Packet loss

About: Packet loss is a research topic. Over the lifetime, 21235 publications have been published within this topic receiving 302453 citations.

Method and apparatus for packet loss detection

Abstract: Conventional network packet traffic loss/drop monitoring mechanisms, such as that employed for pseudowire, IP flow and tunnel traffic monitoring, do not process or diagnose the aggregate counts from both endpoints of a particular pseudowire. A packet loss and detection mechanism periodically exchanges traffic packet counts to maintain an accurate diagnosis of the pseudowire health from either endpoint. Further, the raw packet counts are analyzed to identify misrouted and lost packets, as both should be considered to assess network health and congestion. The pseudowire statistics are maintained for each pseudowire emanating from a particular edge router, providing a complete view of pseudowire traffic affecting a particular edge router. Such statistics are beneficial for problem detection, diagnosis, and for verification of throughput criteria such as those expressed in Quality of Service (QOS) terms and/or SLAs (service level agreements).

Web100: extended TCP instrumentation for research, education and diagnosis

Abstract: TCP has become the dominant protocol for all network data transport because it presents a simple uniform data delivery service which is sufficient for most applications over all types of lower network layers. By its very nature, TCP's adaption and retransmission strategies hide all of the details of the lower layers from the application. For example the only symptom of spurious packet loss (or nearly any other network problem) is longer elapsed time and lower performance.This information hiding is fundamentally important to the growth of the Internet because it decouples the evolution of applications from the evolution of link layers. However it also hides valuable information from researchers, educators, network administrators, and other people who would benefit from insight into the inner workings of TCP and the lower layers.In this paper, we present an architecture and infrastructure that provides for per-connection TCP instrumentation to expose otherwise hidden protocol events. We show examples how the infrastructure can be used in support of research, education and advanced network diagnostic tools.Our work was motivated by the observation that since about 1985 network data rates for typical novice network users have fallen by about three orders of magnitude behind expert users (who have kept up with Moore's Law). We use the term "Wizard Gap" to describe this phenomenon. The Web100 and Net100 projects were formed as one step in closing the Wizard Gap.

Quality-of-service aware routing for static and mobile IPv6-based low-power and lossy sensor networks using RPL

Abstract: The Internet of Things (IoT) has emerged as a paradigm over the last few years as a result of the tight integration of the computing and the physical world. The requirement of remote sensing makes low-power wireless sensor networks one of the key enabling technologies of IoT. These networks encompass several challenges, especially in communication and networking, due to their inherent constraints of low-power features, deployment in harsh and lossy environments, and limited computing and storage resources. The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) 1 was proposed by the IETF ROLL (Routing Over Low-power Lossy links) working group and is currently adopted as an IETF standard in the RFC 6550 since March 2012. Although RPL greatly satisfied the requirements of low-power and lossy sensor networks, several issues remain open for improvement and specification, in particular with respect to Quality of Service (QoS) guarantees and support for mobility.In this paper, we focus mainly on the RPL routing protocol. We propose some enhancements to the standard specification in order to provide QoS guarantees for static as well as mobile LLNs. For this purpose, we propose OF-FL (Objective Function based on Fuzzy Logic), a new objective function that overcomes the limitations of the standardized objective functions that were designed for RPL by considering important link and node metrics, namely end-to-end delay, number of hops, ETX (Expected transmission count) and LQL (Link Quality Level). In addition, we present the design of Co-RPL, an extension to RPL based on the corona mechanism that supports mobility in order to overcome the problem of slow reactivity to frequent topology changes and thus providing a better quality of service mainly in dynamic networks application. Performance evaluation results show that both OF-FL and Co-RPL allow a great improvement when compared to the standard specification, mainly in terms of packet loss ratio and average network latency.

Co-RPL: RPL Routing for Mobile Low Power Wireless Sensor Networks using Corona Mechanism

Abstract: Mobility support for wireless sensor networks has always been a challenging research topic. This paper addresses the issue of mobility support in the Routing Protocol for Low power and lossy networks (RPL), the recently adopted IETF routing protocol standard for low power wireless sensor networks. RPL was originally designed for static networks, with no support for mobility. In this work, we address this gap and propose Co-RPL as an extension to RPL based on the Corona mechanism to support mobility. To demonstrate the effectiveness of Co-RPL, we conducted an extensive simulation study using the Contiki/Cooja simulator and compared the performance against standard RPL. We study the impact of node speed, packet transmission rate and number of Directed Acyclic Graphs (DAG) roots on network performance. The simulation results show that Co-RPL decreases packet loss ratio by 45%, average energy consumption by 50% and end-to-end delay by 2.5 seconds, in comparison with the standard RPL.

BFT protocols under fire

Abstract: Much recent work on Byzantine state machine replication focuses on protocols with improved performance under benign conditions (LANs, homogeneous replicas, limited crash faults), with relatively little evaluation under typical, practical conditions (WAN delays, packet loss, transient disconnection, shared resources). This makes it difficult for system designers to choose the appropriate protocol for a real target deployment. Moreover, most protocol implementations differ in their choice of runtime environment, crypto library, and transport, hindering direct protocol comparisons even under similar conditions. We present a simulation environment for such protocols that combines a declarative networking system with a robust network simulator. Protocols can be rapidly implemented from pseudocode in the high-level declarative language of the former, while network conditions and (measured) costs of communication packages and crypto primitives can be plugged into the latter. We show that the resulting simulator faithfully predicts the performance of native protocol implementations, both as published and as measured in our local network. We use the simulator to compare representative protocols under identical conditions and rapidly explore the effects of changes in the costs of crypto operations, workloads, network conditions and faults. For example, we show that Zyzzyva outperforms protocols like PBFT and Q/U undermost but not all conditions, indicating that one-size-fits-all protocols may be hard if not impossible to design in practice.