The Master´s thesis deals with the field of converged networks and their effective utilization, focusing specifically on telematic networks. For modelling of a specific application, the field of vehicle telematics has been chosen. The thesis consists of two series of simulations performed in Opnet Modeler network simulator. The first theoretic part gave an overview of protocols used in converged networks, with a more detailed description of routing protocols. The attention also centred on the mechanisms for assuring the quality of service in IP. The subsequent practical part consisted in creating the simulation of a converged telematic network in Opnet Modeler network simulator, configuration of scenarios for assuring QoS using RSVP and DSCP protocols and the simulation itself. The results of the simulations for both scenarios were compared and represented in graphic form. The second theoretic part described queueing disciplines, as well as congestion control and congestion avoidance mechanisms. The corresponding practical part compared FIFO, PQ and WFQ queueing algorithms within the same simulated converged telematic network, using DSCP protocol scenario, which gave much better results in the first series of simulations. Again, the results of the simulations were compared and represented in graphic form.

In order to easily send data between two end elements without congestion, methods that suitably control flow of date and evaluate possible overload state are necessary. One such method is to control the data flow directly on the transport layer. This layer offers a range of mechanisms dedicated to deal with this issue. The aim of this paper is divided into three parts. The first part describes the integration of transport layer TCP/IP model, and the ability to process TCP data stream. The second part describes methods to manage congestion, their integration by usage environment. It mainly focuses on methods of TCP Reno and TCP Vegas. Their simulation and analysis on transmission the data stream stream. The third part deals with the analysis in detail of TCP Vegas. Analyzes possible parameters for alpha a beta within the TCP Vegas, and a combination of TCP Vegas and TCP Reno.

<p>  Modern datacenter network applications continue to demand ultra low latencies and very high throughputs. At the same time, network infrastructure keeps achieving higher speeds and larger bandwidths. We still need better network management solutions to keep these two demand and supply fronts go hand-in-hand. There are key metrics that define network performance such as flow completion time (the lower the better), throughput (the higher the better), and end-to-end latency (the lower the better) that are mainly governed by how effectively network application get their fair share of network resources. We observe that buffer utilization on network switches gives a very accurate indication of network performance. Therefore, network buffer management is important in modern datacenter networks, and other network management solutions can be efficiently built around buffer utilization. This dissertation presents three solutions based on buffer use on network switches.</p> <p>  This dissertation consists of three main sections. The first section is on a specification language for buffer management in modern programmable switches. The second section is on a congestion control solution for Remote Direct Memory Access (RDMA) networks. The third section is on a solution to head-of-the-line blocking in modern datacenter networks.</p>

