We study the problem of maximizing the aggregated information in sensor networks with deadline constraints. Our model is that of a sensor network that is arranged in the form of a tree topology, where the root corresponds to the sink node, and the rest of the network detects an event and transmits data to the sink over one or more hops. We assume a time-slotted synchronized system and a node-exclusive (also called a primary) interference model. We formulate this problem as an integer optimization problem and show that for unit capacity links, the optimal solution involves solving a Bipartite Maximum Weighted Matching problem at each hop. We propose a polynomial time algorithm that uses only local information at each hop to obtain the optimal solution. Thus, we answer the question of when a node should stop waiting to aggregate data from its predecessors and start transmitting in order to maximize aggregated information within a deadline imposed by the sink. We extend our model to allow for practical considerations such as arbitrary link capacities, and also for multiple overlapping events. Further, we show that our framework is general enough that it can be extended to a number of interesting cases such as incorporating sleep-wake scheduling, minimizing aggregate sensing error, etc.
['Srikanth Hariharan', 'Ness B. Shroff']
Maximizing Aggregated Information in Sensor Networks Under Deadline Constraints