27,518 research outputs found
High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems)
Computing plays an essential role in all aspects of high energy physics. As
computational technology evolves rapidly in new directions, and data throughput
and volume continue to follow a steep trend-line, it is important for the HEP
community to develop an effective response to a series of expected challenges.
In order to help shape the desired response, the HEP Forum for Computational
Excellence (HEP-FCE) initiated a roadmap planning activity with two key
overlapping drivers -- 1) software effectiveness, and 2) infrastructure and
expertise advancement. The HEP-FCE formed three working groups, 1) Applications
Software, 2) Software Libraries and Tools, and 3) Systems (including systems
software), to provide an overview of the current status of HEP computing and to
present findings and opportunities for the desired HEP computational roadmap.
The final versions of the reports are combined in this document, and are
presented along with introductory material.Comment: 72 page
Monitoring Large-Scale Cloud Systems with Layered Gossip Protocols
Monitoring is an essential aspect of maintaining and developing computer
systems that increases in difficulty proportional to the size of the system.
The need for robust monitoring tools has become more evident with the advent of
cloud computing. Infrastructure as a Service (IaaS) clouds allow end users to
deploy vast numbers of virtual machines as part of dynamic and transient
architectures. Current monitoring solutions, including many of those in the
open-source domain rely on outdated concepts including manual deployment and
configuration, centralised data collection and adapt poorly to membership
churn.
In this paper we propose the development of a cloud monitoring suite to
provide scalable and robust lookup, data collection and analysis services for
large-scale cloud systems. In lieu of centrally managed monitoring we propose a
multi-tier architecture using a layered gossip protocol to aggregate monitoring
information and facilitate lookup, information collection and the
identification of redundant capacity. This allows for a resource aware data
collection and storage architecture that operates over the system being
monitored. This in turn enables monitoring to be done in-situ without the need
for significant additional infrastructure to facilitate monitoring services. We
evaluate this approach against alternative monitoring paradigms and demonstrate
how our solution is well adapted to usage in a cloud-computing context.Comment: Extended Abstract for the ACM International Symposium on
High-Performance Parallel and Distributed Computing (HPDC 2013) Poster Trac
Observing the clouds : a survey and taxonomy of cloud monitoring
This research was supported by a Royal Society Industry Fellowship and an Amazon Web Services (AWS) grant. Date of Acceptance: 10/12/2014Monitoring is an important aspect of designing and maintaining large-scale systems. Cloud computing presents a unique set of challenges to monitoring including: on-demand infrastructure, unprecedented scalability, rapid elasticity and performance uncertainty. There are a wide range of monitoring tools originating from cluster and high-performance computing, grid computing and enterprise computing, as well as a series of newer bespoke tools, which have been designed exclusively for cloud monitoring. These tools express a number of common elements and designs, which address the demands of cloud monitoring to various degrees. This paper performs an exhaustive survey of contemporary monitoring tools from which we derive a taxonomy, which examines how effectively existing tools and designs meet the challenges of cloud monitoring. We conclude by examining the socio-technical aspects of monitoring, and investigate the engineering challenges and practices behind implementing monitoring strategies for cloud computing.Publisher PDFPeer reviewe
Enabling Micro-level Demand-Side Grid Flexiblity in Resource Constrained Environments
The increased penetration of uncertain and variable renewable energy presents
various resource and operational electric grid challenges. Micro-level
(household and small commercial) demand-side grid flexibility could be a
cost-effective strategy to integrate high penetrations of wind and solar
energy, but literature and field deployments exploring the necessary
information and communication technologies (ICTs) are scant. This paper
presents an exploratory framework for enabling information driven grid
flexibility through the Internet of Things (IoT), and a proof-of-concept
wireless sensor gateway (FlexBox) to collect the necessary parameters for
adequately monitoring and actuating the micro-level demand-side. In the summer
of 2015, thirty sensor gateways were deployed in the city of Managua
(Nicaragua) to develop a baseline for a near future small-scale demand response
pilot implementation. FlexBox field data has begun shedding light on
relationships between ambient temperature and load energy consumption, load and
building envelope energy efficiency challenges, latency communication network
challenges, and opportunities to engage existing demand-side user behavioral
patterns. Information driven grid flexibility strategies present great
opportunity to develop new technologies, system architectures, and
implementation approaches that can easily scale across regions, incomes, and
levels of development
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