PDRM : a proactive data replication mechanism to improve content mobility support in NDN using location awareness

The problem of handling user mobility has been around since mobile devices became capable of handling multimedia content and is still one of the most relevant challenges in networking. The conventional Internet architecture is inadequate in dealing with an ever-growing number of mobile devices that are both consuming and producing content. Named Data Networking (NDN) is a network architecture that can potentially overcome this mobility challenge. It supports consumer mobility by design but fails to offer the same level of support for content mobility. Content mobility requires guaranteeing that consumers manage to find and retrieve desired content even when the corresponding producer (or primary host) is not available. In this thesis, we propose PDRM, a Proactive and locality-aware Data Replication Mechanism that increases content availability through data redundancy in the context of the NDN architecture. It explores available resources from end-users in the vicinity to improve content availability even in the case of producer mobility. Throughout the thesis, we discuss the design of PDRM, evaluate the impact of the number of available providers in the vicinity and in-network cache capacity on its operation, and compare its performance to Vanilla NDN and two state-of-the-art proposals. The evaluation indicates that PDRM improves content mobility support due to using object popularity information and spare resources in the vicinity to help the proactive replication. Results show that PDRM can reduce the download times up to 53.55%, producer load up to 71.6%, inter-domain traffic up to 46.5%, and generated overhead up to 25% compared to Vanilla NDN and other evaluated mechanisms.O problema de lidar com a mobilidade dos usuários existe desde que os dispositivos móveis se tornaram capazes de lidar com conteúdo multimídia e ainda é um dos desafios mais relevantes na área de redes de computadores. A arquitetura de Internet convencional é inadequada em lidar com um número cada vez maior de dispositivos móveis que estão tanto consumindo quanto produzindo conteúdo. Named Data Networking (NDN) é uma arquitetura de rede que pode potencialmente superar este desafio de mobilidade. Ela suporta a mobilidade do consumidor nativamente, mas não oferece o mesmo nível de suporte para a mobilidade de conteúdo. A mobilidade de conteúdo exige garantir que os consumidores consigam encontrar e recuperar o conteúdo desejado mesmo quando o produtor correspondente (ou o hospedeiro principal) não estiver disponível. Nesta tese, propomos o PDRM (Proactive Data Replication Mechanism), um mecanismo de replicação de dados proativo e consciente de localização, que aumenta a disponibilidade de conteúdo através da redundância de dados no contexto da arquitetura NDN. Ele explora os recursos disponíveis dos usuários finais na vizinhança para melhorar a disponibilidade de conteúdo, mesmo no caso da mobilidade do produtor. Ao longo da tese, discutimos o projeto do PDRM, avaliamos o impacto do número de provedores disponíveis na vizinhança e a capacidade de cache na rede em sua operação e comparamos seu desempenho com NDN padrão e duas propostas do estado-da-arte. A avaliação indica que o PDRM melhora o suporte à mobilidade de conteúdo devido ao uso de informações de popularidade dos objetos e recursos extras na vizinhança para ajudar a replicação pró-ativa. Os resultados mostram que o PDRM pode reduzir os tempos de download até 53,55%, o carregamento do produtor até 71,6%, o tráfego entre domínios até 46,5% e a sobrecarga gerada até 25% em comparação com NDN padrão e os demais mecanismos avaliados

ANFIS TVA Power Plants Availability Modeling Development

In the present chapter, the evaluation of the Tennessee Valley Authority (TVA) Markov model transient behavior is derived and studied. It is focused on finding the models of the transient-state availability and unavailability of the four (TVA) models among using an adaptive neuro-fuzzy inference system (ANFIS). The developed ANFIS model for the TVA models is derived, and both availability and unavailability of the four TVA models are derived using the curve fitting technique, where each model of the transient availability of the three-state models of the TVA models is found. Each model is considered as a three-state model, and its equations obtained using the curve fitting technique are helping for the future availabilities and unavailabilities. The availability is a very important measure of performance for the availability of TVA power plants. The technique is used and applied on the four models in the present study to formulate and obtain the TVA models’ results and are compared. In addition, the generation effects on the reliability investigation. The generation study evaluates the improvement in reliability over a time

Resource considerate data routing through satellite networks

In many envisaged satellite-based networks, such as constellations or federations, there often exists a desire to reduce data latency, increase delivered data volume, or simply exploit unused resources. A strategy is presented that achieves efficient routing of data, in a store-carry-forward fashion, through satellite networks that exhibit delay- and disruption-tolerant network characteristics. This network-layer protocol, termed Spae, exploits information about the schedule of future contacts between network nodes, because satellite motion is deterministic, along with the capacity of these contacts to route data in such a way as to avoid significant overcommitment of data along a resource limited journey. Results from simulations of a federated satellite system indicate consistent benefit in terms of network performance over other, less-sophisticated, conventional methods, and comparable performance to a packet-optimal, full-knowledge approach

