The Interactive Visualization of Communication Graphs in Wireless Networks

The Research Project

Recent years have seen significant advances in smart antenna technologies, and the beginnings of deployment of smart antennas into wireless networks. A directional antenna is a type of smart antenna capable of concentrating its transmission energy within a narrow angle, aimed in an intended direction, thereby enjoying the benefits of spatially confined transmission and reduced interference. Translated into geometric terms, a directional antenna is a cone defined by three configurable parameters – orientation θ, range r, and angular aperture α – which adhere to geometric constraints (see Figure 1a). Wireless nodes are points in space, and two nodes are connected by an edge (communication link) if and only if the region covered by a directional antenna beam at each node includes the counterpart node. The collection of all communication links forms a communication graph.

Most of the current research covers the case k = 1, α = 2π and θ = 0, which is the case of omnidirectional antennas. However, current approaches with omnidirectional antennas cannot be directly extended to support efficient use of directional antennas. The employment of directional antennas in wireless networks poses new challenges and offers numerous opportunities for novel research in computational geometry. Essentially, we ask ourselves this question: Can we provide each node with multiple directional antennas, and configure these antennas appropriately to form efficient communication graphs, to improve a variety of notions of performance? A minimum requirement for the communication graph in question would be to maintain connectivity among nodes, so that messages may be passed from any one node to any other. Another essential property is to maintain short paths between pairs of nodes, for efficient communication.

Our main goal is to establish relationships between antenna parameters (such as minimum required radius to maintain connectivity) and properties of the induced communication graph.

This research project has been funded by the CRA-W Program for Collaborative Research Experiences for Undergraduates (CREU).