842 research outputs found
A Survey on Graph Database Management Techniques for Huge Unstructured Data
Data analysis, data management, and big data play a major role in both social and business perspective, in the last decade. Nowadays, the graph database is the hottest and trending research topic. A graph database is preferred to deal with the dynamic and complex relationships in connected data and offer better results. Every data element is represented as a node. For example, in social media site, a person is represented as a node, and its properties name, age, likes, and dislikes, etc and the nodes are connected with the relationships via edges. Use of graph database is expected to be beneficial in business, and social networking sites that generate huge unstructured data as that Big Data requires proper and efficient computational techniques to handle with. This paper reviews the existing graph data computational techniques and the research work, to offer the future research line up in graph database management
SeaNet -- Towards A Knowledge Graph Based Autonomic Management of Software Defined Networks
Automatic network management driven by Artificial Intelligent technologies
has been heatedly discussed over decades. However, current reports mainly focus
on theoretic proposals and architecture designs, works on practical
implementations on real-life networks are yet to appear. This paper proposes
our effort toward the implementation of knowledge graph driven approach for
autonomic network management in software defined networks (SDNs), termed as
SeaNet. Driven by the ToCo ontology, SeaNet is reprogrammed based on Mininet (a
SDN emulator). It consists three core components, a knowledge graph generator,
a SPARQL engine, and a network management API. The knowledge graph generator
represents the knowledge in the telecommunication network management tasks into
formally represented ontology driven model. Expert experience and network
management rules can be formalized into knowledge graph and by automatically
inferenced by SPARQL engine, Network management API is able to packet
technology-specific details and expose technology-independent interfaces to
users. The Experiments are carried out to evaluate proposed work by comparing
with a commercial SDN controller Ryu implemented by the same language Python.
The evaluation results show that SeaNet is considerably faster in most
circumstances than Ryu and the SeaNet code is significantly more compact.
Benefit from RDF reasoning, SeaNet is able to achieve O(1) time complexity on
different scales of the knowledge graph while the traditional database can
achieve O(nlogn) at its best. With the developed network management API, SeaNet
enables researchers to develop semantic-intelligent applications on their own
SDNs
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
Intelligent Management and Efficient Operation of Big Data
This chapter details how Big Data can be used and implemented in networking
and computing infrastructures. Specifically, it addresses three main aspects:
the timely extraction of relevant knowledge from heterogeneous, and very often
unstructured large data sources, the enhancement on the performance of
processing and networking (cloud) infrastructures that are the most important
foundational pillars of Big Data applications or services, and novel ways to
efficiently manage network infrastructures with high-level composed policies
for supporting the transmission of large amounts of data with distinct
requisites (video vs. non-video). A case study involving an intelligent
management solution to route data traffic with diverse requirements in a wide
area Internet Exchange Point is presented, discussed in the context of Big
Data, and evaluated.Comment: In book Handbook of Research on Trends and Future Directions in Big
Data and Web Intelligence, IGI Global, 201
Clustering Arabic Tweets for Sentiment Analysis
The focus of this study is to evaluate the impact of linguistic preprocessing and similarity functions for clustering Arabic Twitter tweets. The experiments apply an optimized version of the standard K-Means algorithm to assign tweets into positive and negative categories. The results show that root-based stemming has a significant advantage over light stemming in all settings. The Averaged Kullback-Leibler Divergence similarity function clearly outperforms the Cosine, Pearson Correlation, Jaccard Coefficient and Euclidean functions. The combination of the Averaged Kullback-Leibler Divergence and root-based stemming achieved the highest purity of 0.764 while the second-best purity was 0.719. These results are of importance as it is contrary to normal-sized documents where, in many information retrieval applications, light stemming performs better than root-based stemming and the Cosine function is commonly used
Clustering Arabic Tweets for Sentiment Analysis
The focus of this study is to evaluate the impact of linguistic preprocessing and similarity functions for clustering Arabic Twitter tweets. The experiments apply an optimized version of the standard K-Means algorithm to assign tweets into positive and negative categories. The results show that root-based stemming has a significant advantage over light stemming in all settings. The Averaged Kullback-Leibler Divergence similarity function clearly outperforms the Cosine, Pearson Correlation, Jaccard Coefficient and Euclidean functions. The combination of the Averaged Kullback-Leibler Divergence and root-based stemming achieved the highest purity of 0.764 while the second-best purity was 0.719. These results are of importance as it is contrary to normal-sized documents where, in many information retrieval applications, light stemming performs better than root-based stemming and the Cosine function is commonly used