QOE-AWARE CONTENT DISTRIBUTION SYSTEMS FOR ADAPTIVE BITRATE VIDEO STREAMING

A prodigious increase in video streaming content along with a simultaneous rise in end system capabilities has led to the proliferation of adaptive bit rate video streaming users in the Internet. Today, video streaming services range from Video-on-Demand services like traditional IP TV to more recent technologies such as immersive 3D experiences for live sports events. In order to meet the demands of these services, the multimedia and networking research community continues to strive toward efficiently delivering high quality content across the Internet while also trying to minimize content storage and delivery costs. The introduction of flexible and adaptable technologies such as compute and storage clouds, Network Function Virtualization and Software Defined Networking continue to fuel content provider revenue. Today, content providers such as Google and Facebook build their own Software-Defined WANs to efficiently serve millions of users worldwide, while NetFlix partners with ISPs such as ATT (using OpenConnect) and cloud providers such as Amazon EC2 to serve their content and manage the delivery of several petabytes of high-quality video content for millions of subscribers at a global scale, respectively. In recent years, the unprecedented growth of video traffic in the Internet has seen several innovative systems such as Software Defined Networks and Information Centric Networks as well as inventive protocols such as QUIC, in an effort to keep up with the effects of this remarkable growth. While most existing systems continue to sub-optimally satisfy user requirements, future video streaming systems will require optimal management of storage and bandwidth resources that are several orders of magnitude larger than what is implemented today. Moreover, Quality-of-Experience metrics are becoming increasingly fine-grained in order to accurately quantify diverse content and consumer needs. In this dissertation, we design and investigate innovative adaptive bit rate video streaming systems and analyze the implications of recent technologies on traditional streaming approaches using real-world experimentation methods. We provide useful insights for current and future content distribution network administrators to tackle Quality-of-Experience dilemmas and serve high quality video content to several users at a global scale. In order to show how Quality-of-Experience can benefit from core network architectural modifications, we design and evaluate prototypes for video streaming in Information Centric Networks and Software-Defined Networks. We also present a real-world, in-depth analysis of adaptive bitrate video streaming over protocols such as QUIC and MPQUIC to show how end-to-end protocol innovation can contribute to substantial Quality-of-Experience benefits for adaptive bit rate video streaming systems. We investigate a cross-layer approach based on QUIC and observe that application layer-based information can be successfully used to determine transport layer parameters for ABR streaming applications

Information-centric communication in mobile and wireless networks

Information-centric networking (ICN) is a new communication paradigm that has been proposed to cope with drawbacks of host-based communication protocols, namely scalability and security. In this thesis, we base our work on Named Data Networking (NDN), which is a popular ICN architecture, and investigate NDN in the context of wireless and mobile ad hoc networks. In a first part, we focus on NDN efficiency (and potential improvements) in wireless environments by investigating NDN in wireless one-hop communication, i.e., without any routing protocols. A basic requirement to initiate informationcentric communication is the knowledge of existing and available content names. Therefore, we develop three opportunistic content discovery algorithms and evaluate them in diverse scenarios for different node densities and content distributions. After content names are known, requesters can retrieve content opportunistically from any neighbor node that provides the content. However, in case of short contact times to content sources, content retrieval may be disrupted. Therefore, we develop a requester application that keeps meta information of disrupted content retrievals and enables resume operations when a new content source has been found. Besides message efficiency, we also evaluate power consumption of information-centric broadcast and unicast communication. Based on our findings, we develop two mechanisms to increase efficiency of information-centric wireless one-hop communication. The first approach called Dynamic Unicast (DU) avoids broadcast communication whenever possible since broadcast transmissions result in more duplicate Data transmissions, lower data rates and higher energy consumption on mobile nodes, which are not interested in overheard Data, compared to unicast communication. Hence, DU uses broadcast communication only until a content source has been found and then retrieves content directly via unicast from the same source. The second approach called RC-NDN targets efficiency of wireless broadcast communication by reducing the number of duplicate Data transmissions. In particular, RC-NDN is a Data encoding scheme for content sources that increases diversity in wireless broadcast transmissions such that multiple concurrent requesters can profit from each others’ (overheard) message transmissions. If requesters and content sources are not in one-hop distance to each other, requests need to be forwarded via multi-hop routing. Therefore, in a second part of this thesis, we investigate information-centric wireless multi-hop communication. First, we consider multi-hop broadcast communication in the context of rather static community networks. We introduce the concept of preferred forwarders, which relay Interest messages slightly faster than non-preferred forwarders to reduce redundant duplicate message transmissions. While this approach works well in static networks, the performance may degrade in mobile networks if preferred forwarders may regularly move away. Thus, to enable routing in mobile ad hoc networks, we extend DU for multi-hop communication. Compared to one-hop communication, multi-hop DU requires efficient path update mechanisms (since multi-hop paths may expire quickly) and new forwarding strategies to maintain NDN benefits (request aggregation and caching) such that only a few messages need to be transmitted over the entire end-to-end path even in case of multiple concurrent requesters. To perform quick retransmission in case of collisions or other transmission errors, we implement and evaluate retransmission timers from related work and compare them to CCNTimer, which is a new algorithm that enables shorter content retrieval times in information-centric wireless multi-hop communication. Yet, in case of intermittent connectivity between requesters and content sources, multi-hop routing protocols may not work because they require continuous end-to-end paths. Therefore, we present agent-based content retrieval (ACR) for delay-tolerant networks. In ACR, requester nodes can delegate content retrieval to mobile agent nodes, which move closer to content sources, can retrieve content and return it to requesters. Thus, ACR exploits the mobility of agent nodes to retrieve content from remote locations. To enable delay-tolerant communication via agents, retrieved content needs to be stored persistently such that requesters can verify its authenticity via original publisher signatures. To achieve this, we develop a persistent caching concept that maintains received popular content in repositories and deletes unpopular content if free space is required. Since our persistent caching concept can complement regular short-term caching in the content store, it can also be used for network caching to store popular delay-tolerant content at edge routers (to reduce network traffic and improve network performance) while real-time traffic can still be maintained and served from the content store

