32,217 research outputs found
Queuing theory-based latency/power tradeoff models for replicated search engines
Large-scale search engines are built upon huge infrastructures involving thousands of computers in order to achieve fast response times. In contrast, the energy consumed (and hence the financial cost) is also high, leading to environmental damage.
This paper proposes new approaches to increase energy and financial savings in large-scale search engines, while maintaining good query response times. We aim to improve current state-of-the-art models used for balancing power and latency, by integrating new advanced features. On one hand, we propose to improve the power savings by completely powering down the query servers that are not necessary when the load of the system is low. Besides, we consider energy rates into the model formulation. On the other hand, we focus on how to accurately estimate the latency of the whole system by means of Queueing Theory.
Experiments using actual query logs attest the high energy (and financial) savings regarding current baselines. To the best of our knowledge, this is the first paper in successfully applying stationary Queueing Theory models to estimate the latency in a large-scale search engine
A Virtual Network PaaS for 3GPP 4G and Beyond Core Network Services
Cloud computing and Network Function Virtualization (NFV) are emerging as key
technologies to overcome the challenges facing 4G and beyond mobile systems.
Over the last few years, Platform-as-a-Service (PaaS) has gained momentum and
has become more widely adopted throughout IT enterprises. It simplifies the
applications provisioning and accelerates time-to-market while lowering costs.
Telco can leverage the same model to provision the 4G and beyond core network
services using NFV technology. However, many challenges have to be addressed,
mainly due to the specificities of network services. This paper proposes an
architecture for a Virtual Network Platform-as-a-Service (VNPaaS) to provision
3GPP 4G and beyond core network services in a distributed environment. As an
illustrative use case, the proposed architecture is employed to provision the
3GPP Home Subscriber Server (HSS) as-a-Service (HSSaaS). The HSSaaS is built
from Virtualized Network Functions (VNFs) resulting from a novel decomposition
of HSS. A prototype is implemented and early measurements are made.Comment: 7 pages, 6 figures, 2 tables, 5th IEEE International Conference on
Cloud Networking (IEEE CloudNet 2016
Intrusion Detection Systems for Community Wireless Mesh Networks
Wireless mesh networks are being increasingly used to provide affordable network connectivity to communities where wired deployment strategies are either not possible or are prohibitively expensive. Unfortunately, computer networks (including mesh networks) are frequently being exploited by increasingly profit-driven and insidious attackers, which can affect their utility for legitimate use. In response to this, a number of countermeasures have been developed, including intrusion detection systems that aim to detect anomalous behaviour caused by attacks. We present a set of socio-technical challenges associated with developing an intrusion detection system for a community wireless mesh network. The attack space on a mesh network is particularly large; we motivate the need for and describe the challenges of adopting an asset-driven approach to managing this space. Finally, we present an initial design of a modular architecture for intrusion detection, highlighting how it addresses the identified challenges
SARSCEST (human factors)
People interact with the processes and products of contemporary technology. Individuals are affected by these in various ways and individuals shape them. Such interactions come under the label 'human factors'. To expand the understanding of those to whom the term is relatively unfamiliar, its domain includes both an applied science and applications of knowledge. It means both research and development, with implications of research both for basic science and for development. It encompasses not only design and testing but also training and personnel requirements, even though some unwisely try to split these apart both by name and institutionally. The territory includes more than performance at work, though concentration on that aspect, epitomized in the derivation of the term ergonomics, has overshadowed human factors interest in interactions between technology and the home, health, safety, consumers, children and later life, the handicapped, sports and recreation education, and travel. Two aspects of technology considered most significant for work performance, systems and automation, and several approaches to these, are discussed
BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations
Objective: The advent of High-Performance Computing (HPC) in recent years has
led to its increasing use in brain study through computational models. The
scale and complexity of such models are constantly increasing, leading to
challenging computational requirements. Even though modern HPC platforms can
often deal with such challenges, the vast diversity of the modeling field does
not permit for a single acceleration (or homogeneous) platform to effectively
address the complete array of modeling requirements. Approach: In this paper we
propose and build BrainFrame, a heterogeneous acceleration platform,
incorporating three distinct acceleration technologies, a Dataflow Engine, a
Xeon Phi and a GP-GPU. The PyNN framework is also integrated into the platform.
As a challenging proof of concept, we analyze the performance of BrainFrame on
different instances of a state-of-the-art neuron model, modeling the Inferior-
Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley
representation. The model instances take into account not only the neuronal-
network dimensions but also different network-connectivity circumstances that
can drastically change application workload characteristics. Main results: The
synthetic approach of three HPC technologies demonstrated that BrainFrame is
better able to cope with the modeling diversity encountered. Our performance
analysis shows clearly that the model directly affect performance and all three
technologies are required to cope with all the model use cases.Comment: 16 pages, 18 figures, 5 table
Augmenting conversations through context-aware multimedia retrieval based on speech recognition
Future’s environments will be sensitive and responsive to the presence of people to support them carrying out their everyday life activities, tasks and rituals, in an easy and natural way. Such interactive spaces will use the information and communication technologies to bring the computation into the physical world, in order to enhance ordinary activities of their users. This paper describes a speech-based spoken multimedia retrieval system that can be used to present relevant video-podcast (vodcast) footage, in response to spontaneous speech and conversations during daily life activities. The proposed system allows users to search the spoken content of multimedia files rather than their associated meta-information and let them navigate to the right portion where queried words are spoken by facilitating within-medium searches of multimedia content through a bag-of-words approach. Finally, we have studied the proposed system on different scenarios by using vodcasts in English from various categories, as the targeted multimedia, and discussed how it would enhance people’s everyday life activities by different scenarios including education, entertainment, marketing, news and workplace
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