Scheduling and bandwidth allocation in cognitive radio sensor networks
The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio (CR). A cognitive radio sensor network (CRSN) is a promising technology to meet the rapid demand for implementing wirele...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/77763/1/FK%202019%2063%20IR.pdf |
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| Summary: | The rapid expansion of wireless monitoring and surveillance applications in several
domains reinforces the trend of exploiting emerging technologies such as the cognitive
radio (CR). A cognitive radio sensor network (CRSN) is a promising technology
to meet the rapid demand for implementing wireless sensor network (WSN) applications
in new fields beside the conventional ones. CRSN technology enables sensor
nodes to utilize licensed radio channels opportunistically for the new applications,
which combine various types of data, traffic patterns, and quality of service (QoS)
requirements. However, several challenges arise due to the conventional capabilitylimitation
of end-sensor nodes and the strict obligations required for the licensed
users. Hence, there is a critical need to manage the network's limited resources
efficiently.
In this research, a new paradigm for CRSN is proposed to achieve a significant balancing
between network's complexity, cost, lifetime, scalability and QoS satisfaction.
In particular, an efficient resource allocation scheme is proposed to deal with multilevel
of heterogeneity that becomes a common advantage in the emerging networks.
The proposed scheme tackles provisioning multilevel of QoS for two key resource
allocation elements, namely, the scheduling and the radio channel allocation.
This research focuses on proposing a new cognitive radio-based medium access control
(MAC) scheme that treats the heterogeneous nature of new networks in terms
of the traffic pattern and the required QoS. In addition to addressing and modelling
delay, throughput, and power consumption, several other performance metrics such
as reliability and scalability have been treated efficiently when designing the scheme.
The proposed paradigm decreases the consumed power on several fronts and achieves
up to 68% as power-saving for the end-sensor nodes.
The effectiveness of the proposed scheme also includes increasing the opportunity to
utilize a wider range of the radio spectrum. Furthermore, to reinforce the scheme's efficiency and mitigate interference, the impact of data packet size on the performance
of the adaptive CRSN is also analysed to determine the appropriate size.
As a result, the proposed scheme is quite appropriate for real time monitoring and
critical communications applications that acquire significant attention in the next
5G of wireless networks.
In addition, the proposed method is analysed and modelled in both homogeneous
and heterogeneous radio environments. Simulation results and the comparisons with
related works show that the proposed scheme provides satisfactory levels of latency
and spectrum utilization thanks to the efficiency of the scheduling and radio allocation
mechanism. |
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