Work-in-progress: A new random walk for data collection in sensor networks

Motivated by the problem of efficient sensor network data collection via a mobile sink, we present undergoing research in accelerated random walks on Random Geometric Graphs. We first propose a new type of random walk, called the α-stretched random walk, and compare it to three known random walks. We also define a novel performance metric called Proximity Cover Time which, along with other metrics such us visit overlap statistics and proximity variation, we use to evaluate the performance properties and features of the various walks. Finally, we present future plans on investigating a relevant combinatorial property of Random Geometric Graphs that may lead to new, faster random walks and metrics.