Estimating and Enhancing Real-Time Data Service Delays: Control-Theoretic Approaches

Kang, Kyoung-Don; Zhou, Yan; Oh, Jisu

doi:10.1109/tkde.2010.138

Cited by 9 publications

(5 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Caching decisions are likely to be dependent on the delay tolerance of different IoT applications [27] and their require-ments on data freshness [28] [29]. Some information pieces that are periodically delivered to a remote monitoring centre for performance tracking purposes are delay tolerant [30], whereas others relating to critical events must be relayed urgently to a remote control centre [31].…”

Section: A In-network Cachingmentioning

confidence: 99%

See 1 more Smart Citation

Caching Transient Data in Internet Content Routers

Vural

Wang

Navaratnam

et al. 2017

IEEE/ACM Trans. Networking

View full text Add to dashboard Cite

Abstract-The Internet-of-Things (IoT) paradigm envisions billions of devices all connected to the Internet, generating low-rate monitoring and measurement data to be delivered to application servers or end-users. Recently, the possibility of applying innetwork data caching techniques to IoT traffic flows has been discussed in research forums. The main challenge as opposed to the typically cached content at routers, e.g. multimedia files, is that IoT data are transient and therefore require different caching policies. In fact, the emerging location-based services can also benefit from new caching techniques that are specifically designed for small transient data. This paper studies in-network caching of transient data at content routers, considering a key temporal data property: data item lifetime. An analytical model that captures the trade-off between multihop communication costs and data item freshness is proposed. Simulation results demonstrate that caching transient data is a promising information-centric networking technique that can reduce the distance between content requesters and the location in the network where the content is fetched from. To the best of our knowledge, this is a pioneering research work aiming to systematically analyse the feasibility and benefit of using Internet routers to cache transient data generated by IoT applications.

show abstract

Section: A In-network Cachingmentioning

confidence: 99%

“…a few hours, until being discarded by the publishers. Finally, stock quotes and trade transactions [29] also deal with real-time data service requests. By caching these transient items in routers, systems can react to application requests for real-time data more quickly.…”

Section: A In-network Cachingmentioning

confidence: 99%

Caching Transient Data in Internet Content Routers

Vural

Wang

Navaratnam

et al. 2017

IEEE/ACM Trans. Networking

View full text Add to dashboard Cite

show abstract

“…Concretely, the similarity between two subgraphs is minimized, while the similarity within each subgraph is maximized (line 1). When is split to multiple subclusters, we remove and related edges from the cluster network (lines 5-10), and add the generated subclusters with related edges into the cluster network (lines [11][12][13][14][15][16][17][18][19][20][21][22][23]. Note that the weights on the edges between two DP service vectors in a cluster are updated in lines 4-15 of Algorithm 2.…”

Section: : End Formentioning

confidence: 99%

“…DP services are common nowadays [5]- [7]. Besides data-driven Web services, DP services can also be services built upon data centers, 2 Grid data sources [8], scientific services [9], pervasive and location-based data services [10], [11], data access service [12], [13], real-time data services [14], and even data correlation between Web pages [15]. Different from EP services which are usually modeled by means of input, output, preconditions, and effects [16], DP services have no preconditions and do not bring effects.…”

Section: Introductionmentioning

confidence: 99%

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

Zhou

Sellami

Gaaloul

et al. 2013

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

In service-oriented computing, a user usually needs to locate a desired service for: (i) fulfilling her requirements or (ii) replacing a service, which disappears or is unavailable for some reasons, to perform an interaction. With the increasing number of services available within an enterprise and over the Internet, locating a service online may not be appropriate from the performance perspective, especially in large Internet-based service repositories. Instead, services usually need to be clustered according to their similarity. Thereafter, services in one or several clusters are necessary to be examined online during dynamic service discovery. In this paper, we propose to cluster data providing (DP) services using a refined fuzzy -means algorithm. We consider the composite relation between DP service elements (i.e., input, output, and semantic relation between them) when representing DP services in terms of vectors. A DP service vector is assigned to one or multiple clusters with certain degrees. In addition, we introduce some operations for managing service clusters, when new services emerge or existing services disappear or become unavailable. When grouping similar services into one cluster, while partitioning different services into different clusters, the capability of service search engine is improved significantly. We have prototyped our approach and the source code is freely available on the web. We have evaluated our clustering approach in different settings and the results are very promising.Note to Practitioners-DP services are common nowadays, and there are a huge number of DP services in the Internet-scale environment. Locating an appropriate DP service accurately and efficiently with respect to the requirements of a certain requestor is a challenging task. This work presents a novel clustering-oriented approach, which aims to group DP services into clusters offline leveraging the semantic description of these DP services, and provides operations for managing these clusters. The clustering procedure is conducted by means of a machine learning technique which is a refined fuzzy -means method. A DP service can be assigned to one or several clusters with certain degrees. DP service clusters constitute a cluster network. Operations are provided for facilitating the evolution of cluster network, when a DP service emerges or disappears sometime for some reason. A prototype has been implemented and the approach has been evaluated on two test collections of DP services considering factors impacting the efficiency. Our method can be readily used in industrial DP service repository for supporting DP service discovery and replacement.