Platooning has the potential to be a breakthrough in increasing road capacity and reducing fuel consumption, as it allows a chain of vehicles to closely follow each other on the road. When the number of vehicles increases, platoons will follow one another in what is referred to as multiplatooning. Many Cooperative Intelligent Transportation Systems (C-ITS) applications rely on periodically exchanged beacons among vehicles to improve traffic safety. However, as the number of connected vehicles increases, the network may become congested due to periodically exchanged beacons. Therefore, without some congestion control method, safety critical messages such as Cooperative Awareness Messages (CAMs) may not be delivered on time in high vehicle density scenarios. Both the European Telecommunications Standards Institute (ETSI) and the Institute of Electrical and Electronics Engineers (IEEE) have been working on different standards to support vehicular communication. ETSI dened the Decentralized Congestion Control (DCC) mechanism which adapts transmission parameters (message rate, transmit data rate, and transmit power, etc.) to keep channel load under control. ETSI DCC utilizes a three-state machine with RELAXED, ACTIVE, and RESTRICTIVE states. In this thesis, we implemented this three-state machine by adapting the message rate based on the channel busy ratio (CBR). We name this message-rate based three-state machine DCC-3. DCC-3 has the ability to control channel load; however, it has unfairness and instability problems due to the dramatic parameter changes between states. Therefore, we divided the ACTIVE state of DCC-3 into ve sub-states, and refer to this as DCC-7. We benchmarked DCC-3 against static beaconing (STB), dynamic beaconing (DynB), LInear MEssage Rate Integrated Control (LIMERIC), and DCC-7 using different evaluation metrics with different numbers of platoons. Our results from the Plexe simulator demonstrate that DCC-7 has the best performance when considering all evaluation metrics, including CBR, Inter-reception time (IRT), collisions, safe time ratio, and fairness. Furthermore, we found using transmit power control could greatly improve the performance of CBR and collision rates. / Platooning (fordonskonvojer) har potential att bli ett genombrott i öka vägkapaciteten och minska bränsleförbrukning, eftersom det tillåter en kedja av fordon att noga följa varandra på vägen. När antalet fordon ökar, kommer att plutoner följa varandra i vad som benämns multiplatooning (konvoj av fordonskonvojer). Många kooperativ intelligenta transportsystem (C-ITS) tillämpningar förlitar sig på regelbundet utbytte beacons bland fordon att förbättra traffiksäkerheten. Dock som antalet uppkopplade fordon ökar, kan nätverket bli överbelastat på grund av regelbundet utbytte beacons. Utan någon trängsel kontrollmetod, får därför säkerhet kritiska meddelanden såsom kooperativ medvetenhet meddelanden (CAMs) inte levereras i tid i höga fordon densitet scenarier. Både Europeiska institutet för telekommunikationsstandarder (ETSI) och Institute el och elektroniska tekniker (IEEE) har arbetat på olika standarder för att stödja vehicular kommunikation. ETSI definieras den decentraliserade överbelastning kontroll (DCC) mekanism som anpassar överföring parametrar (meddelande hastighet, överföra datahastighet och sändningseffekt, etc.) för att hålla kanalen belastningen under kontroll. ETSI DCC använder en tre-state maskin med RELAXED, ACTIVE och RESTRICTIVE stater. I denna avhandling har genomfört vi denna tre-state maskin genom att anpassa meddelande hastighet baserat på kanal upptagen förhållandet (CBR). Vi nämna detta meddelande-hastighet baserat tre-state machine DCC-3. DCC-3 har förmågan att kontrollera kanal belastning; Det har dock otillbörlighet och instabilitet problem på grund av de dramatiska parameterändringar mellan stater. Därför vi indelat det ACTIVE tillståndet för DCC-3 i fem undertillstånd och hänvisar till detta som DCC-7. Vi benchmarkade DCC-3 mot statiska leda (STB), dynamisk leda (DynB), linjära MEssage Rate integrerad kontroll (LIMERIC) och DCC-7 med olika utvärdering statistik med olika antal plutoner. Våra resultat från Plexe simulator visar att DCC-7 har bästa prestanda när man överväger alla utvärdering statistik, inklusive CBR, mellan receptionen tid (IRT), kollisioner, säker tid baserat och rättvisa. Vi fann dessutom använda Sändareffektstyrning kan avsevärt förbättra prestanda för CBR och kollision priser.

Since the field of computer networks has rapidly grown in the last two decades, congestion control of traffic loads within networks has become a high priority. Congestion occurs in network routers when the number of incoming packets exceeds the available network resources, such as buffer space and bandwidth allocation. This may result in a poor network performance with reference to average packet queueing delay, packet loss rate and throughput. To enhance the performance when the network becomes congested, several different active queue management (AQM) methods have been proposed and some of these are discussed in this thesis. Specifically, these AQM methods are surveyed in detail and their strengths and limitations are highlighted. A comparison is conducted between five known AQM methods, Random Early Detection (RED), Gentle Random Early Detection (GRED), Adaptive Random Early Detection (ARED), Dynamic Random Early Drop (DRED) and BLUE, based on several performance measures, including mean queue length, throughput, average queueing delay, overflow packet loss probability, packet dropping probability and the total of overflow loss and dropping probabilities for packets, with the aim of identifying which AQM method gives the most satisfactory results of the performance measures. This thesis presents a new AQM approach based on the RED algorithm that determines and controls the congested router buffers in an early stage. This approach is called Dynamic RED (REDD), which stabilises the average queue length between minimum and maximum threshold positions at a certain level called the target level to prevent building up the queues in the router buffers. A comparison is made between the proposed REDD, RED and ARED approaches regarding the above performance measures. Moreover, three methods based on RED and fuzzy logic are proposed to control the congested router buffers incipiently. These methods are named REDD1, REDD2, and REDD3 and their performances are also compared with RED using the above performance measures to identify which method achieves the most satisfactory results. Furthermore, a set of discrete-time queue analytical models are developed based on the following approaches: RED, GRED, DRED and BLUE, to detect the congestion at router buffers in an early stage. The proposed analytical models use the instantaneous queue length as a congestion measure to capture short term changes in the input and prevent packet loss due to overflow. The proposed analytical models are experimentally compared with their corresponding AQM simulations with reference to the above performance measures to identify which approach gives the most satisfactory results. The simulations for RED, GRED, ARED, DRED, BLUE, REDD, REDD1, REDD2 and REDD3 are run ten times, each time with a change of seed and the results of each run are used to obtain mean values, variance, standard deviation and 95% confidence intervals. The performance measures are calculated based on data collected only after the system has reached a steady state. After extensive experimentation, the results show that the proposed REDD, REDD1, REDD2 and REDD3 algorithms and some of the proposed analytical models such as DRED-Alpha, RED and GRED models offer somewhat better results of mean queue length and average queueing delay than these achieved by RED and its variants when the values of packet arrival probability are greater than the value of packet departure probability, i.e. in a congestion situation. This suggests that when traffic is largely of a non bursty nature, instantaneous queue length might be a better congestion measure to use rather than the average queue length as in the more traditional models.

