Per-hop Internet Measurement Protocols

Accurately measuring per-hop packet dynamics on an Internet path is difficult. Currently available techniques have many well-known limitations that can make it difficult to accurately measure per-hop packet dynamics. Much of the difficulty of per-hop measurement is due to the lack of protocol support available to measure an Internet path on a per-hop basis. This thesis classifies common weaknesses and describes a protocol for per-hop measurement of Internet packet dynamics, known as the IP Measurement Protocol, or IPMP. With IPMP, a specially formed probe packet collects information from intermediate routers on the packet's dynamics as the packet is forwarded. This information includes an IP address from the interface that received the packet, a timestamp that records when the packet was received, and a counter that records the arrival order of echo packets belonging to the same flow. Probing a path with IPMP allows the topology of the path to be directly determined, and for direct measurement of per-hop behaviours such as queueing delay, jitter, reordering, and loss. This is useful in many operational situations, as well as for researchers in characterising Internet behaviour. IPMP's design goals of being tightly constrained and easy to implement are tested by building implementations in hardware and software. Implementations of IPMP presented in this thesis show that an IPMP measurement probe can be processed in hardware without delaying the packet, and processed in software with little overhead. This thesis presents IPMP-based measurement techniques for measuring per-hop packet delay, jitter, loss, reordering, and capacity that are more robust, require less probes to be sent, and are potentially more accurate and convenient than corresponding measurement techniques that do not use IPMP

PoissonProb: A new rate-based available bandwidth measurement algorithm.

Accurate available bandwidth measurement is important for network protocols and distributed programs design, traffic optimization, capacity planning, and service verification. Research on measuring available bandwidth falls into two basic classes: the network traffic modeling algorithms and the self-induced algorithms. The self-induced algorithms are based on packet dispersion techniques. The currently available bandwidth measurement algorithms face the problems of distortion of measurement on multi-hop paths, system resource limitations, probe traffic intrusiveness and measurement accuracy. We have developed a new rate-based self-induced algorithm---PoissonProb. The intervals between probe packets of this algorithm are in Poisson distribution format and the algorithm infers the available bandwidth according to the average of probe packets rate. The algorithm has been implemented as the PoissonProb Available Bandwidth (PAB) measurement tool. The PAB tool can be operated in either sender-based or receiver-based mode. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .X56. Source: Masters Abstracts International, Volume: 44-03, page: 1418. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Cross-layer signalling and middleware: a survey for inelastic soft real-time applications in MANETs

This paper provides a review of the different cross-layer design and protocol tuning approaches that may be used to meet a growing need to support inelastic soft real-time streams in MANETs. These streams are characterised by critical timing and throughput requirements and low packet loss tolerance levels. Many cross-layer approaches exist either for provision of QoS to soft real-time streams in static wireless networks or to improve the performance of real and non-real-time transmissions in MANETs. The common ground and lessons learned from these approaches, with a view to the potential provision of much needed support to real-time applications in MANETs, is therefore discussed

Network traffic management for the next generation Internet

Measurement-based performance evaluation of network traffic is a fundamental prerequisite for the provisioning of managed and controlled services in short timescales, as well as for enabling the accountability of network resources. The steady introduction and deployment of the Internet Protocol Next Generation (IPNG-IPv6) promises a network address space that can accommodate any device capable of generating a digital heart-beat. Under such a ubiquitous communication environment, Internet traffic measurement becomes of particular importance, especially for the assured provisioning of differentiated levels of service quality to the different application flows. The non-identical response of flows to the different types of network-imposed performance degradation and the foreseeable expansion of networked devices raise the need for ubiquitous measurement mechanisms that can be equally applicable to different applications and transports. This thesis introduces a new measurement technique that exploits native features of IPv6 to become an integral part of the Internet's operation, and to provide intrinsic support for performance measurements at the universally-present network layer. IPv6 Extension Headers have been used to carry both the triggers that invoke the measurement activity and the instantaneous measurement indicators in-line with the payload data itself, providing a high level of confidence that the behaviour of the real user traffic flows is observed. The in-line measurements mechanism has been critically compared and contrasted to existing measurement techniques, and its design and a software-based prototype implementation have been documented. The developed system has been used to provisionally evaluate numerous performance properties of a diverse set of application flows, over different-capacity IPv6 experimental configurations. Through experimentation and theoretical argumentation, it has been shown that IPv6-based, in-line measurements can form the basis for accurate and low-overhead performance assessment of network traffic flows in short time-scales, by being dynamically deployed where and when required in a multi-service Internet environment.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Network and service monitoring in heterogeneous home networks

