Bandwidth Estimation for IEEE 802.11-based Ad Hoc Networks

International audienceSince 2005, IEEE 802.11-based networks have been able to provide a certain level of quality of service (QoS) by the means of service differentiation, due to the IEEE 802.11e amendment. However, no mechanism or method has been standardized to accurately evaluate the amount of resources remaining on a given channel. Such an evaluation would, however, be a good asset for bandwidth-constrained applications. In multihop ad hoc networks, such evaluation becomes even more difficult. Consequently, despite the various contributions around this research topic, the estimation of the available bandwidth still represents one of the main issues in this field. In this paper, we propose an improved mechanism to estimate the available bandwidth in IEEE 802.11-based ad hoc networks. Through simulations, we compare the accuracy of the estimation we propose to the estimation performed by other state-of-the-art QoS protocols, BRuIT, AAC, and QoS-AODV

Bandwidth Estimation Problem & Solutions in IEEE 802.11 based Ad Hoc Networks

Abstract-With the rise in multimedia applications in ad hoc networks it is necessary to ensure the quality of service support from network. The routers which may be mobile nodes in ad hoc networks should be able to evaluate the resources available in the network, prior to offering guarantees on delay, bandwidth or any other metric. Estimating the available bandwidth is often required before performing admission control, flows management, congestion control or routing based on bandwidth constraints so that before any new flow is admitted the existing flow does not degrade. Lot of work in terms of various tools and techniques has been proposed to evaluate the available bandwidth in last decade; no consensus has yet been arrived. We present a comprehensive review on the various state of art work proposed carried out in this are

A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks

One of the major challenges for the transmission of time-sensitive data like video over mobile ad-hoc networks (MANETs) is the deployment of an end-to-end QoS support mechanism. Therefore, several approaches and enhancements have been proposed concerning the routing protocols. In this paper we propose a new QoS routing protocol based on AODV (named AQA-AODV), which creates routes according to application QoS requirements. We have introduced link and path available bandwidth estimation mechanisms and an adaptive scheme that can provide feedback to the source node about the current network state, to allow the application to appropriately adjust the transmission rate. In the same way, we propose a route recovery approach into the AQA-AODV protocol, which provides a mechanism to detect the link failures in a route and re-establish the connections taking into account the conditions of QoS that have been established during the previous route discovery phase. The simulation results reveal performance improvements in terms of packet delay, number of link failures and connection setup latency while we make more efficient use of the available bandwidth than other protocols like AODV and QAODV. In terms of video transmission, the obtained results prove that the combined use of AQA-AODV and the scalable video coding provides an efficient platform for supporting rate-adaptive video streaming.Castellanos Hernández, WE.; Guerri Cebollada, JC.; Arce Vila, P. (2016). A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks. Computer Communications. 77:10-25. doi:10.1016/j.comcom.2015.08.012S10257

TCP Sintok: Transmission control protocol with delay-based loss detection and contention avoidance mechanisms for mobile ad hoc networks

Mobile Ad hoc Network (MANET) consists of mobile devices that are connected to each other using a wireless channel, forming a temporary network without the aid of fixed infrastructure; in which hosts are free to move randomly as well as free to join or leave. This decentralized nature of MANET comes with new challenges that violate the design concepts of Transmission Control Protocol (TCP); the current dominant protocol of the Internet. TCP always infers packet loss as an indicator of network congestion and causes it to perform a sharp reduction to its sending rate. MANET suffers from several types of packet losses due to its mobility feature and contention on wireless channel access and these would lead to poor TCP performance. This experimental study investigates mobility and contention issues by proposing a protocol named TCP Sintok. This protocol comprises two mechanisms: Delay-based Loss Detection Mechanism (LDM), and Contention Avoidance Mechanism (CAM). LDM was introduced to determine the cause of the packet loss by monitoring the trend of end-to-end delay samples. CAM was developed to adapt the sending rate (congestion window) according to the current network condition. A series of experimental studies were conducted to validate the effectiveness of TCP Sintok in identifying the cause of packet loss and adapting the sending rate appropriately. Two variants of TCP protocol known as TCP NewReno and ADTCP were chosen to evaluate the performance of TCP Sintok through simulation. The results demonstrate that TCP Sintok improves jitter, delay and throughput as compared to the two variants. The findings have significant implication in providing reliable data transfer within MANET and supporting its deployment on mobile device communication

