Wireless channel emulators are important tools for testing radio devices, especially in mobile environments. Wireless network emulators give the same accuracy and control for testing radio network systems that traditional channel emulators give to point to point radio links. Network emulators require many more independent channels than traditional channel emulators. This problem is particularly challenging for the real time channel simulator in the emulator. The challenges of designing a wireless network channel simulator are discussed and a design is presented on a Xilinx Virtex-II Pro FPGA. This channel simulator can model 210 independent channels between 15 nodes with a bandwidth of 90 MHz. The performance of the design was verified by measuring transport-layer throughput between 802.11b radios transmitting through the channel simulator.

Testing and evaluating protocols and applications for wireless networks and mobile users is challenging because the physical environment has a significant impact on the behavior and dynamics of the system. It is however important that these physical world effects are considered during system impleme

Increasingly, 802.11 devices are being used by mobile users. This results in very dynamic wireless channels that are difficult to use efficiently. Current rate selection algorithms are dominated by probe-based approaches that search for the best transmission rate using trial-and-error. In mobile environments, probe-based techniques often perform poorly because they inefficiently search for the moving target presented by the constantly changing channel. We have developed a channel-aware rate adaptation algorithm CHARM - that uses signal strength measurements collected by the wireless cards to help select the transmission rate. Moreover, unlike previous approaches CHARM leverages channel reciprocity to obtain channel information, so the information is available to the transmitter without incurring RTS/CTS overhead. This combination of techniques allows CHARM to respond quickly to dynamic channel changes. We implemented CHARM in the Madwifi driver for wireless cards using the Atheros chipset. Our evaluation both in the real world and on a controlled testbed shows that channel-aware rate selection can significantly outperform probe-based rate adaptation, especially over dynamic channels.

Current rate selection algorithms are dominated by probe-based approaches that search for the best transmission rate using trial-and-error. When operating over a dynamic channel, probe-based techniques can perform poorly since they inefficiently search for the moving target presented by the constantly changing channel. We have developed a channel-aware rate adaptation algorithm - CHARM - that responds quickly to dynamic channel changes, and significantly outperforms probe-based algorithms in many instances. Unlike previous approaches, CHARM leverages channel reciprocity to obtain channel information without incurring RTS/CTS overhead. Our work shows that channel-aware rate selection is viable, and can significantly outperform probe-based rate adaptation over both static and dynamic channels.

Networking researchers have long faced a fundamental tension between the experimental realism of wireless testbeds on one hand, and the control and repeatability of simulation on the other hand. To overcome the stark tradeoff of these traditional alternatives, we have developed a wireless network emulator that enables both realistic and repeatable experimentation at network scale. A critical component in this emulator is the RF front end that converts RF signals to lower frequencies - where they can be digitized - and vice versa. We discuss the unique requirements that physical layer network emulation demands of an RF front end. We present a design that meets these demands and demonstrate its performance via measurements.

Over the past few years, wireless networking technologies have made vast forays into our daily lives. Today, one can find 802.11 hardware and other personal wireless technology employed at homes, shopping malls, coffee shops and airports. Present-day wireless network deployments bear two important properties: they are unplanned, with most access points (APs) deployed by users in a spontaneous manner, resulting in highly variable AP densities; and they are unmanaged, since manually configuring and managing a wireless network is very complicated. We refer to such wireless deployments as being chaotic.In this paper, we present a study of the impact of interference in chaotic 802.11 deployments on end-client performance. First, using large-scale measurement data from several cities, we show that it is not uncommon to have tens of APs deployed in close proximity of each other. Moreover, most APs are not configured to minimize interference with their neighbors. We then perform trace-driven simulations to show that the performance of end-clients could suffer significantly in chaotic deployments. We argue that end-client experience could be significantly improved by making chaotic wireless networks self-managing. We design and evaluate automated power control and rate adaptation algorithms to minimize interference among neighboring APs, while ensuring robust end-client performance.