Home networks are becoming dynamic and technologically heterogeneous. They consist of an increasing number of devices which offer several functionalities and can be used for many different services. In the home, these devices are interconnected using a mixture of networking technologies (for example, Ethernet, Wifi, coaxial cable, or power-line). However, interconnecting these devices is often not easy. The increasing heterogeneity has led to significant device- and service-management complexity. In addition, home networks provide a critical "last meters" access to the public telecom and Internet infrastructure and have a dramatic impact on to the end-to-end reliability and performance of services from these networks. This challenges service providers not only to maintain a satisfactory quality of service level in such heterogeneous home networks, but also to remotely monitor and troubleshoot them. The present thesis work contributes research and several solutions in the field of network and service monitoring in home networks, mainly in three areas: (1) providing automatic device- and service-discovery and configuration, (2) remote management, and (3) providing quality of service (QoS). With regard to the first area, current service discovery technology is designed to relieve the increasing human role in network and service administration. However, the relevant Service Discovery Protocols (SDPs) are lacking crucial features namely: (1) they are not platform- and network-independent, and (2) they do not provide sufficient mechanisms for (device) resource reservation. Consequently, devices implementing different SDPs cannot communicate with each other and share their functionalities and resources in a managed way, especially when they use different network technologies. As a solution to the first problem, we propose a new proxy server architecture that enables IP-based devices and services to be discovered on non-IP based network and vice versa. We implemented the proxy architecture using UPnP respectively Bluetooth SDP as IP- and non-IP-based SDPs. The proxy allows Bluetooth devices and UPnP control points to discover, access, and utilize services located on the other network. Validation experiments with the proxy prototype showed that seamless inter-working can be achieved keeping all proxy functionalities on a single device, thus not requiring modification of currently existing UPnP and Bluetooth end devices. Although the proxy itself taxes the end-to-end performance of the service, it is shown to be still acceptable for an end user. For mitigating resource conflicts in SDPs, we propose a generic resource reservation scheme with properties derived from common SDP operation. Performance studies with a prototype showed that this reservation scheme significantly improves the scalability and sustainability of service access in SDPs, at a minor computational cost. With regard to the second area, it is known that the end-to-end quality of Internet services depends crucially on the performance of the home network. Consequently, service providers require the ability to monitor and configure devices in the home network, behind the home gateway (HG). However, they can only put limited requirements to these off-the-shelf devices, as the consumer electronics market is largely outside their span of control. Therefore they have to make intelligent use of the given device control and management protocols. In this work, we propose an architecture for remote discovery and management of devices in a highly heterogeneous home network. A proof-of-concept is developed for the remote management of UPnP devices in the home with a TR-069/UPnP proxy on the HG. Although this architecture is protocol specific, it can be easily adapted to other web-services based protocols. Service providers are also asking for diagnostic tools with which they can remotely troubleshoot the home networks. One of these tools should be able to gather information about the topology of the home network. Although topology discovery protocols already exist, nothing is known yet about their performance. In this work we propose a set of key performance indicators for home network topology discovery architectures, and how they should be measured. We applied them to the Link-Layer Topology Discovery (LLTD) protocol and the Link-Layer Discovery Protocol (LLDP). Our performance measurement results show that these protocols do not fulfill all the requirements as formulated by the service providers. With regard to the third area, current QoS solutions are mostly based on traffic classification. Because they need to be supported by all devices in the network, they are relatively expensive for home networks. Furthermore, they are not interoperable between different networking technologies. Alternative QoS provision techniques have been proposed in the literature. These techniques require end-user services to pragmatically adapt their properties to the actual condition of the network. For this, the condition of the home network in terms of its available bandwidth, delay, jitter, etc., needs to be known in real time. Appropriate tools for determining the available home network resources do not yet exist. In this work we propose a new method to probe the path capacity and available bandwidth between a server and a client in a home network. The main features of this method are: (a) it does not require adaptation of existing end devices, (b) it does not require pre-knowledge of the link-layer network topology, and (c) it is accurate enough to make reliable QoS predictions for the most relevant home applications. To use these predictions for effective service- or content-adaptation or admission control, one should also know how the state of the home network is expected to change immediately after the current state has been probed. However, not much is known about the stochastic properties of traffic in home networks. Based on a relatively small set of traffic observations in several home networks in the Netherlands, we were able to build a preliminary model for home network traffic dynamics

