Improved Resource Allocation and Network Connectivity in CRSN Based Smart Grid for Efficient Grid Automation

Ogbodo, Emmanuel U.; Dorrell, David G.; Abu‐Mahfouz, Adnan M.

doi:10.1109/ictas.2019.8703608

Cited by 4 publications

(6 citation statements)

References 22 publications

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“…Radio resource optimization criterion, which is an important consideration for resource allocation in a CRSN based SG, has been highlighted. In addition, an improved RRA architecture called DHC architecture for a CRSN based SG [114] has been adopted in this work as a recommendation for CRSN based SG deployment. The various resource allocation schemes, i.e., RRA architecture in a CRSN based SG, have been presented in this paper.…”

Section: Discussionmentioning

confidence: 99%

“…The DHC architecture from a recent work [114] can be adopted for a CRSN based SG deployment in order to leverage multiple performance improvement criteria. The architecture consists of heterogeneous CRSN nodes such as normal ZigBee CR nodes, actuator, and multimedia sensor nodes.…”

Section: Distributed Heterogeneous Clustered (Dhc) Architecturementioning

confidence: 99%

“…To obtain an appreciable or higher received average SNR, the error or blocking probability should be minimal. But the error or blocking probability, ̅ of the MQAM signal under Rayleigh fading channel is given by [114]: The relationship of SNR and throughput is given to obtain the maximized throughput so that…”

Section: Guaranteed Network Connectivity Channel Allocation Formentioning

confidence: 99%

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Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

Ogbodo¹,

Dorrell²,

Abu‐Mahfouz³

2019

Preprint

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A cognitive radio sensor network (CRSN) based Smart Grid (SG) is a new paradigm for a modern SG. It is totally different from the traditional power grid and also different from the conventional SG that uses a static resource allocation technique to allocate resources to sensor nodes and communication devices in the SG network. Due to the challenges associated with competitive sensor nodes and communication devices in accessing and utilizing radio resources, the need for dynamic radio resource allocation (RRA) has been proposed as a solution for allocating radio resources to sensor nodes in a CRSN based smart grid ecosystem (network). These challenges include energy/power constraints, poor quality of service (QoS), interference, delay, spectrum efficiency issues, and excessive spectrum hand-offs. Hence, the optimization of resource allocation criteria, such as energy efficiency, throughput maximization, QoS guarantee, fairness, priority, interference mitigation/avoidance, etc., will go a long way in addressing the problems of RRA in a CRSN based SG. Consequently, this work explores RRA in CRSNs for SGs. Various resource allocation schemes, as well as its architecture in a CRSN for SG environment, are presented. The work reported in this paper introduces a model called the “guaranteed network connectivity channel allocation” for throughput maximization (GNC-TM) and optimal spectrum band determination in RRA for improved throughput criteria in CRSNs for SGs. The results show that the model outperforms the existing protocol in terms of throughput and error probability. Finally, the contribution to knowledge and future research direction, such as energy efficiency and hybrid energy harvesting schemes are highlighted.

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Section: Discussionmentioning

confidence: 99%

Section: Distributed Heterogeneous Clustered (Dhc) Architecturementioning

confidence: 99%

Section: Guaranteed Network Connectivity Channel Allocation Formentioning

confidence: 99%

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Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

Ogbodo¹,

Dorrell²,

Abu‐Mahfouz³

2019

Preprint

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“…However, the mesh topology has higher complexity and energy consumption with minimal delay. Detailed discussions on the network topologies including their merits and demerits can be found in [40][41][42].…”

Section: Lpwan Architecturementioning

confidence: 99%

A Survey on 5G and LPWAN-IoT for Improved Smart Cities and Remote Area Applications: From the Aspect of Architecture and Security

Ogbodo

Abu‐Mahfouz

Kurien

2022

Sensors

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Addressing the recent trend of the massive demand for resources and ubiquitous use for all citizens has led to the conceptualization of technologies such as the Internet of Things (IoT) and smart cities. Ubiquitous IoT connectivity can be achieved to serve both urban and underserved remote areas such as rural communities by deploying 5G mobile networks with Low Power Wide Area Network (LPWAN). The current architectures will not offer flexible connectivity to many IoT applications due to high service demand, data exchange, emerging technologies, and security challenges. Hence, this paper explores various architectures that consider a hybrid 5G-LPWAN-IoT and Smart Cities. This includes security challenges as well as endogenous security and solutions in 5G and LPWAN-IoT. The slicing of virtual networks using software-defined network (SDN)/network function virtualization (NFV) based on the different quality of service (QoS) to satisfy different services and quality of experience (QoE) is presented. Also, a strategy that considers the implementation of 5G jointly with Weightless-N (TVWS) technologies to reduce the cell edge interference is considered. Discussions on the need for ubiquity connectivity leveraging 5G and LPWAN-IoT are presented. In addition, future research directions are presented, including a unified 5G network and LPWAN-IoT architecture that will holistically support integration with emerging technologies and endogenous security for improved/secured smart cities and remote areas IoT applications. Finally, the use of LPWAN jointly with low earth orbit (LEO) satellites for ubiquitous IoT connectivity is advocated in this paper.

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“…However, the EDHC-SA network connectivity method, is modeled by a equilateral triangulation pattern, denoted as G = (V , E), where V represents the vertices of the triangle and E are the edges which is the communication links or line segments between the vertices. Hence, in order to maintain network coverage and connectivity, the following properties stipulated in Ogbodo et al 17 are adopted:…”

Section: Edhc-sa Network Modelmentioning

confidence: 99%

Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid

Ogbodo

Dorrell

Abu‐Mahfouz

2021

International Journal of Distributed Sensor Networks

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The development of a modern electric power grid has triggered the need for large-scale monitoring and communication in smart grids for efficient grid automation. This has led to the development of smart grids, which utilize cognitive radio sensor networks, which are combinations of cognitive radios and wireless sensor networks. Cognitive radio sensor networks can overcome spectrum limitations and interference challenges. The implementation of dense cognitive radio sensor networks, based on the specific topology of smart grids, is one of the critical issues for guaranteed quality of service through a communication network. In this article, various topologies of ZigBee cognitive radio sensor networks are investigated. Suitable topologies with energy-efficient spectrum-aware algorithms of ZigBee cognitive radio sensor networks in smart grids are proposed. The performance of the proposed ZigBee cognitive radio sensor network model with its control algorithms is analyzed and compared with existing ZigBee sensor network topologies within the smart grid environment. The quality of service metrics used for evaluating the performance are the end-to-end delay, bit error rate, and energy consumption. The simulation results confirm that the proposed topology model is preferable for sensor network deployment in smart grids based on reduced bit error rate, end-to-end delay (latency), and energy consumption. Smart grid applications require prompt, reliable, and efficient communication with low latency. Hence, the proposed topology model supports heterogeneous cognitive radio sensor networks and guarantees network connectivity with spectrum-awareness. Hence, it is suitable for efficient grid automation in cognitive radio sensor network–based smart grids. The traditional model lacks these capability features.

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Improved Resource Allocation and Network Connectivity in CRSN Based Smart Grid for Efficient Grid Automation

Cited by 4 publications

References 22 publications

Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

A Survey on 5G and LPWAN-IoT for Improved Smart Cities and Remote Area Applications: From the Aspect of Architecture and Security

Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid

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