David Kotz

Experimental evaluation of wireless simulation assumptions

All analytical and simulation research on ad~hoc wireless networks must necessarily model radio propagation using simplifying assumptions. We provide a comprehensive review of six assumptions that are still part of many ad hoc network simulation studies, despite increasing awareness of the need to represent more realistic features, including hills, obstacles, link asymmetries, and unpredictable fading. We use an extensive set of measurements from a large outdoor routing experiment to demonstrate the weakness of these assumptions, and show how these assumptions cause simulation results to differ significantly from experimental results. We close with a series of recommendations for researchers, whether they develop protocols, analytic models, or simulators for ad~hoc wireless networks.

Extracting a Mobility Model from Real User Traces

Understanding user mobility is critical for simula- tions of mobile devices in a wireless network, but current mobility models often do not reflect real user movements. In this paper, we provide a foundation for such work by exploring mobility characteristics in traces of mobile users. We present a method to estimate the physical location of users from a large trace of mobile devices associating with access points in a wireless network. Using this method, we extracted tracks of always-on Wi-Fi devices from a 13-month trace. We discovered that the speed and pause time each follow a log-normal distribution and that the direction of movements closely reflects the direction of roads and walkways. Based on the extracted mobility characteristics, we developed a mobility model, focusing on movements among popular regions. Our validation shows that synthetic tracks match real tracks with a median relative error of 17%.

Mobile agents and the future of the internet

Use of the Internet has exploded in recent years with the appearance of the World-Wide Web. In this paper, we show how current technological trends may lead to a system based substantially on mobile code, and in many cases, mobile agents. We discuss several technical and non-technical hurdles along the path to that eventuality. It seems likely that, within a few years, nearly all major Internet sites will be capable of hosting and willing to host some form of mobile code or mobile agents.

Detecting 802.11 MAC Layer Spoofing Using Received Signal Strength

MAC addresses can be easily spoofed in 802.11 wireless LANs. An adversary can exploit this vulnerability to launch a large number of attacks. For example, an attacker may masquerade as a legitimate access point to disrupt network services or to advertise false services, tricking nearby wireless stations. On the other hand, the received signal strength (RSS) is a measurement that is hard to forge arbitrarily and it is highly correlated to the transmitters location. Assuming the attacker and the victim are separated by a reasonable distance, RSS can be used to differentiate them to detect MAC spoofing, as recently proposed by several researchers. By analyzing the RSS pattern of typical 802.11 transmitters in a 3-floor building covered by 20 air monitors, we observed that the RSS readings followed a mixture of multiple Gaussian distributions. We discovered that this phenomenon was mainly due to antenna diversity, a widely-adopted technique to improve the stability and robustness of wireless connectivity. This observation renders existing approaches ineffective because they assume a single RSS source. We propose an approach based on Gaussian mixture models, building RSS profiles for spoofing detection. Experiments on the same testbed show that our method is robust against antenna diversity and significantly outperforms existing approaches. At a 3% false positive rate, we detect 73.4%, 89.6% and 97.8% of attacks using the three proposed algorithms, based on local statistics of a single AM, combining local results from AMs, and global multi-AM detection, respectively.

CRAWDAD: A Community Resource for Archiving Wireless Data at Dartmouth

Wireless network researchers are seriously starved for data about how real users, applications, and devices use real networks under real network conditions. CRAWDAD (Community Resource for Archiving Wireless Data at Dartmouth) is a new National Science Foundation-funded project to build a wireless-network data archive for the research community. It will host wireless data and provide tools and documents to make collecting and using the data easy. This resource should help researchers identify and evaluate real and interesting problems in mobile and pervasive computing. To learn more about CRAWDAD and discuss its direction, about 30 interested people gathered at a workshop held in conjunction with MobiCom 2005.