Optimized acquisition of spatially distributed phenomena in public sensing systems

Nowadays, an increasing number of popular consumer electronics is shipped with a variety of sensors. The usage of these as a wireless sensing platform, where users are the key architectural component, and ubiquitous access to communication infrastructure has established a new application area called public sensing. We present an opportunistic public sensing system that allows for a flexible and efficient acquisition of sensor readings. This work considers the usage of smartphones as a sensor network in a model-driven sensor data acquisition. We focus on efficiency of query dissemination to mobile nodes, while retaining high effectiveness regarding defined sensing quality of collected data. We adopted and extended an existing geographic routing protocol to design an efficient com- munication system that executes model-driven data acquisition and is robust to changing sensors availability. We use in-network processing paradigm to efficiently distribute queries to mobile nodes and to collect results afterwards. The developed approach was simulated using OMNeT++ network simulator. To verify implemented algorithms and test the overall system performance, we run simulations in different scenarios and evaluate them using adequate cov- erage metrics. Moreover, we verify our intuitive extension to adopted routing protocol and show that it can have a strong impact on the efficiency of protocol in question

Forecasting in Mathematics

Mathematical probability and statistics are an attractive, thriving, and respectable part of mathematics. Some mathematicians and philosophers of science say they are the gateway to mathematics’ deepest mysteries. Moreover, mathematical statistics denotes an accumulation of mathematical discussions connected with efforts to most efficiently collect and use numerical data subject to random or deterministic variations. Currently, the concept of probability and mathematical statistics has become one of the fundamental notions of modern science and the philosophy of nature. This book is an illustration of the use of mathematics to solve specific problems in engineering, statistics, and science in general

Compound popular content caching strategy to enhance the cache management performance in named data networking

Named Data Networking (NDN) is a leading research paradigm for the future Internet architecture. The NDN offers in-network cache which is the most beneficial feature to reduce the difficulties of the location-based Internet paradigm. The objective of cache is to achieve a scalable, effective, and consistent distribution of information. However, the main issue which NDN facing is the selection of appropriate router during the content’s transmission that can disrupt the overall network performance. The reason is that how each router takes a decision to the cache which content needs to cache at what location that can enhance the complete caching performance. Therefore, several cache management strategies have been developed. Still, it is not clear which caching strategy is the most ideal for each situation. This study proposes a new cache management strategy named as Compound Popular Content Caching Strategy (CPCCS) to minimize cache redundancy with enhanced diversity ratio and improving the accessibility of cached content by providing short stretch paths. The CPCCS was developed by combining two mechanisms named as Compound Popular Content Selection (CPCS) and Compound Popular Content Caching (CPCC) to differentiate the contents regarding their Interest frequencies using dynamic threshold and to find the best possible caching positions respectively. CPCCS is compared with other NDN-based caching strategies, such as Max-Gain In-network Caching, WAVE popularity-based caching strategy, Hop-based Probabilistic Caching, Leaf Popular Down, Most Popular Cache, and Cache Capacity Aware Caching in a simulation environment. The results show that the CPCCS performs better in which the diversity and cache hit ratio are increased by 34% and 14% respectively. In addition, the redundancy and path stretch are decreased by 44% and 46% respectively. The outcomes showed that the CPCCS have achieved enhanced caching performance with respect to different cache size (1GB to 10GB) and simulation parameters than other caching strategies. Thus, CPCCS can be applicable in future for the NDN-based emerging technologies such as Internet of Things, fog and edge computing