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Structural change and uncertainty are fundamental properties of dynamic networks, making it difficult to develop communication strategies, i.e., network-level approaches to transport data from sender to receiver. At a basic level, change and uncertainty affect how long any state maintained by a communication strategy remains useful, and so influence the trade-offs made to collect that state. In this talk, I will introduce a framework for organizing the decision space for deciding when a communication strategy should maintain state, and what type of state should be maintained, in a dynamic network. The framework is based on the observation that three network properties (connectivity, unpredictability, and resource contention) determine when state is useful. I will first illustrate the framework by showing an instantiation in terms of specific measures that can be used to describe a network setting. I will then show the framework correctly and consistently organizes the decision space for different communication strategies. Finally, I will demonstrate the analytic power of the framework by using it to (1) uncover surprising aspects of well-known data traces, and (2) identify the need for, and value of, a new strategy for network communication. Joint work with Mark Crovella and Jim Kurose.
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