36 research outputs found

    Improving Network Performance Through Endpoint Diagnosis And Multipath Communications

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    Components of networks, and by extension the internet can fail. It is, therefore, important to find the points of failure and resolve existing issues as quickly as possible. Resolution, however, takes time and its important to maintain high quality of service (QoS) for existing clients while it is in progress. In this work, our goal is to provide clients with means of avoiding failures if/when possible to maintain high QoS while enabling them to assist in the diagnosis process to speed up the time to recovery. Fixing failures relies on first detecting that there is one and then identifying where it occurred so as to be able to remedy it. We take a two-step approach in our solution. First, we identify the entity (Client, Server, Network) responsible for the failure. Next, if a failure is identified as network related additional algorithms are triggered to detect the device responsible. To achieve the first step, we revisit the question: how much can you infer about a failure using TCP statistics collected at one of the endpoints in a connection? Using an agent that captures TCP statistics at one of the end points we devise a classification algorithm that identifies the root cause of failures. Using insights derived from this classification algorithm we identify dominant TCP metrics that indicate where/why problems occur. If/when a failure is identified as a network related problem, the second step is triggered, where the algorithm uses additional information that is collected from ``failed\u27\u27 connections to identify the device which resulted in the failure. Failures are also disruptive to user\u27s performance. Resolution may take time. Therefore, it is important to be able to shield clients from their effects as much as possible. One option for avoiding problems resulting from failures is to rely on multiple paths (they are unlikely to go bad at the same time). The use of multiple paths involves both selecting paths (routing) and using them effectively. The second part of this thesis explores the efficacy of multipath communication in such situations. It is expected that multi-path communications have monetary implications for the ISP\u27s and content providers. Our solution, therefore, aims to minimize such costs to the content providers while significantly improving user performance

    Predicting expected TCP throughput using genetic algorithm

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    Predicting the expected throughput of TCP is important for several aspects such as e.g. determining handover criteria for future multihomed mobile nodes or determining the expected throughput of a given MPTCP subflow for load-balancing reasons. However, this is challenging due to time varying behavior of the underlying network characteristics. In this paper, we present a genetic-algorithm-based prediction model for estimating TCP throughput values. Our approach tries to find the best matching combination of mathematical functions that approximate a given time series that accounts for the TCP throughput samples using genetic algorithm. Based on collected historical datapoints about measured TCP throughput samples, our algorithm estimates expected throughput over time. We evaluate the quality of the prediction using different selection and diversity strategies for creating new chromosomes. Also, we explore the use of different fitness functions in order to evaluate the goodness of a chromosome. The goal is to show how different tuning on the genetic algorithm may have an impact on the prediction. Using extensive simulations over several TCP throughput traces, we find that the genetic algorithm successfully finds reasonable matching mathematical functions that allow to describe the TCP sampled throughput values with good fidelity. We also explore the effectiveness of predicting time series throughput samples for a given prediction horizon and estimate the prediction error and confidence.Peer ReviewedPostprint (author's final draft

    Analysis and simulation of feedback in network coded transmission

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    In questa tesi si propongono due protocolli di trasmissione multi-interfaccia, entrambi basati sul Network Coding, e studiamo un schema di feedback compatibile con questi e che permetta di sfruttare le proprietĂ  di questo schema di codifica. Inoltre questi protocolli vengono implementati in un simulatore in linguaggio Python, e i risultati vengono ricavati tramite un'estensiva campagna di simulazioni, specialmente riguardo a overhead e feedbacks

    A proxy for reliable 5G (and beyond) mmWave communications. Contributions to multi-path scheduling for a reliability focused mmWave proxy

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    Reliable, consistent and very high data rate mobile communication will become especially important for future services such as, among other things, future emergency communication needs. MmWave technology provides the needed capacity, however, lacks the reliability due to the abrupt capacity changes any one path experiences. Intelligently making use of varying numbers of available mmWave paths, efficiently scheduling data across the paths, perhaps even through multi-operator agreements; and balancing mobile power consumption with path costs and the need for reliable consistent quality will be critical to attaining this aim. In this thesis, the multipath scheduling problem in a mmWave proxy when the paths have dynamically changing path characteristics is considered. To address this problem, a hybrid scheduler is proposed, the performance of which is compared with the Round Robin scheduler, Random scheduler and the Highest Capacity First scheduler. Forward error correction is explored as a means of enhancing the scheduling. Keywords:Multipath Scheduling, mmWave Proxy, Forward Error Correction, beyond 5G

    Modelling users in networks with path choice: four studies in telecommunications and transit

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    Networks of interacting users arise in many important modelling applications. Commuters interact with each other and form traffic jams during peak-time. Network protocols are users in a communication network that control sending rate and server choice. When protocols send with too high rates, network links get overloaded resulting in lost data and high delays. Although these two example users seem very different, they are similar on a conceptual modelling level. Accurate user models are essential to study complex interactions in networks. The behaviour of a user with access to different paths in a network can be modelled as an optimisation problem. Users who choose paths with the highest utility are common in many different application areas, for example road traffic, Internet protocol modelling, and general societal networks, i.e. networks of humans in everyday life. Optimisation-based user models are also attractive from the perspective of a modeller since they often allow the derivation of insights about the behaviour of the entire system by only describing a user model. The aim of this thesis is to show, in four practical studies from telecommunications and transit networks, where optimisation-based models have limitations when modelling users with path choice. We study users who have access to a limited number of paths in large scale data centers and investigate how many paths per user are realistically needed in order to get high throughput in the network. In multimedia streaming, we study a protocol that streams data on multiple paths and path properties matter. We also investigate complex energy models for data interfaces on mobile phones and evaluate how to switch interfaces to save energy. Finally, we analyse a long-term data set from 20,000 transit commuters and give insights on how they change their travel behaviour in response to incentives and targeted offers. We use tools from optimisation, simulation, and statistics to evaluate the four studies and point out problems we faced when modelling and implementing the system. The findings of this thesis indicate where user models need to be extended in order to be of practical use. The results can serve as a guide towards better user models for future modelling applications

