Jakob Eriksson

The pothole patrol: using a mobile sensor network for road surface monitoring

This paper investigates an application of mobile sensing: detecting and reporting the surface conditions of roads. We describe a system and associated algorithms to monitor this important civil infrastructure using a collection of sensor-equipped vehicles. This system, which we call the Pothole Patrol (P2), uses the inherent mobility of the participating vehicles, opportunistically gathering data from vibration and GPS sensors, and processing the data to assess road surface conditions. We have deployed P2 on 7 taxis running in the Boston area. Using a simple machine-learning approach, we show that we are able to identify potholes and other severe road surface anomalies from accelerometer data. Via careful selection of training data and signal features, we have been able to build a detector that misidentifies good road segments as having potholes less than 0.2% of the time. We evaluate our system on data from thousands of kilometers of taxi drives, and show that it can successfully detect a number of real potholes in and around the Boston area. After clustering to further reduce spurious detections, manual inspection of reported potholes shows that over 90% contain road anomalies in need of repair.

Cabernet: vehicular content delivery using WiFi

Cabernet is a system for delivering data to and from moving vehicles using open 802.11 (WiFi) access points encountered opportunistically during travel. Using open WiFi access from the road can be challenging. Network connectivity in Cabernet is both fleeting (access points are typically within range for a few seconds) and intermittent (because the access points do not provide continuous coverage), and suffers from high packet loss rates over the wireless channel. On the positive side, WiFi data transfers, when available, can occur at broadband speeds. In this paper, we introduce two new components for improving openWiFi data delivery to moving vehicles: The first, QuickWiFi, is a streamlined client-side process to establish end-to-end connectivity, reducing mean connection time to less than 400 ms, from over 10 seconds when using standard wireless networking software. The second part, CTP, is a transport protocol that distinguishes congestion on the wired portion of the path from losses over the wireless link, resulting in a 2x throughput improvement over TCP. To characterize the amount of open WiFi capacity available to vehicular users, we deployed Cabernet on a fleet of 10 taxis in the Boston area. The long-term average transfer rate achieved was approximately 38 Mbytes/hour per car (86 kbit/s), making Cabernet a viable system for a number of non-interactive applications.

Cooperative transit tracking using smart-phones

Real-time transit tracking is gaining popularity as a means for transit agencies to improve the rider experience. However, many transit agencies lack either the funding or initiative to provide such tracking services. In this paper, we describe a crowd-sourced alternative to official transit tracking, which we call cooperative transit tracking. Participating users install an application on their smart-phone. With the help of built-in sensors, such as GPS, WiFi, and accelerometer, the application automatically detects when the user is riding in a transit vehicle. On these occasions (and only these), it sends periodic, anonymized, location updates to a central tracking server. Our technical contributions include (a) an accelerometer-based activity classification algorithm for determining whether or not the user is riding in a vehicle, (b) a memory and time-efficient route matching algorithm for determining whether the user is in a bus vs. another vehicle, (c) a method for tracking underground vehicles, and an evaluation of the above on real-world data. By simulating the Chicago transit network, we find that the proposed system would shorten expected wait times by 2 minutes with only 5% of transit riders using the system. At a 20% penetration level, the mean wait time is reduced from 9 to 3 minutes.

TrueLink: A Practical Countermeasure to the Wormhole Attack in Wireless Networks

In a wormhole attack, wireless transmissions are recorded at one location and replayed at another, creating a virtual link under attacker control. Proposed counter-measures to this attack use tight clock synchronization, specialized hardware, or overhearing, making them difficult to realize in practice. TrueLink is a timing based countermeasure to the wormhole attack. Using TrueLink, a node i can verify the existence of a direct link to an apparent neighbor, j. Verification of a link i harr j operates in two phases. In the rendezvous phase, the nodes exchange nonces alphaj and betai. This is done with tight timing constraints, within which it is impossible for attackers to forward the exchange between distant nodes. In the authentication phase, i and j transmit a signed message (alphaj,betai), mutually authenticating themselves as the originator of their respective nonce. TrueLink does not rely on precise clock synchronization, GPS coordinates, overhearing, geometric inconsistencies, or statistical methods. It can be implemented using only standard IEEE 802.11 hardware with a minor backwards compatible firmware update. TrueLink is meant to be used together with a secure routing protocol. Such protocols require an authentication mechanism, which will also be used by TrueLink. TrueLink is virtually independent of the routing protocol used. Our performance evaluation shows that TrueLink provides effective protection against potentially devastating wormhole attacks.

DART: dynamic address routing for scalable ad hoc and mesh networks

It is well known that the current ad hoc protocol suites do not scale to work efficiently in networks of more than a few hundred nodes. Most current ad hoc routing architectures use flat static addressing and thus, need to keep track of each node individually, creating a massive overhead problem as the network grows. Could dynamic addressing alleviate this problem? In this paper, we argue that the use of dynamic addressing can enable scalable routing in ad hoc networks. We provide an initial design of a routing layer based on dynamic addressing, and evaluate its performance. Each node has a unique permanent identifier and a transient routing address, which indicates its location in the network at any given time. The main challenge is dynamic address allocation in the face of node mobility. We propose mechanisms to implement dynamic addressing efficiently. Our initial evaluation suggests that dynamic addressing is a promising approach for achieving scalable routing in large ad hoc and mesh networks

