Stochastic Delay Bound in Sink-Tree Networks

Abstract

Sensor networks are deployed in many fields for its availability and timeliness to capture significant information. It is very important to provide a guaranteed delay for some timesensitive applications. Unfortunately, many previous work focus on routing strategy or energy management, and these related results bring longer delay to sensor networks. Actually, the theoretical bound is significant for sensor network deployment. Some articles have concerned the delay bound of aggregating flows, but all of these methods only provide some deterministic results, which is not consistent with the reality that the sensor node generates signal randomly and wireless links could undergo stochastic changes. In this paper, an aggregation output property in sensor networks with sink-tree structure is derived from stochastic network calculus theory. Based on this property, a stochastic delay bound of aggregation flows is obtained. Compared with the result in deterministic network calculus, the new bound is very tight and more applicable. A brief conclusion and the future work are also introduced in the last section.

Hybrid Modeling Method Based on FSPN for Sensor Networks

“…Considering a sink-tree model in sensor networks [8], [9] as shown in Fig. 1, it is the typical sensor network model which is also adopted in this paper.…”

“…In this section, we show the ability of the FSPN modeling mechanism by an example chosen from [9]. Fig.…”