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Network capacity is a critical feature of wireless ad hoc and sensor networks. It is particularly challenging to determine network capacity when combined with other performance objectives such as timeliness. This paper investigates real-time capacity for event-driven data-gathering sensor networks with unbalanced many-to-one traffic patterns. First, the authors compute the average allowable throughputs of nodes for a given event distribution, based on which they then leverage results of queuing theory to estimate the per-hop delays. They develop a new slack time distribution scheme for unbalanced many-to-one traffic patterns, and prove it as optimal in terms of the per-hop success probability. Here the per-hop success probability is defined as the probability for a packet to meet its sub-deadlines at each hop.
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