Available Bandwidth Estimation Tools Metrics, Approaches and Performance

The estimation of the available bandwidth (av bw) between two end nodes through the Internet, is an area that has motivated researchers around the world in the last twenty years, to have faster and more accurate tools; Due to the utility it has in various network applications; Such as routing management, intrusion detection systems and the performance of transport protocols. Different tools use different estimation techniques but generally only analyze the three most used metrics as av bw, relative error and estimation time. This work expands the information regarding the evaluation literature of the current Available Bandwidth Estimation Tools (ABET’s), where they analyze the estimation techniques, metrics, different generation tools of cross-traf?c and evaluation testbed; Concentrating on the techniques and estimation methodologies used, as well as the challenges faced by open-source tools in high-performance networks of 10Gbps or higher

Available Bandwidth Estimation Tools Metrics, Approaches and Performance

The estimation of the available bandwidth (av_bw) between two end nodes through the Internet, is an area that has motivated researchers around the world in the last twenty years, to have faster and more accurate tools; Due to the utility it has in various network applications; Such as routing management, intrusion detection systems and the performance of transport protocols. Different tools use different estimation techniques but generally only analyze the three most used metrics as av_bw, relative error and estimation time. This work expands the information regarding the evaluation literature of the current Available Bandwidth Estimation Tools (ABET's), where they analyze the estimation techniques, metrics, different generation tools of cross-traffic and evaluation testbed; Concentrating on the techniques and estimation methodologies used, as well as the challenges faced by open-source tools in high-performance networks of 10 Gbps or higher

Understanding the performance of Internet video over residential networks

Video streaming applications are now commonplace among home Internet users, who typically access the Internet using DSL or Cable technologies. However, the effect of these technologies on video performance, in terms of degradations in video quality, is not well understood. To enable continued deployment of applications with improved quality of experience for home users, it is essential to understand the nature of network impairments and develop means to overcome them. In this dissertation, I demonstrate the type of network conditions experienced by Internet video traffic, by presenting a new dataset of the packet level performance of real-time streaming to residential Internet users. Then, I use these packet level traces to evaluate the performance of commonly used models for packet loss simulation, and finding the models to be insufficient, present a new type of model that more accurately captures the loss behaviour. Finally, to demonstrate how a better understanding of the network can improve video quality in a real application scenario, I evaluate the performance of forward error correction schemes for Internet video using the measurements. I show that performance can be poor, devise a new metric to predict performance of error recovery from the characteristics of the input, and validate that the new packet loss model allows more realistic simulations. For the effective deployment of Internet video systems to users of residential access networks, a firm understanding of these networks is required. This dissertation provides insights into the packet level characteristics that can be expected from such networks, and techniques to realistically simulate their behaviour, promoting development of future video applications