Tracking unmodified smartphones using wi-fi monitors

Smartphones with Wi-Fi enabled periodically transmit Wi-Fi messages, even when not associated to a network. In one 12-hour trial on a busy road (average daily traffic count 37,000 according to the state DOT), 7,000 unique devices were detected by a single road-side monitoring station, or about 1 device for every 5 vehicles. In this paper, we describe a system for passively tracking unmodified smartphones, based on such Wi-Fi detections. This system uses only common, off-the-shelf access point hardware to both collect and deliver detections. Thus, in addition to high detection rates, it potentially offers very low equipment and installation cost. However, the long range and sparse nature of our opportunistically collected Wi-Fi transmissions presents a significant localization challenge. We propose a trajectory estimation method based on Viterbis algorithm which takes second-by-second detections of a moving device as input, and produces the most likely spatio-temporal path taken. In addition, we present several methods that prompt passing devices to send additional messages, increasing detection rates an use signal-strength for improved accuracy. Based on our experimental evaluation from one 9-month deployment and several single-day deployments, passive Wi-Fi tracking detects a large fraction of passing smartphones, and produces high-accuracy trajectory estimates.

Scalable ad hoc routing: the case for dynamic addressing

We show that the use of dynamic addressing can enable scalable routing in ad hoc networks. It is well known that the current ad hoc protocol suites do not scale to work efficiently in networks of more than a few hundred nodes. Most current ad hoc routing architectures use flat static addressing and thus, need to keep track of each node individually, creating a massive overhead problem as the network grows. Could dynamic addressing alleviate this problem? To begin to answer this question, we provide an initial design of a routing layer based on dynamic addressing, and evaluate its performance. Each node has a unique permanent identifier and a transient routing address, which indicates its location in the network at any given time. The main challenge is dynamic address allocation in the face of node mobility. We propose mechanisms to implement dynamic addressing efficiently. Our initial evaluation suggests that dynamic addressing is a promising approach for achieving scalable routing in meganode ad hoc networks.

Feasibility study of mesh networks for all-wireless offices

There is a fair amount of evidence that mesh (static multihop wireless) networks are gaining popularity, both in the academic literature and in the commercial space. Nonetheless, none of the prior work has evaluated the feasibility of applications on mesh through the use of deployed networks and real user traffic. The state of the art is the use of deployed testbeds with synthetic traces consisting of random traffic patterns.In this paper, we evaluate the feasibility of a mesh network for an all-wireless office using traces of office users and an actual 21-node multi-radio mesh testbed in an office area. Unlike previous mesh studies that have examined routing design in detail, we examine how different office mesh design choices impact the performance of user traffic. From our traces of 11 users spanning over a month, we identify 3 one hour trace periods with different characteristics and evaluate network performance for them. In addition, we consider different user-server placement, different wireless hardware, different wireless settings and different routing metrics.We find that our captured traffic is significantly different from the synthetic workloads typically used in the prior work. Our trace capture and replay methodology allows us to directly quantify the feasibility of office meshes by measuring the additional delay experienced by individual transactions made by user applications. Performance on our mesh network depends on the routing metric chosen, the user-server placement and the traffic load period. The choice of wireless hardware and wireless settings has a significant impact on performance under heavy load and challenging placement. Ultimately we conclude that for our traces and deployed system, under most conditions, all-wireless office meshes are feasible. In most cases, individual transactions incur under 20ms of additional delay over the mesh network. We believe this is an acceptable delay for most applications where a wired network to every machine is not readily available. We argue that our results are scalable to a network of over 100 users.

Map inference in the face of noise and disparity

This paper describes a process for automatically inferring maps from large collections of opportunistically collected GPS traces. In this type of dataset, there is often a great disparity in terms of coverage. For example, a freeway may be represented by thousands of trips, whereas a residential road may only have a handful of observations. Additionally, while modern GPS receivers typically produce high-quality location estimates, errors over 100 meters are not uncommon, especially near tall buildings or under dense tree coverage. Combined, GPS trace disparity and error present a formidable challenge for the current state of the art in map inference. By tuning the parameters of existing algorithms, a user may choose to remove spurious roads created by GPS noise, or admit less-frequently traveled roads, but not both. In this paper, we present an extensible map inference pipeline, designed to mitigate GPS error, admit less-frequently traveled roads, and scale to large datasets. We demonstrate and compare the performance of our proposed pipeline against existing methods, both qualitatively and quantitatively, using a real-world dataset that includes both high disparity and noise. Our results show significant improvements over the current state of the art.

PeerNet: Pushing Peer-to-Peer Down the Stack

An unwritten principle of the Internet Protocol is that the IP address of a node also serves as its identifier. We observe that many scalability problems result from this principle, especially when we consider mobile networks. In this work, we examine how we would design a network with a separation between address and identity. We develop PeerNet, a peer-to-peer-based network layer for large networks. PeerNet is not an overlay on top of IP, it is an alternative to the IP layer. In PeerNet, the address reflects the node’s current location in the network. This simplifies routing significantly but creates two new challenges: the need for consistent address allocation and an efficient node lookup service. We develop fully distributed solutions to address these and other issues using a per-node state of O(log N), where N is the number of nodes in the network. PeerNet is a radically different alternative to current network layers, and our initial design suggests that the PeerNet approach is promising and worth further examination.