AGENT TCL: targeting the needs of mobile computers

Mobile computers have become increasingly popular as users discover the benefits of having their electronic work available at all times. Using Internet resources from a mobile platform, however, is a major challenge. Mobile computers do not have a permanent network connection and are often disconnected for long periods. When the computer is connected, the connection is often prone to sudden failure, such as when a physical obstruction blocks the signal from a cellular modem. In addition, the network connection often performs poorly and can vary dramatically from one session to the next, since the computer might use different transmission channels at different locations. Finally, depending on the transmission channel, the computer might be assigned a different network address each time it reconnects. Mobile agents are one way to handle these unforgiving network conditions. A mobile agent is an autonomous program that can move from machine to machine in a heterogeneous network under its own control. It can suspend its execution at any point, transport itself to a new machine, and resume execution on the new machine from the point at which it left off. Agent Tcl is a mobile agent system whose agents can be written in Tcl, Java, and Scheme. Agent Tcl has extensive navigation and communication services, security mechanisms, and debugging and tracking tools. We focus on Agent Tcls architecture and security mechanisms, its RPC system, and its docking system, which lets an agent move transparently among mobile computers, regardless of when they are connected to the network.

File-access characteristics of parallel scientific workloads

Phenomenal improvements in the computational performance of multiprocessors have not been matched by comparable gains in I/O system performance. This imbalance has resulted in I/O becoming a significant bottleneck for many scientific applications. One key to overcoming this bottleneck is improving the performance of multiprocessor file systems. The design of a high-performance multiprocessor file system requires a comprehensive understanding of the expected workload. Unfortunately, until recently, no general workload studies of multiprocessor file systems have been conducted. The goal of the CHARISMA project was to remedy this problem by characterizing the behavior of several production workloads, on different machines, at the level of individual reads and writes. The first set of results from the CHARISMA project describe the workloads observed on an Intel iPSC/860 and a Thinking Machines CM-5. This paper is intended to compare and contrast these two workloads for an understanding of their essential similarities and differences, isolating common trends and platform-dependent variances. Using this comparison, we are able to gain more insight into the general principles that should guide multiprocessor file-system design.

Analysis of a campus-wide wireless network

Abstract Understanding usage patterns in wireless local-area networks (WLANs) is critical for those who develop, deploy, and manage WLAN technology, as well as those who develop systems and application software for wireless networks. This paper presents results from the largest and most comprehensive trace of network activity in a large, production wireless LAN. For eleven weeks we traced the activity of nearly two thousand users drawn from a general campus population, using a campus-wide network of 476 access points spread over 161 buildings at Dartmouth College. Our study expands on those done by Tang and Baker, with a significantly larger and broader population. We found that residential traffic dominated all other traffic, particularly in residences populated by newer students; students are increasingly choosing a wireless laptop as their primary computer. Although web protocols were the single largest component of traffic volume, network backup and file sharing contributed an unexpectedly large amount to the traffic. Although there was some roaming within a network session, we were surprised by the number of situations in which cards roamed excessively, unable to settle on one access point. Cross-subnet roams were an especial problem, because they broke IP connections, indicating the need for solutions that avoid or accommodate such roams.

Disk-directed I/O for MIMD multiprocessors

Many scientific applications that run on todays multiprocessors, such as weather forecasting and seismic analysis, are bottlenecked by their file-I/O needs. Even if the multiprocessor is configured with sufficient I/O hardware, the file-system software often fails to provide the available bandwidth to the application. Although libraries and enhanced file-system interfaces can make a significant improvement, we believe that fundamental changes are needed in the file-server software. We propose a new technique, disk-directed I/O, to allow the disk servers to determine the flow of data for maximum performance. Our simulations show that tremendous performance gains are possible. Indeed, disk-directed I/O provided consistent high performance that was largely independent of data distribution, obtained up to 93% of peak disk bandwidth, and was as much as 16 times faster than traditional parallel file systems.

Evaluating Next-Cell Predictors with Extensive Wi-Fi Mobility Data

Location is an important feature for many applications, and wireless networks may serve their clients better by anticipating client mobility. As a result, many location predictors have been proposed in the literature, though few have been evaluated with empirical evidence. This paper reports on the results of the first extensive empirical evaluation of location predictors using a two-year trace of the mobility patterns of more than 6,000 users on Dartmouths campus-wide Wi-Fi wireless network. The surprising results provide critical evidence for anyone designing or using mobility predictors. We implemented and compared the prediction accuracy of several location predictors drawn from four major families of domain-independent predictors, namely, Markov-based, compression-based, PPM, and SPM predictors. We found that low-order Markov predictors performed as well or better than the more complex and more space-consuming compression-based predictors