Obtaining sound inferences over remote networks via active or passive measurements is difficult. Active measurement campaigns face challenges of load, coverage, and visibility. Passive measurements require a privileged vantage point. Even networks under our own control too often remain poorly understood and hard to diagnose. As a step toward the democratization of Internet measurement, we consider the inferential power possible were the network to include a constant and predictable stream of dedicated lightweight measurement traffic. We posit an Internet "heartbeat," which nodes periodically send to random destinations, and show how aggregating heartbeats facilitates introspection into parts of the network that are today generally obtuse. We explore the design space of an Internet heartbeat, potential use cases, incentives, and paths to deployment.
Individual networks frequently perform regular pair-wise measurements between nodes or networks under their control, Content Distribution Networks (CDNs) that run continual measurements to detect and route around path problems @cite_39 . The IHB seeks to push such functionality deeper into the network stack such that all networks are empowered with such knowledge without having to implement their own application-layer protocols and measurements. As importantly, the IHB disseminates global knowledge about the Internet, rather than focusing on an individual network.
@cite_39
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Content distribution networks (CDNs) need to make decisions, such as server selection and routing, to improve performance for their clients. The performance may be limited by various factors such as packet loss in the network, a small receive buffer at the client, or constrained server CPU and disk resources. Conventional measurement techniques are not effective for distinguishing these performance problems: application-layer logs are too coarse-grained, while network-level traces are too expensive to collect all the time. We argue that passively monitoring the transport-level statistics in the server's network stack is a better approach. This paper presents a tool for monitoring and analyzing TCP statistics, and an analysis of a CoralCDN node in PlanetLab for six weeks. Our analysis shows that more than 10 of connections are server-limited at least 40 of the time, and many connections are limited by the congestion window despite no packet loss. Still, we see that clients in 377 Autonomous Systems (ASes) experience persistent packet loss. By separating network congestion from other performance problems, our analysis provides a much more accurate view of the performance of the network paths than what is possible with server logs alone. In multi-hop ad hoc networks, stations may pump more traffic into the networks than can be supported, resulting in high packet-loss rate, re-routing instability and unfairness problems. This paper shows that controlling the offered load at the sources can eliminate these problems. To verify the simulation results, we set up a real 6-node multi-hop network. The experimental measurements confirm the existence of the optimal offered load. In addition, we provide an analysis to estimate the optimal offered load that maximizes the throughput of a multi-hop traffic flow. We believe this is a first paper in the literature to provide a quantitative analysis (as opposed to simulation) for the impact of hidden nodes and signal capture on sustainable throughput. The analysis is based on the observation that a large-scale 802.11 network with hidden nodes is a network in which the carrier-sensing capability breaks down partially. Its performance is therefore somewhere between that of a carrier-sensing network and that of an Aloha network. Indeed, our analytical closed-form solution has the appearance of the throughput equation of the Aloha network. Our approach allows one to identify whether the performance of an 802.11 network is hidden-node limited or spatial-reuse limited. In wireless mesh networks (WMNs) traffic is routed from mobile clients through a multihop wireless backbone to and from Internet gateways (IGWs). Because of their limited number, IGWs become the major traffic bottlenecks. The purpose of this work is to explore the benefits of introducing load-dependent routing metrics to increase WMN capacity and performance. We use weighted shortest path routing and introduce LAETT a weight metric that captures both traffic load and link quality. We compare the scheme to ETT and MIC, two load independent metrics, and show in simulation its benefits for various network and traffic configurations. Wireless Sensor Networks (WSNs) are being designed to solve a gamut of interesting real-world problems. Limitations on available energy and bandwidth, message loss, high rates of node failure, and communication restrictions pose challenging requirements for these systems. Beyond these inherent limitations, both the possibility of node mobility and energy conserving protocols that power down nodes introduce additional complexity to routing protocols that depend on up to date routing or neighborhood tables. Such state-based protocols suffer excessive delay or message loss, as system dynamics require expensive upkeep of these tables. Utilizing characteristics of high node density and location awareness, we introduce IGF, a location-aware routing protocol that is robust and works without knowledge of the existence of neighboring nodes (state-free). We compare our work against established routing protocols to demonstrate the efficacy of our solution when nodes are mobile or periodically sleep to conserve energy. We show that IGF far outperforms these protocols, in some cases delivering close to 100 of the packets transmitted while alternate solutions fail to even find a path between a source and destination. Specifically, we show that our protocol demonstrates a vast improvement over prior work using metrics of delivery ratio, control overhead, and end-to-end delay.