Abstract
Wireless and mobile network technologies often impose severe resource limitations, resulting in poor and often unsatisfactory performance of the commonly used wireless networking protocols. For instance, power and memory/storage constraints of miniaturized network nodes reduce the throughput and increase the network latency. Through various approaches and technological advances, researchers attempt to compensate somehow for such hardware limitations. However, this is not always necessary. Sometimes, the required performance of such networks does not need to adhere to the level of services that would be required for performancecritical applications. For example, for some applications of sensor networks, minimal latency is not a critical factor and it could be traded off for a more limited resource, such as energy or throughput. Thus, to reduce the energy expenditure, the transmission range of such sensor nodes would be quite short, leading to network topologies in which the average number of neighbors of the network nodes is very small. If the sensor nodes are mobile, then most of the time a node has no neighbors; only infrequently another node migrates into its neighborhood. This means that the classical networking approach of store-and-forward would not work well, as there is nearly never an intact path between a source and a destination.
In this work we introduce the Shared Wireless Infostation Model (SWIM), a model for the propagation of packets in networks with frequent partitions. Using SWIM, a packet propagates through the network by being copied (rather than forwarded) from a node to a node, as links are sporadically created. The goal is that one of the copies of the packet reaches the destination. We derive analytical Markov chains that exhibit tradeoffs between the network resources and non-critical performance such as the tradeoffs between energy, delay, storage, capacity, and processing complexity. To demonstrate how SWIM can be applied to solve a practical problem, we use the example of a biological information acquisition system - radio-tagged whales - as nodes in an ad hoc network.
PhD thesis
My PhD thesis is available at Cornell Library in hardcopy, or an online copy can be viewed as a pdf file.
Applet on whale application of SWIM
This Java applet simulates a network of radio tags that are implanted in whales, our primary application for SWIM.