A Cross-Layer Modification to the DSR Routing Protocol in Wireless Mesh Networks

A cross-layer modification to the DSR routing protocol that finds high throughput paths in WMNs has been introduced in this work. The Access Efficiency Factor (AEF) has been introduced in this modification as a local congestion avoidance metric for the DSR routing mechanism as an alternative to the hop count (Hc) metric. In this modification, the selected path is identified by finding a path with the highest minimum AEF (max_min_AEF) value. The basis of this study is to compare the performance of the Hc and max_min_AEF as routing metrics for the DSR protocol in WMNs using the OPNET modeler. Performance comparisons between max_min_AEF, Metric Path (MP), and the well known ETT metrics are also carried out in this work. The results of this modification suggest that employing the max_min_AEF as a routing metric outperforms the Hc, ETT, and MP within the DSR protocol in WMNs in terms of throughput. This is because the max_min_AEF is based upon avoiding directing traffic through congested nodes where significant packet loss is likely to occur. This throughput improvement is associated with an increment in the delay time due to the long paths taken to avoid congested regions. To overcome this drawback, a further modification to the routing discovery mechanism has been made by imposing a hop count limit (HCL) on the discovered paths. Tuning the HCL allows the network manager to tradeoff throughput against delay. The choice of congestion avoidance metric exhibits another shortcoming owing to its dependency on the packet size. It penalises the smaller packets over large ones in terms of path lengths. This has been corrected for by introducing a ModAEF metric that explicitly considers the size of the packet. The ModAEF metric includes a tuning factor that allows the operator determine the level of the weighting that should be applied to the packet size to correct for this dependence