show abstract

“…Skillicorn, Martin (2011),Chang, Fan (2008),Cao, Zhang, Zhou (2008),Mohammadnezhad-Shourkaei et al (2011) eLingras, Chen, Miao (2009), tratando respectivamente dos seguintes problemas: diversas aplicações de telecomunicações, web logs, aplicações financeiras e análise de sensores de dados trabalham com fluxos de dados com elevadas taxas de transmissão, criando novas perspectivas em mineração de dados; A mineração de dados é uma abordagem eficiente para a análise de séries temporais utilizando wavelet, e demonstrou ser especialmente produtiva na análise, modelagem e previsão do comportamento de instrumentos financeiros em detrimento de técnicas como redes neurais; infra-estrutura corporativa on-line construída para a mineração de dados financeiros e de investigação e desenvolvimento multiagentes; árvores de decisão juntamente com a técnica de programação linear inteira mista podem modelar as taxas de falha dependentes do tempo de equipamentos nas redes de distribuição de energia e para avaliar a eficácia de várias estratégias de manutenção; definição de clusters de perfil de gastos pessoais.No que tange o raciocínio incerto, 5 artigos trataram o assunto Chang, Fan, Liu (2009),Huang, Pasquier, Quek (2009),Chan, Milanovic, Delahunty (2011). eKang, Zhou, Oh (2011) tratam da utilização de lógica fuzzy para tratar os seguintes problemas respectivamente: diversas limitações para os modelos de previsão de preços de ações são o ruído, a dimensionalidade complexa e a quantidade de dados de preços; teóricos financeiros questionam a possibilidade de prever o mercado financeiro usando apenas análise técnica; na perda financeira relativa a interrupção no fornecimento de energia em uma planta industrial, de modo a constar a variação do valor de perda na modelo de avaliação de risco; na análise da eficácia temporal de dados que deve ser suportada por meio da atualização periódica de dados temporais, como os preços de ações.Angelov et al (2008) comentam que a Lógica fuzzy baseada em regras de sistema tornaram-se uma das estruturas alternativas para o projeto de classificadores de fluxo de dado em processos industriais avançados, sistemas autônomos, aviação, indústria financeira, mercados consumidores, etc. Na linha de representação de conhecimento foram encontrados 2 artigos.…”

unclassified

Aplicação Da Teoria Das Filas: Melhoria Do Atendimento Do Hospital Universitário Maria Aparecida Pedrossian

Júnior¹,

Carvalho²

2018

A Engenharia De Produção Na Contemporaneidade 3

View full text Add to dashboard Cite

Engenharia econômica. 2. Engenharia de produção. 3.Pesquisa operacional. I. Título.CDD 658.5 Elaborado por Maurício Amormino Júnior -CRB6/2422 O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores. 2018 Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterá-la de nenhuma forma ou utilizá-la para fins comerciais.www.atenaeditora.com.br APRESENTAÇÃOA obra "A Engenharia de Produção na Contemporaneidade" aborda uma série de livros de publicação da Atena Editora. O volume III apresenta, em seus 25 capítulos, os novos conhecimentos para a engenharia de produção nas áreas de engenharia econômica e pesquisa operacional na tomada de decisão.As áreas temáticas de engenharia econômica e pesquisa operacional na tomada de decisão, tratam de temas relevantes para otimização dos recursos organizacionais.A constante mutação neste cenário torna necessária a inovação na forma de pensar e fazer gestão, planejar e controlar as organizações, para que estas tornem-se agentes de desenvolvimento técnico-científico, econômico e social.Tanto as ferramentas da engenharia econômica, como os estudos da pesquisa operacional, auxiliam no processo de tomada de decisão, tornando-as mais assertivas e economicamente eficientes.Este volume dedicado à aplicação da engenharia econômica e pesquisa operacional na tomada de decisão traz artigos que tratam de temas emergentes sobre a gestão de custos e informações econômicas, análise de viabilidade, gestão financeira e de desempenho, pesquisa operacional e aplicação de métodos multicritério na tomada de decisão.Aos autores dos capítulos, ficam registrados os agradecimentos do Organizador e da Atena Editora, pela dedicação e empenho sem limites que tornaram realidade esta obra, que retrata os recentes avanços científicos do tema.Por fim, espero que esta obra venha a corroborar no desenvolvimento de novos conhecimentos e inovações, e auxilie os estudantes e pesquisadores na imersão em novas reflexões acerca dos tópicos relevantes na área de engenharia de produção.Boa leitura!

show abstract

Estimating and Enhancing Real-Time Data Service Delays: Control-Theoretic Approaches

Cited by 9 publications

References 25 publications

Caching Transient Data in Internet Content Routers

Caching Transient Data in Internet Content Routers

Data Providing Services Clustering and Management for Facilitating Service Discovery and Replacement

Aplicação Da Teoria Das Filas: Melhoria Do Atendimento Do Hospital Universitário Maria Aparecida Pedrossian

Contact Info

Product

Resources

About