  Information-driven networks include a large category of networking systems,
where network nodes are aware of information delivered and thus can not only
forward data packets but may also perform information processing. In many
situations, the quality of service (QoS) in information-driven networks is
provisioned with the redundancy in information. Traditional performance models
generally adopt evaluation measures suitable for packet-oriented service
guarantee, such as packet delay, throughput, and packet loss rate. These
performance measures, however, do not align well with the actual need of
information-driven networks. New performance measures and models for
information-driven networks, despite their importance, have been mainly blank,
largely because information processing is clearly application dependent and
cannot be easily captured within a generic framework. To fill the vacancy, we
present a new performance evaluation framework particularly tailored for
information-driven networks, based on the recent development of stochastic
network calculus. We analyze the QoS with respect to information delivery and
study the scheduling problem with the new performance metrics. Our analytical
framework can be used to calculate the network capacity in information delivery
and in the meantime to help transmission scheduling for a large body of systems
where QoS is stochastically guaranteed with the redundancy in information.