Optimizing the delivery of multimedia over mobile networks

Mención Internacional en el título de doctorThe consumption of multimedia content is moving from a residential environment to mobile phones. Mobile data traffic, driven mostly by video demand, is increasing rapidly and wireless spectrum is becoming a more and more scarce resource. This makes it highly important to operate mobile networks efficiently. To tackle this, recent developments in anticipatory networking schemes make it possible to to predict the future capacity of mobile devices and optimize the allocation of the limited wireless resources. Further, optimizing Quality of Experience—smooth, quick, and high quality playback—is more difficult in the mobile setting, due to the highly dynamic nature of wireless links. A key requirement for achieving, both anticipatory networking schemes and QoE optimization, is estimating the available bandwidth of mobile devices. Ideally, this should be done quickly and with low overhead. In summary, we propose a series of improvements to the delivery of multimedia over mobile networks. We do so, be identifying inefficiencies in the interconnection of mobile operators with the servers hosting content, propose an algorithm to opportunistically create frequent capacity estimations suitable for use in resource optimization solutions and finally propose another algorithm able to estimate the bandwidth class of a device based on minimal traffic in order to identify the ideal streaming quality its connection may support before commencing playback. The main body of this thesis proposes two lightweight algorithms designed to provide bandwidth estimations under the high constraints of the mobile environment, such as and most notably the usually very limited traffic quota. To do so, we begin with providing a thorough overview of the communication path between a content server and a mobile device. We continue with analysing how accurate smartphone measurements can be and also go in depth identifying the various artifacts adding noise to the fidelity of on device measurements. Then, we first propose a novel lightweight measurement technique that can be used as a basis for advanced resource optimization algorithms to be run on mobile phones. Our main idea leverages an original packet dispersion based technique to estimate per user capacity. This allows passive measurements by just sampling the existing mobile traffic. Our technique is able to efficiently filter outliers introduced by mobile network schedulers and phone hardware. In order to asses and verify our measurement technique, we apply it to a diverse dataset generated by both extensive simulations and a week-long measurement campaign spanning two cities in two countries, different radio technologies, and covering all times of the day. The results demonstrate that our technique is effective even if it is provided only with a small fraction of the exchanged packets of a flow. The only requirement for the input data is that it should consist of a few consecutive packets that are gathered periodically. This makes the measurement algorithm a good candidate for inclusion in OS libraries to allow for advanced resource optimization and application-level traffic scheduling, based on current and predicted future user capacity. We proceed with another algorithm that takes advantage of the traffic generated by short-lived TCP connections, which form the majority of the mobile connections, to passively estimate the currently available bandwidth class. Our algorithm is able to extract useful information even if the TCP connection never exits the slow start phase. To the best of our knowledge, no other solution can operate with such constrained input. Our estimation method is able to achieve good precision despite artifacts introduced by the slow start behavior of TCP, mobile scheduler and phone hardware. We evaluate our solution against traces collected in 4 European countries. Furthermore, the small footprint of our algorithm allows its deployment on resource limited devices. Finally, in an attempt to face the rapid traffic increase, mobile application developers outsource their cloud infrastructure deployment and content delivery to cloud computing services and content delivery networks. Studying how these services, which we collectively denote Cloud Service Providers (CSPs), perform over Mobile Network Operators (MNOs) is crucial to understanding some of the performance limitations of today’s mobile apps. To that end, we perform the first empirical study of the complex dynamics between applications, MNOs and CSPs. First, we use real mobile app traffic traces that we gathered through a global crowdsourcing campaign to identify the most prevalent CSPs supporting today’s mobile Internet. Then, we investigate how well these services interconnect with major European MNOs at a topological level, and measure their performance over European MNO networks through a month-long measurement campaign on the MONROE mobile broadband testbed. We discover that the top 6 most prevalent CSPs are used by 85% of apps, and observe significant differences in their performance across different MNOs due to the nature of their services, peering relationships with MNOs, and deployment strategies. We also find that CSP performance in MNOs is affected by inflated path length, roaming, and presence of middleboxes, but not influenced by the choice of DNS resolver. We also observe that the choice of operator’s Point of Presence (PoP) may inflate by at least 20% the delay towards popular websites.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Ahmed Elmokashfi.- Secretario: Rubén Cuevas Rumín.- Vocal: Paolo Din

Cloud and mobile infrastructure monitoring for latency and bandwidth sensitive applications