    5G Communications: Energy Efficiency

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    Cooperative data transfers for 5G networks

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    The demand for higher capacity, higher data rate and larger bandwidth has driven the research and industrial world to develop next generation wireless communication technology, namely, the 5G. Among all the approaches proposed for such a high demand, only the cooperative communication approach promises to significantly improve of the performances (capacity, data rate, bandwidth, etc.) with a low cost. In this thesis, we propose a D2D communication scheme as a solution for the out-door scenario and a cooperative scheme among the access infrastructures as the in-door scenario solution. In the first part, we address the implementation of content-centric routing in a D2D architecture for Android devices based on WiFi Direct, a protocol recently standardised by the Wi-Fi Alliance. After discussing the creation of multiple D2D groups, we introduce novel paradigms featuring intra- and inter-group bidirectional communication. We then present the primitives involved in content advertising and requesting among members of the multi-group network. In addition to the communications, we also devise a mechanism to enable the devices to spontaneously establish the multi-group D2D network. Finally, we evaluate the performance of our architecture and the network formation mechanism in a real testbed consisting of Android devices. In the second part, we propose, implement and evaluate a bandwidth aggregation service for residential users that allows to improve the upload throughput of the ADSL connection by leveraging the unused bandwidth of neighboring users. The residential access gateway adopts the 802.11 radio interface to simultaneously serve the local home users and to share the broadband connectivity with neighboring access gateways. Differently from previous works, our aggregation scheme is transparent both for local users, who are not required to modify their applications or device drivers, and for neighboring users, who do not experience any meaningful performance degradation. In order to evaluate the achievable performance and tune the parameters driving the traffic balancing, we developed a fluid model which was shown experimentally to be very accurate. Our proposed scheme is amenable to efficient implementation on Linux networking stack. Indeed, we implemented it and tested in some realistic scenarios, showing an efficient exploitation of the whole available bandwidth, also for legacy cloud storage applications

    Experimentation and Characterization of Mobile Broadband Networks

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    The Internet has brought substantial changes to our life as the main tool to access a large variety of services and applications. Internet distributed nature and technological improvements lead to new challenges for researchers, service providers, and network administrators. Internet traffic measurement and analysis is one of the most trivial and powerful tools to study such a complex environment from different aspects. Mobile BroadBand (MBB) networks have become one of the main means to access the Internet. MBB networks are evolving at a rapid pace with technology enhancements that promise drastic improvements in capacity, connectivity, and coverage, i.e., better performance in general. Open experimentation with operational MBB networks in the wild is currently a fundamental requirement of the research community in its endeavor to address the need for innovative solutions for mobile communications. There is a strong need for objective data relating to stability and performance of MBB (e.g., 2G, 3G, 4G, and soon-to-come 5G) networks and for tools that rigorously and scientifically assess their performance. Thus, measuring end user performance in such an environment is a challenge that calls for large-scale measurements and profound analysis of the collected data. The intertwining of technologies, protocols, and setups makes it even more complicated to design scientifically sound and robust measurement campaigns. In such a complex scenario, the randomness of the wireless access channel coupled with the often unknown operator configurations makes this scenario even more challenging. In this thesis, we introduce the MONROE measurement platform: an open access and flexible hardware-based platform for measurements on operational MBB networks. The MONROE platform enables accurate, realistic, and meaningful assessment of the performance and reliability of MBB networks. We detail the challenges we overcame while building and testing the MONROE testbed and argue our design and implementation choices accordingly. Measurements are designed to stress performance of MBB networks at different network layers by proposing scalable experiments and methodologies. We study: (i) Network layer performance, characterizing and possibly estimating the download speed offered by commercial MBB networks; (ii) End users’ Quality of Experience (QoE), specifically targeting the web performance of HTTP1.1/TLS and HTTP2 on various popular web sites; (iii) Implication of roaming in Europe, understanding the roaming ecosystem in Europe after the "Roam like Home" initiative; and (iv) A novel adaptive scheduler family with deadline is proposed for multihomed devices that only require a very coarse knowledge of the wireless bandwidth. Our results comprise different contributions in the scope of each research topic. To put it in a nutshell, we pinpoint the impact of different network configurations that further complicate the picture and hopefully contribute to the debate about performance assessment in MBB networks. The MBB users web performance shows that HTTP1.1/TLS is very similar to HTTP2 in our large-scale measurements. Furthermore, we observe that roaming is well supported for the monitored operators and the operators using the same approach for routing roaming traffic. The proposed adaptive schedulers for content upload in multihomed devices are evaluated in both numerical simulations and real mobile nodes. Simulation results show that the adaptive solutions can effectively leverage the fundamental tradeoff between the upload cost and completion time, despite unpredictable variations in available bandwidth of wireless interfaces. Experiments in the real mobile nodes provided by the MONROE platform confirm the findings
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