Network coding switch

Tese de mestrado, Engenharia Informática (Arquitetura, Sistemas e Redes de Computadores) Universidade de Lisboa, Faculdade de Ciências, 2019O tráfego na internet está a crescer a um ritmo elevado. A ocorrência de Gargalos é, então, cada vez mais, uma ocorrência comum, resultando em atrasos no transporte de informação e em ineficiências. Isto é um problema em parte decorrente do paradigma tradicional “store and foreward”. Quando um pacote chega a um nó da rede, é armazenado numa fila de espera enquanto aguarda por uma decisão de encaminhamento. Quando existe tráfego elevado, as filas de pacotes crescem e os atrasos aumentam (assim como as perdas de pacotes). O conceito de Codificação na Rede procura oferecer um paradigma. A ideia fundamental é a seguinte: à capacidade de armazenamento e encaminhamento. Quando existe tráfego elevado, as filas de pacotes crescem e os atrasos aumentam (assim como a perda dos pacotes).O Conceito de Codificação na Rede procura oferecer uma alternativa de paradigma. A ideia fundamental é a seguinte: à capacidade de armazenamento e encaminhamento é adicionada aos nós a capacidade de combinar pacotes. Com esta Técnica é possível aumentar as taxas de transferência de informação, assim como a resiliência da rede. Para se entender melhor o conceito vajamos um exemplo. Considere um nó A e um B que comunicam através de um ponto de acesso S, num ambiente sem fios. Vejamos as transmissões necessárias para A enviar a e B, e para B enviar mensagem b para A, usando o modelo tradicional:1A envia a para S 2B envia b para S 3S faz broadcast de a para os dois nós4S faz broadcast de b para os dois nós Como se pode observar, foram necessárias quatro transmissões ao todo. Ao aplicarmos codificação na rede podemos poupar no número de transmissões da seguinte forma:1A envia a para S2B envia b para S3S combina as duas mensagens aplicando um XOR sobre elas e envia o resultado, a b, para A e BNo entanto, o exemplo demonstrado acima é um caso base de Linear Network Coding (LNC). Esta técnica de codificação consiste em dar capacidade, a cada nó da rede, de gerar novos pacotes através de combinações lineares de pacotes recebidos anteriormente, multiplicando-os por coeficientes escolhidos de um dado campo finito, sendo o mais comum de tamanho 28. Já no exemplo anterior, em que foi utilizado uma técnica de codificação através do XOR para codificar dois pacotes, o tamanho do campo finito era de 2. Sendo este, então, um caso particular.Porém, o LNC requere que os coeficientes utilizados nas combinações lineares sejam definidos e computados à prori por todos os nós da rede através de um algoritmo e de informação partilhada. Estamos, então, perante uma Limitação desta técnica que introduz um custo. Random Linear Network Coding (RLNC), uma variante da técnica de LNC, permite ultrapassar essa limitação. Isto é possível devido à sua natureza aleatória, significando que os coeficientes empregues nas combinações lineares são gerados deforma aleatória dado um certo campo finito. Esta propriedade garante com uma dada probabilidade, desde que o campo finito tenha um tamanho suficiente largo, de que as combinações lineares geradas sejam independentes entre si, com o intuito de aumentar esta probabilidade, RLNC introduz ainda a capacidade de recodificar pacotes, isto é, codificar pacotes que já foram codificados por outro nó na rede. Assim, quando o nó destinatário recebe uma quantidade suficiente de pacotes codificados que sejam linearmente independentes é possível descodificar os pacotes resolvendo as combinações lineares. Para tal, o destinatário tem de ter conhecimento dos coeficientes empregues nas combinações lineares. Então, por norma, em RLNC os coeficientes empregues nas combinações lineares. Então por norma, em RLNC os coeficientes são anexados ao cabeçalho do pacote, após a codificação deste, para que os coeficientes sejam levados até ao destinatário. Tanto a operação de codificação como de descodificação introduzem uma certa complexidade computacional proporcional ao tamanho dos dados a serem transmitidos. A técnica designada por Generation-based RLNC, permite solucionar este problema. Esta consiste em dividir em grandes quantidades de dados em blocos mais pequenos, chamados gerações. Então, tanto a operação de codificação como a de descodificação são aplicadas por geração e não na totalidade de dados. Existe uma grande quantidade de trabalho teórico relacionado com Network Coding e implementações ao nível da Camada aplicacional. No entanto, não existe nenhum trabalho concreto cujo objetivo tenha sido desenvolver e implementar uma solução de Network Coding diretamente no plano de dados da rede. Isto resulta do facto de os switches serem hardware especializado com função única, não permitindo a codificação de pacotes.Recentemente, no entanto, foram desenvolvidos switches programáveis, que removem esta restrição. Ao contrário dos switches tradicionais que são dispositivos fechados que seguem um conjunto de protocolos definidos pelo fabricante, estes switches permitem ao operador definir exatamente o processamento dos pacotes. Entretanto foi desenvolvida também uma linguagem de alto nível para programar estes novos switches programáveis, designada como P4. Em Suma, uma das limitações de todas as soluções de codificação em rede existentes prende-se com o facto de serem implementações em software. Esta Limitação é resultado de inflexibilidade dos planos de dados em hardware (switches e routers) tradicionais, que não permitem a combinação de pacotes. Nesta dissertação começamos a atacar este problema através da exploração dos novos switches em hardware programáveis, desenhando e implementando um switch que executa Random Linear Network Coding usando a versão mais recente da linguagem de programação de switches P4 (especificamente, P4_16). A avaliação da nossa solução oferece boas perspetivas para a possibilidade de deployment em hardware destas técnicas de codificação em rede, mas apresente também alguns dos desafios que permanecem em aberto para explorar em trabalho futuro

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Opportunistic Routing with Network Coding in Powerline Communications

