Performance Modeling of WSN with Bursty Delivery Mode

TL;DR

This paper analyzes the performance of Wireless Sensor Networks under bursty traffic conditions, focusing on packet delay and buffer overflow, using analytical methods and simulations with various traffic models.

Contribution

It introduces an N-BURST traffic model for WSNs and evaluates the impact of bursty traffic on network performance through analytical and simulation approaches.

Findings

Bursty traffic significantly affects packet delay and buffer overflow.

Long-range dependency traffic exhibits different behavior than short-range dependency.

Simulation results over multiple days reveal day-to-day statistical fluctuations.

Abstract

Wireless Sensor Network (WSN) usually consist of hundreds or thousands of sensor nodes scattered in a geographical area and one or multiple sink(s) collecting information. The special design and character of sensors and their applications make WSNs different from traditional networks. These characteristics pose great challenges for architecture and protocol design, performance modeling, and implementation. Accurately modeling the data generated by each sensor node is essential for correctly simulating network traffic, network congestion, interference between nodes and the energy expended by each node. Successful design leads to enhancing the overall performance of the whole of network. In this paper we analyze the performance of WSN with N-BURST traffic model. The impact of bursty traffic on the mean packet delay and buffer overflow probability is investigated analytically. We study the effects of bursty WSN traffic through simulations with three different cases. Both short-range dependency (SRD) traffic and long range dependency (LRD) traffic are simulated over different burst parameters. Finally we study the effect of pareto OFF time through simulation. The results are collected for 10 different 24 hour simulated periods in order to study and measure day-today statistical fluctuation.