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that have / Ministry of Higher Education in Egypt and the Egyptian Cultural Centre and Educational Bureau in London

BBR is a congestion control recently proposed by Google, unlike the traditional congestion control which uses packet loss as the signal of congestion, BBR uses the estimation of bottleneck bandwidth to control the sending rate. However, recent work shows that BBR suffers from a variety of problems such as large queuing delays with multiple flows in the network. Most of the existing work in this area has so far focused on the performance analysis of BBR. Despite these efforts, there exists still a lack of understanding on how to improve the performance of BBR in different scenarios. In this paper, we first present the behaviour of the original BBR in the Network Simulator 3 (ns-3), then, we provide an improvement that carefully adjusts the pacing rate based on the RTT of the flow, finally, to validate our method, we run simulations varying different bottlenecks, latency, and numbers of flows in both small and large buffer size scenarios on ns-3 network simulator. The results show that our improvement can significantly reduce the queuing delay on the bottleneck at a very small cost of throughput in large buffer scenarios, and also achieve less than 0.1% retransmission rate in small buffer scenarios. / BBR är en typ av stockningskontroll som nyligen föreslagits av Google. Till skillnad från traditionell stockningskontroll som använder paketförlust som stockningssignal använder BBR en uppskattning av bandbredden i flaskhalsen mellan sändare och mottagare för att styra sändningshastigheten. Senare arbete visar dock att BBR lider av olika problem, såsom långa förseningar i paketköer med flera flöden i nätverket. Det mesta av det befintliga arbetet inom detta område har hittills fokuserat på att analysera BBR-prestanda. Trots dessa ansträngningar saknas det fortfarande förståelse för hur man kan förbättra BBR:s prestanda i olika scenarier. I den här rapporten presenterar vi först beteendet hos den ursprungliga BBR i nätverkssimulatorn ns-3. Därefter föreslår vi en förbättring som noggrant justerar sändningstakten enligt RTT (Round Trip Time) för flödet. Slutligen, för att validera vår metod, utför vi simuleringar som varierar olika flaskhalsar, fördröjningar och antal paketströmmar i små och stora buffertstorlekar i ns-3. Resultaten visar att vår förbättring avsevärt kan minska köfördröjningar i flaskhalsar för stora buffertstorlekar till en mycket låg kostnad i genomströmning, samt uppnå mindre än 0.1% omsändningshastighet i scenarier med små buffertstorlekar.

No / Traffic congestion in communication networks can dramatically deteriorate user-perceived Quality-of-Service (QoS). The integration of the Random Early Detection (RED) and priority scheduling mechanisms is a promising scheme for congestion control and provisioning of differentiated QoS required by multimedia applications. Although analytical modelling of RED congestion control has received significant research efforts, the performance models reported in the current literature were primarily restricted to the RED algorithm only without consideration of traffic scheduling scheme for QoS differentiation. Moreover, for analytical tractability, these models were developed under the simplified assumption that the traffic follows Short-Range-Dependent (SRD) arrival processes (e.g., Poisson or Markov processes), which are unable to capture the self-similar nature (i.e., scale-invariant burstiness) of multimedia traffic in modern communication networks. To fill these gaps, this paper presents a new analytical model of RED congestion control for prioritized multi-class self-similar traffic. The closed-form expressions for the loss probability of individual traffic classes are derived. The effectiveness and accuracy of the model are validated through extensive comparison between analytical and simulation results. To illustrate its application, the model is adopted as a cost-effective tool to investigate the optimal threshold configuration and minimize the required buffer space with congestion control.