Opportunistic Routing (OR) can be used as an alternative to the legacy routing (LR) protocols in networks with a broadcast lossy channel and possibility of overhearing the signal. The power line medium creates such an environment. OR can better exploit the channel than LR because it allows the cooperation of all nodes that receive any data. With LR, only a chain of nodes is selected for communication. Other nodes drop the received information. We investigate OR for the one-source one-destination scenario with one traffic flow. First, we evaluate the upper bound on the achievable data rate and advocate the decentralized algorithm for its calculation. This knowledge is used in the design of Basic Routing Rules (BRR). They use the link quality metric that equals the upper bound on the achievable data rate between the given node and the destination. We call it the node priority. It considers the possibility of multi-path communication and the packet loss correlation. BRR allows achieving the optimal data rate pertaining certain theoretical assumptions. The Extended BRR (BRR-E) are free of them. The major difference between BRR and BRR-E lies in the usage of Network Coding (NC) for prognosis of the feedback. In this way, the protocol overhead can be severely reduced. We also study Automatic Repeat-reQuest (ARQ) mechanism that is applicable with OR. It differs to ARQ with LR in that each sender has several sinks and none of the sinks except destination require the full recovery of the original message. Using BRR-E, ARQ and other services like network initialization and link state control, we design the Advanced Network Coding based Opportunistic Routing protocol (ANChOR). With the analytic and simulation results we demonstrate the near optimum performance of ANChOR. For the triangular topology, the achievable data rate is just 2% away from the theoretical maximum and it is up to 90% higher than it is possible to achieve with LR. Using the G.hn standard, we also show the full protocol stack simulation results (including IP/UDP and realistic channel model). In this simulation we revealed that the gain of OR to LR can be even more increased by reducing the head-of-the-line problem in ARQ. Even considering the ANChOR overhead through additional headers and feedbacks, it outperforms the original G.hn setup in data rate up to 40% and in latency up to 60%.:1 Introduction 2 1.1 Intra-flow Network Coding 6 1.2 Random Linear Network Coding (RLNC) 7 2 Performance Limits of Routing Protocols in PowerLine Communications (PLC) 13 2.1 System model 14 2.2 Channel model 14 2.3 Upper bound on the achievable data rate 16 2.4 Achieving the upper bound data rate 17 2.5 Potential gain of Opportunistic Routing Protocol (ORP) over Common Single-path Routing Protocol (CSPR) 19 2.6 Evaluation of ORP potential 19 3 Opportunistic Routing: Realizations and Challenges 24 3.1 Vertex priority and cooperation group 26 3.2 Transmission policy in idealized network 34 3.2.1 Basic Routing Rules (BRR) 36 3.3 Transmission policy in real network 40 3.3.1 Purpose of Network Coding (NC) in ORP 41 3.3.2 Extended Basic Routing Rules (BRR) (BRR-E) 43 3.4 Automatic ReQuest reply (ARQ) 50 3.4.1 Retransmission request message contents 51 3.4.2 Retransmission Request (RR) origination and forwarding 66 3.4.3 Retransmission response 67 3.5 Congestion control 68 3.5.1 Congestion control in our work 70 3.6 Network initialization 74 3.7 Formation of the cooperation groups (coalitions) 76 3.8 Advanced Network Coding based Opportunistic Routing protocol (ANChOR) header 77 3.9 Communication of protocol information 77 3.10 ANChOR simulation . .79 3.10.1 ANChOR information in real time .80 3.10.2 Selection of the coding rate 87 3.10.3 Routing Protocol Information (RPI) broadcasting frequency 89 3.10.4 RR contents 91 3.10.5 Selection of RR forwarder 92 3.10.6 ANChOR stability 92 3.11 Summary 95 4 ANChOR in the Gigabit Home Network (G.hn) Protocol 97 4.1 Compatibility with the PLC protocol stack 99 4.2 Channel and noise model 101 4.2.1 In-home scenario 102 4.2.2 Access network scenario 102 4.3 Physical layer (PHY) layer implementation 102 4.3.1 Bit Allocation Algorithm (BAA) 103 4.4 Multiple Access Control layer (MAC) layer 109 4.5 Logical Link Control layer (LLC) layer 111 4.5.1 Reference Automatic Repeat reQuest (ARQ) 111 4.5.2 Hybrid Automatic Repeat reQuest (HARQ) in ANChOR 114 4.5.3 Modeling Protocol Data Unit (PDU) erasures on LLC 116 4.6 Summary 117 5 Study of G.hn with ANChOR 119 5.1 ARQ analysis 119 5.2 Medium and PHY requirements for “good” cooperation 125 5.3 Access network scenario 128 5.4 In-home scenario 135 5.4.1 Modeling packet erasures 136 5.4.2 Linear Dependence Ratio (LDR) 139 5.4.3 Worst case scenario 143 5.4.4 Analysis of in-home topologies 145 6 Conclusions . . . . . . . . . . . . . . . 154 A Proof of the neccessity of the exclusion rule 160 B Gain of ORPs to CSRPs 163 C Broadcasting rule 165 D Proof of optimality of BRR for triangular topology 167 E Reducing the retransmission probability 168 F Calculation of Expected Average number of transmissions (EAX) for topologies with bi-directional links 170 G Feedback overhead of full coding matrices 174 H Block diagram of G.hn physical layer in ns-3 model 175 I PER to BER mapping 17