Abstract

As the reference communication standard of wireless sensor networks (WSNs), the IEEE 802.15.4 standard has been adopted in various WSN-based applications. In many of these applications, one of the most common traffic pattern types is a periodic traffic patterns, however, the majority of existing analytical models target either saturated or unsaturated network traffic patterns. Furthermore, few of them can be directly extended to the periodic traffic scenario, since periodic traffic brings unstable load status to sensor nodes. To better characterize the WSNs with periodic traffic, we propose an accurate and scalable analytical framework for the IEEE 802.15.4 MAC protocol. By formulating the relationship between clear channel assessment (CCA) and its successful probability from the perspective of channel state and node state, single node’s behavior and whole network’s performance under different network scales and traffic loads can be derived. Extensive simulations are conducted to validate the proposed framework in terms of both local statistics and overall statistics, and the results show that the model can represent the actual behavior and the real performance of both single node and whole network. Besides, as the simplified version of double CCAs mode (DS mode), single CCA mode (SS mode), is also analyzed with simple modifications on the proposed analytical framework. Combining the analytical framework with simulation results, the applicable network scenarios of two modes are also demonstrated respectively. Finally, an approximate distribution of one data packet’s backoff duration is proposed. With this approximate distribution, a conservative estimation of data packet’s average transmission latency in networks with given configurations can be easily carried out.

Highlights

  • Wireless sensor networks (WSNs) have penetrated various kinds of applications, ranging from habitat monitoring to industrial process control, for their advantages of low deployment costs, ease of installation, maintenance and reconfiguration, and the inherent intelligent-processing capability over traditional wired devices [1]

  • The framework is unfolded from two perspectives, channel state and node state

  • Different from assuming single clear channel assessment (CCA) mode (SS mode) as previous works do, this paper proposes a Markov chain-based channel state model which supports the analysis of networks adopting double CCA mode (DS mode)

Read more

Summary

Introduction

Wireless sensor networks (WSNs) have penetrated various kinds of applications, ranging from habitat monitoring to industrial process control, for their advantages of low deployment costs, ease of installation, maintenance and reconfiguration, and the inherent intelligent-processing capability over traditional wired devices [1]. In WSNs that support advanced metering infrastructure (AMI) applications, sensors are usually configured to periodically send application-specific data (such as electricity consumption) to a base station collector for system monitoring and analysis [12,13] Another example is the transmission line monitoring applications. To accurately characterize the MAC behavior of nodes and the performance of WSNs with periodic traffic, we propose a competent analytical framework of the slotted CSMA/CA protocol. By formulating the relationship between the probability of performing clear channel assessment (CCA) and its successful probability from both perspectives, the performance statistics of single node and whole network under different scales and traffic loads are carried out. With a given network scale, data packet’s inter-arrival time and channel access parameters, the performance statistics of a single node and the whole network can be estimated.

Related Works
The Slotted CSMA-CA Protocol
Channel State Analysis
Node State Analysis
The Distribution of Backoff Period
The Probability of Saturated Load Status
The Analysis of Single Node’s CCA1 Operation
The Probability of CCA1 Operation
The Probability of Collision
Throughput Analysis
Energy Consumption Analysis
Simulation Setup
Model Validation
An Estimation of Average Transmission Latency
Findings
Conclusions
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.