No / People, systems, and things in the cities generate large amount of data which is considered to be the most scalable asset of any smart city. Linux users are rapidly increased in last few years, and many large multinational organizations are deploying long distance high bandwidth (LDHB) cloud networks for centralizing the data from various smart cities on a central location. TCP is responsible for reliable communication of data in these cloud networks. For reliability communication among various smart cities, a number of TCP congestion control mechanisms have been developed in the past. TCP Compound, TCP Fusion, and TCP CUBIC are the default TCP congestion control mechanisms for Microsoft Windows, Sun Solaris, and Linux operating systems respectively. The response function of TCP CUBIC is higher than the response function of Standard TCP, which is a trademark congestion control mechanism. As a result, TCP CUBIC does not behave friendly with Standard TCP in LDHB cloud networks. The Congestion Window (cwnd) reduction and growth of TCP CUBIC is very aggressive, which causes high packet loss rate and unfair share of available link bandwidth among competing flows from various smart cities. The aim of this research is to design a new TCP congestion control mechanism for Linux operating system to achieve maximum performance in LDHB cloud networks being used by smart cities. In this paper, congestion control module for slow start (CCM-SS) is designed by increasing the lower boundary limit of cwnd size in slow start phase of communication. Congestion control module for loss event (CCM-LE) is designed by increasing the cwnd reduction rate at each packet loss event and finally Advance Response Function for TCP CUBIC (ARFC) is proposed to design a new congestion control mechanism for Linux operating system. NS-2 is used to compare the performance of TCP CUBIC* with TCP CUBIC in short distance high bandwidth (SDHB) and long distance high bandwidth (LDHB) cloud networks. Results show that TCP CUBIC* has outperformed in LDHB networks, at least by a factor of 18% as compared to TCP CUBIC.

Along with playing an ever-increasing role in the integration of other communication networks and expanding in application diversities, the current Internet suffers from serious overuse and congestion bottlenecks. Efficient congestion control is fundamental to ensure the Internet reliability, satisfy the specified Quality-of-Service (QoS) constraints and achieve desirable performance in response to varying application scenarios. Active Queue Management (AQM) is a promising scheme to support end-to-end Transmission Control Protocol (TCP) congestion control because it enables the sender to react appropriately to the real network situation. Analytical performance models are powerful tools which can be adopted to investigate optimal setting of AQM parameters. Among the existing research efforts in this field, however, there is a current lack of analytical models that can be viewed as a cost-effective performance evaluation tool for AQM in the presence of heterogeneous traffic, generated by various network applications. This thesis aims to provide a generic and extensible analytical framework for analyzing AQM congestion control for various traffic types, such as non-bursty Poisson and bursty Markov-Modulated Poisson Process (MMPP) traffic. Specifically, the Markov analytical models are developed for AQM congestion control scheme coupled with queue thresholds and then are adopted to derive expressions for important QoS metrics. The main contributions of this thesis are listed as follows: • Study the queueing systems for modeling AQM scheme subject to single-class and multiple-classes Poisson traffic, respectively. Analyze the effects of the varying threshold, mean traffic arrival rate, service rate and buffer capacity on the key performance metrics. • Propose an analytical model for AQM scheme with single class bursty traffic and investigate how burstiness and correlations affect the performance metrics. The analytical results reveal that high burstiness and correlation can result in significant degradation of AQM performance, such as increased queueing delay and packet loss probability, and reduced throughput and utlization. • Develop an analytical model for a single server queueing system with AQM in the presence of heterogeneous traffic and evaluate the aggregate and marginal performance subject to different threshold values, burstiness degree and correlation. • Conduct stochastic analysis of a single-server system with single-queue and multiple-queues, respectively, for AQM scheme in the presence of multiple priority traffic classes scheduled by the Priority Resume (PR) policy. • Carry out the performance comparison of AQM with PR and First-In First-Out (FIFO) scheme and compare the performance of AQM with single PR priority queue and multiple priority queues, respectively.