Vladislav Petkov

SCORPION: a heterogeneous wireless networking testbed

During the last decade, the success and popularity of wireless standards such as IEEE 802.11 have drawn the attention of the research community to wireless networks. A great amount of effort has been invested into research in this area, most of which relies heavily on simulation and analysis techniques. However, simulations do not precisely control hardware interrupts, packet timing and real physical and MAC layer behaviors. As a result, simulation results need to be validated by real implementations, which is evident by the change in focus of research activities increasingly moving towards real implementations, including the deployment of testbeds as a main tool to analyze network protocol functionality. Under this context, we present an overview of SCORPION (Santa Cruz mObile Radio Platform for Indoor and Outdoor Networks), a heterogeneous wireless networking testbed that includes a variety of nodes ranging from ground vehicles to autonomous aerial vehicles. The purpose of SCORPION to is to deploy and investigate nascent networking protocols using a variety of mobile platforms utilizing structured as well as unstructured mobility patterns.

Collision-free medium access based on traffic forecasting

In this paper we introduce a novel collision-free, schedule-based medium access control protocol for wireless networks. Our protocol, TRANSFORMA (TRAffic FORecasting Medium Access) uses traffic forecasting to significantly reduce packet delivery delays for delay-sensitive applications while maintaining delivery ratios higher than those of contention-based protocols. TRANSFORMAs novel approach to channel access uses the forecast data rate of each application flow to perform distributed probabilistic channel scheduling. We show through simulations that, thanks to its per-application traffic forecasting capabilities, TRANSFORMA yields lower average delays when compared against DYNAMMA, an existing schedule-based MAC, and against 802.11 under high load. TRANSFORMA caters to emerging high data rate, real-time services that will likely be prevalent particularly at the edges of the Internet of the future. Such services which are currently represented by applications such as Skype, Google Talk, and iChat, exhibit traffic characteristics that are fairly predictable and thus well served by TRANSFORMAs traffic forecasting abilities.

SlugTransit: a location-based public transportation management system

In this paper, we describe SlugTransit, an on-line location-based system which allows public transportation systems to be managed in a cost-effective manner while improving overall systems usability and user satisfaction. SlugTransit vehicles report their location in real-time to SlugTransit base stations; vehicle location information is then uploaded and stored in a database. Software updates and log file retrievals are done through SlugTransit gateways. Through a visual, Web-based interface, system operators as well as users have access to current location information in real-time. This capability enables operators to better manage the transportation network, improving efficiency and, at the same time, user satisfaction.

The case for using traffic forecasting in schedule-based channel access

In this paper, we explore the idea of using traffic forecasting to improve the delay performance of a schedule-based medium access control protocol. Schedule-based channel access has been shown to utilize network and energy resources efficiently but is often hindered by the extra delay that scheduling introduces. We explore the use of traffic forecasting to anticipate transmission schedules instead of establishing them reactively, thereby reducing scheduling delays. We show the potential performance benefits traffic forecasting can bring to schedule-based medium access in the context of an existing MAC protocol called DYNAMMA [14]. Preliminary results using a machine-learning based traffic forecasting technique are also presented.