provisioning of resources to offer
services that are secure, reliable, and cost-efficient. Hence, effective
management of services becomes fundamental in software platforms that
constitute the fabric of computing Clouds. In this direction, this paper
identifies open issues in autonomic resource provisioning and presents
innovative management techniques for supporting SaaS applications hosted on
Clouds. We present a conceptual architecture and early results evidencing the
benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape
Self-Learning Cloud Controllers: Fuzzy Q-Learning for Knowledge Evolution
Cloud controllers aim at responding to application demands by automatically
scaling the compute resources at runtime to meet performance guarantees and
minimize resource costs. Existing cloud controllers often resort to scaling
strategies that are codified as a set of adaptation rules. However, for a cloud
provider, applications running on top of the cloud infrastructure are more or
less black-boxes, making it difficult at design time to define optimal or
pre-emptive adaptation rules. Thus, the burden of taking adaptation decisions
often is delegated to the cloud application. Yet, in most cases, application
developers in turn have limited knowledge of the cloud infrastructure. In this
paper, we propose learning adaptation rules during runtime. To this end, we
introduce FQL4KE, a self-learning fuzzy cloud controller. In particular, FQL4KE
learns and modifies fuzzy rules at runtime. The benefit is that for designing
cloud controllers, we do not have to rely solely on precise design-time
knowledge, which may be difficult to acquire. FQL4KE empowers users to specify
cloud controllers by simply adjusting weights representing priorities in system
goals instead of specifying complex adaptation rules. The applicability of
FQL4KE has been experimentally assessed as part of the cloud application
framework ElasticBench. The experimental results indicate that FQL4KE
outperforms our previously developed fuzzy controller without learning
mechanisms and the native Azure auto-scaling
Performance-oriented Cloud Provisioning: Taxonomy and Survey
Cloud computing is being viewed as the technology of today and the future.
Through this paradigm, the customers gain access to shared computing resources
located in remote data centers that are hosted by cloud providers (CP). This
technology allows for provisioning of various resources such as virtual
machines (VM), physical machines, processors, memory, network, storage and
software as per the needs of customers. Application providers (AP), who are
customers of the CP, deploy applications on the cloud infrastructure and then
these applications are used by the end-users. To meet the fluctuating
application workload demands, dynamic provisioning is essential and this
article provides a detailed literature survey of dynamic provisioning within
cloud systems with focus on application performance. The well-known types of
provisioning and the associated problems are clearly and pictorially explained
and the provisioning terminology is clarified. A very detailed and general
cloud provisioning classification is presented, which views provisioning from
different perspectives, aiding in understanding the process inside-out. Cloud
dynamic provisioning is explained by considering resources, stakeholders,
techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table
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