evaluating the capacity of resource-constrained dtns
Due to their low network connectivity, sparsely-connected networks can support delay-tolerant applications only. Thus, such communication environments are examples of Delay-Tolerant Networks (DTNs). While in some DTN connectivity is predictable (e.g., scheduled), in others, connectivity is created randomly. For instance, to save battery power, nodes in a sensor network may be programmed to follow a pre-arranged sleep patterns, or may enter the sleep state opportunistically. In a sparsely-connected network, source-to-destination route discovery cannot be implemented, since at any particular time, there rarely exists a connected path between the source node and the destination node. Consequently, the conventional approaches to implement network routing do not work and new methods are needed. Flooding (as implemented, for example, using epidemic routing) could be used to spread information through the network. With multiple copies of each packet in the network, the time to offload the data to the destination can be significantly reduced, but at the expense of increased energy and storage utilization. However, in some DTNs, network resources may be limited, for instance due to physical constraints of the network devices. In this paper, we consider the implications of the limited network resources, such as limited communication bandwidth, on the performance and the capacity of a DTN.In particular, leveraging from our previous work on DTN, we use the Shared Wireless Infostation Model (SWIM) to derive a strategy to mathematically represent a DTN, which allows us to evaluate the network throughput capacity, while including a variety of restrictions on network resources. Using this mathematical model derived here, will allow the network designers to adjust the allocated network resources, as to trade off system performance and system resources, while achieving the required network capacity.
dtn delay-tolerant networks sensor networks flooding epidemic routing shared wireless infostation model swim network capacity manet ad hoc networks sparsely connected networks mobility