Fatias de rede fim-a-fim : da extração de perfis de funções de rede a SLAs granulares
Orientador: Christian Rodolfo Esteve RothenbergTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Nos últimos dez anos, processos de softwarização de redes vêm sendo continuamente diversi- ficados e gradativamente incorporados em produção, principalmente através dos paradigmas de Redes Definidas por Software (ex.: regras de fluxos de rede programáveis) e Virtualização de Funções de Rede (ex.: orquestração de funções virtualizadas de rede). Embasado neste processo o conceito de network slice surge como forma de definição de caminhos de rede fim- a-fim programáveis, possivelmente sobre infrastruturas compartilhadas, contendo requisitos estritos de desempenho e dedicado a um modelo particular de negócios. Esta tese investiga a hipótese de que a desagregação de métricas de desempenho de funções virtualizadas de rede impactam e compõe critérios de alocação de network slices (i.e., diversas opções de utiliza- ção de recursos), os quais quando realizados devem ter seu gerenciamento de ciclo de vida implementado de forma transparente em correspondência ao seu caso de negócios de comu- nicação fim-a-fim. A verificação de tal assertiva se dá em três aspectos: entender os graus de liberdade nos quais métricas de desempenho de funções virtualizadas de rede podem ser expressas; métodos de racionalização da alocação de recursos por network slices e seus re- spectivos critérios; e formas transparentes de rastrear e gerenciar recursos de rede fim-a-fim entre múltiplos domínios administrativos. Para atingir estes objetivos, diversas contribuições são realizadas por esta tese, dentre elas: a construção de uma plataforma para automatização de metodologias de testes de desempenho de funções virtualizadas de redes; a elaboração de uma metodologia para análises de alocações de recursos de network slices baseada em um algoritmo classificador de aprendizado de máquinas e outro algoritmo de análise multi- critério; e a construção de um protótipo utilizando blockchain para a realização de contratos inteligentes envolvendo acordos de serviços entre domínios administrativos de rede. Por meio de experimentos e análises sugerimos que: métricas de desempenho de funções virtualizadas de rede dependem da alocação de recursos, configurações internas e estímulo de tráfego de testes; network slices podem ter suas alocações de recursos coerentemente classificadas por diferentes critérios; e acordos entre domínios administrativos podem ser realizados de forma transparente e em variadas formas de granularidade por meio de contratos inteligentes uti- lizando blockchain. Ao final deste trabalho, com base em uma ampla discussão as perguntas de pesquisa associadas à hipótese são respondidas, de forma que a avaliação da hipótese proposta seja realizada perante uma ampla visão das contribuições e trabalhos futuros desta teseAbstract: In the last ten years, network softwarisation processes have been continuously diversified and gradually incorporated into production, mainly through the paradigms of Software Defined Networks (e.g., programmable network flow rules) and Network Functions Virtualization (e.g., orchestration of virtualized network functions). Based on this process, the concept of network slice emerges as a way of defining end-to-end network programmable paths, possibly over shared network infrastructures, requiring strict performance metrics associated to a par- ticular business case. This thesis investigate the hypothesis that the disaggregation of network function performance metrics impacts and composes a network slice footprint incurring in di- verse slicing feature options, which when realized should have their Service Level Agreement (SLA) life cycle management transparently implemented in correspondence to their fulfilling end-to-end communication business case. The validation of such assertive takes place in three aspects: the degrees of freedom by which performance of virtualized network functions can be expressed; the methods of rationalizing the footprint of network slices; and transparent ways to track and manage network assets among multiple administrative domains. In order to achieve such goals, a series of contributions were achieved by this thesis, among them: the construction of a platform for automating methodologies for performance testing of virtual- ized network functions; an elaboration of a methodology for the analysis of footprint features of network slices based on a machine learning classifier algorithm and a multi-criteria analysis algorithm; and the construction of a prototype using blockchain to carry out smart contracts involving service level agreements between administrative systems. Through experiments and analysis we suggest that: performance metrics of virtualized network functions depend on the allocation of resources, internal configurations and test traffic stimulus; network slices can have their resource allocations consistently analyzed/classified by different criteria; and agree- ments between administrative domains can be performed transparently and in various forms of granularity through blockchain smart contracts. At the end of his thesis, through a wide discussion we answer all the research questions associated to the investigated hypothesis in such way its evaluation is performed in face of wide view of the contributions and future work of this thesisDoutoradoEngenharia de ComputaçãoDoutor em Engenharia ElétricaFUNCAM
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