This paper analyzes the causes of packet loss in a 38-node urban multi-hop 802.11b network. The patterns and causes of loss are important in the design of routing and error-correction protocols, as well as in network planning.The paper makes the following observations. The distribution of inter-node loss rates is relatively uniform over the whole range of loss rates; there is no clear threshold separating "in range" and "out of range." Most links have relatively stable loss rates from one second to the next, though a small minority have very bursty losses at that time scale. Signal-to-noise ratio and distance have little predictive value for loss rate. The large number of links with intermediate loss rates is probably due to multi-path fading rather than attenuation or interference.The phenomena discussed here are all well-known. The contributions of this paper are an understanding of their relative importance, of how they interact, and of the implications for MAC and routing protocol design.

Pervasive computing applications are increasingly leveraging contextual information from several sources to provide users with behavior appropriate to the environment in which they reside. If these sources of contextual information are used and deployed in an ad hoc manner however they may provide overlapping functionality, fail to provide needed functionality, and require the use of inconsistent interfaces by applications. To overcome these problems, we introduce a contextual information service that provides applications with contextual information via a virtual database. Unlike previous efforts, our service provides applications a consistent, lightweight, and powerful mechanism for obtaining contextual information, and includes explicit support for the on demand computation of contextual information. We show, via example applications and a contextual information service prototype that we have implemented, how this approach can be used to allow proactive applications to adapt their behavior to match a user's current environment.

Recently, there has been a lot of interest in using Java for parallel programming. Efforts have been hindered by lack of standard Java parallel programming APIs. To alleviate this problem, various groups started projects to develop Java message passing systems modelled on the successful Message Passing Interface (MPI). Official MPI bindings are currently defined only for C, Fortran, and C++, so early MPI-like environments for Java have been divergent. This paper relates an effort undertaken by a working group of the Java Grande Forum, seeking a consensus on an MPI-like API, to enhance the viability of parallel programming using Java. Copyright © 2000 John Wiley & Sons, Ltd.

Phylogenetic analysis is an integral part of many biological research programs. In essence, it is the study of gene genealogy. It is the study of gene mutation and the generational relationships. Phylogenetic analysis is being used in many diverse areas such as human epidemiology, viral transmission, biogeography, and systematics. Researchers are now commonly generating many DNA sequences from many individuals, thus creating very large data sets. However, our ability to analyze the data has not kept pace with data generation, and phylogenetics has now reached a crossroads where we cannot effectively analyze the data we generate. The chief challenge of phylogenetic systematics in the next century will be to develop algorithms and search strategies to effectively analyze large data sets. The crux of the computational problem is that the actual landscape of possible topologies can be extraordinarily difficult to evaluate with large data sets. The parsimony ratchet is actually a family of iterative tree search methods that use a statistical approach to sampling tree islands and ultimately finding the most parsimonious trees for a data set. Each iteration of the parsimony ratchet may occur in parallel as there is no direct dependency between iterations. The authors' implementation of the parallel ratchet is masterworker based. A master process is launched in the DOGMA system which then launches worker tasks on available nodes. Each worker task is simply wrapper code that is used to interact with the newest release version of NONA.

Heterogeneous distributed computing has traditionally been a problematic undertaking which increases in complexity as heterogeneity increases. The recent advent of Java has made heterogeneous computing a fairly straightforward task. Nevertheless, many researchers have not considered the use of Java in a mainstream parallel programming environment. The performance of Java just-in-time compilers currently approaches optimized C for many applications, making Java a serious contender for supercomputing application development. This paper presents DOGMA (Distributed Object Group Metacomputing Architecture)-a new Java-based system which enables parallel computing on heterogeneous computers. DOGMA provides support for dedicated clusters as well as idle workstations through the use of a Web-based browse-in feature or the DOGMA screen saver, which improves workstation utilization. DOGMA supports parallel programming in both a traditional message-passing form and a novel object-oriented approach. This research provides a unified environment for developing high-performance supercomputing applications on heterogeneous systems.

The performance of Java just-in-time compilers currently approaches native C++, making Java a serious contender for supercomputing application development. This paper presents DOGMA – a new Java based system which enables parallel computing on heterogeneous computers. DOGMA supports parallel programming in both a traditional message-passing form and a novel object-oriented approach. DOGMA provides support for dedicated clusters as well as idle workstations through the use of a web-based browse-in feature or the DOGMA screen saver. This research provides a unified environment for developing high-performance supercomputing applications on heterogeneous systems. © 1998 John Wiley & Sons, Ltd.