This PhD thesis involves the study of cloud computing infrastructures (from the networking perspective) to assess the feasibility of applications gaining increasing popularity over recent years, including multimedia and telemedicine applications, demanding low, bounded latency and sufficient bandwidth. I also focus on the case of telemedicine, where remote imaging applications (for example, telepathology or telesurgery) need to achieve a low and stable latency for the remote transmission of images, and also for the remote control of such equipment. Another important use case for telemedicine is denoted as remote computation, which involves the offloading of image processing to help diagnosis; also in this case, bandwidth and latency requirements should be enforced to ensure timely results, although they are less strict compared to the previous scenario. Nowadays, the capability of gaining access to IT resources in a rapid and on-demand fashion, according to a pay-as-you-go model, has made the cloud computing a key-enabler for innovative multimedia and telemedicine services. However, the partial obscurity of cloud performance, and also security concerns are still hindering the adoption of cloud infrastructure. To ensure that the requirements of applications running on the cloud are satisfied, there is the need to design and evaluate proper methodologies, according to the metric of interest. Moreover, some kinds of applications have specific requirements that cannot be satisfied by the current cloud infrastructure. In particular, since the cloud computing involves communication to remote servers, two problems arise: firstly, the core network infrastructure can be overloaded, considering the massive amount of data that has to flow through it to allow clients to reach the datacenters; secondly, the latency resulting from this remote interaction between clients and servers is increased. For these, and many other cases also beyond the field of telemedicine, the Edge and Fog computing paradigms were introduced. In these new paradigms, the IT resources are deployed not only in the core cloud datacenters, but also at the edge of the network, either in the telecom operator access network or even leveraging other users' devices. The proximity of resources to end-users allows to alleviate the burden on the core network and at the same time to reduce latency towards users. Indeed, the latency from users to remote cloud datacenters encompasses delays from the access and core networks, as well as the intra-datacenter delay. Therefore, this latency is expected to be higher than that required to interconnect users to edge servers, which in the envisioned paradigm are deployed in the access network, that is, nearby final users. Therefore, the edge latency is expected to be reduced to only a portion of the overall cloud delay. Moreover, the edge and central resources can be used in conjunction, and therefore attention to core cloud monitoring is of capital importance even when edge architectures will have a widespread adoption, which is not the case yet. While a lot of research work has been presented for monitoring several network-related metrics, such as bandwidth, latency, jitter and packet loss, less attention was given to the monitoring of latency in cloud and edge cloud infrastructures. In detail, while some works target cloud-latency monitoring, the evaluation is lacking a fine-grained analysis of latency considering spatial and temporal trends. Furthermore, the widespread adoption of mobile devices, and the Internet of Things paradigm further accelerate the shift towards the cloud paradigm for the additional benefits it can provide in this context, allowing energy savings and augmenting the computation capabilities of these devices, creating a new scenario denoted as mobile cloud. This scenario poses additional challenges for its bandwidth constraints, accentuating the need for tailored methodologies that can ensure that the crucial requirements of the aforementioned applications can be met by the current infrastructure. In this sense, there is still a gap of works monitoring bandwidth-related metrics in mobile networks, especially when performing in-the-wild assessment targeting actual mobile networks and operators. Moreover, even the few works testing real scenarios typically consider only one provider in one country for a limited period of time, lacking an in-depth assessment of bandwidth variability over space and time. In this thesis, I therefore consider monitoring methodologies for challenging scenarios, focusing on latency perceived by customers of public cloud providers, and bandwidth in mobile broadband networks. Indeed, as described, achieving low latency is a critical requirement for core cloud infrastructures, while providing enough bandwidth is still challenging in mobile networks compared to wired settings, even with the adoption of 4G mobile broadband networks, expecting to overcome this issue only with the widespread availability of 5G connections (with half of total traffic expected to come from 5G networks by 2026). Therefore, in the research activities carried on during my PhD, I focused on monitoring latency and bandwidth on cloud and mobile infrastructures, assessing to which extent the current public cloud infrastructure and mobile network make multimedia and telemedicine applications (as well as others having similar requirements) feasible