Spatiotemporal Characterization of Users’ Experience in Massive Cognitive Radio Networks

Okegbile, Samuel D.; Maharaj, B. T.; Alfa, Attahiru Sule

doi:10.1109/access.2020.2981953

Cited by 12 publications

(18 citation statements)

References 32 publications

(64 reference statements)

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“…Some tasks are known to be delay-sensitive tasks in reallife applications, while some are delay-tolerant. It is therefore important to classify tasks based on their delay requirements to ensure that the QoS of each task is satisfied [32]. With task classifications, different priority levels could be associated with different task requests [10].…”

Section: B Task Generation Modelmentioning

confidence: 99%

A Multi-User Tasks Offloading Scheme for Integrated Edge-Fog-Cloud Computing Environments

Okegbile

Maharaj

Alfa

2022

IEEE Trans. Veh. Technol.

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This paper presents a multi-user, multi-class and multi-layer edge computing-based framework for effective task offloading and computation processes. Important system requirements that were not captured in the existing multi-layer solutions such as offloading, computations and deadline requirements were captured in the system modeling, while both wireless communications and task computation constraints were considered. We considered three layers system, where each device offloads its generated tasks in each time slot to any selected layer for computation. On its arrival at such a selected layer, the task is only accepted if the queue size is below the pre-defined threshold, otherwise, such a task is offloaded to the next layer. Tasks were classified into class 1 and class 2 tasks following tasks' quality of service requirements. We adopted stochastic geometry, parallel computing and queueing theory techniques to model the performance of the considered integrated edge-fog-cloud computing environment and obtained analysis for various performance metrics of interest. The obtained analyses demonstrate the importance of multi-layer and multiclass edge computing systems towards improving the experience of both delay-sensitive and mission-critical applications in any task offloading environment.

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Section: B Task Generation Modelmentioning

confidence: 99%

A Multi-User Tasks Offloading Scheme for Integrated Edge-Fog-Cloud Computing Environments

Okegbile

Maharaj

Alfa

2022

IEEE Trans. Veh. Technol.

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“…There are several spatiotemporal systemic deployment schemes proposed previously [17], [18], [36]- [40], which have pointed out the limitations of separately handling either spatial deployment or real-time resource allocation. spatiotemporal SINR analysis was conducted for HSCNs, trying to overcome the limitation of modeling bias caused by full buffer assumptions in stochastic geometry based spatial allocation [40].…”

Section: Related Workmentioning

confidence: 99%

“…For instance, stochastic geometry based algorithms are considered recently as the backbone of spatial HSCN deployment [17]. However, previous works either build based on the assumption of full buffer [15] or statistic-based estimation [18], which fails to handle the real-time QoS optimization. It even deteriorates, when these previous works tackle real-time resource allocation for mirogrid based MEC-SC deployment.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal D2D Small Cell Allocation and On-Demand Deployment for Microgrids

et al. 2021

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Microgrids in smart grid development create a new era towards resilient energy supply. In turn, They also render complicated cyber-physical system development towards high scalability and comprehensiveness. Heterogeneous Small Cell based Networks (HSCNs) endow a suitable cyber infrastructure for microgrid based cyber-physical systems. To tackle this emerging research area, this paper proposes a Spatiotemporal Device-to-device communication based HSCN Deployment scheme for Microgrid based Smart grid Development (3xSD), to achieve high energy efficiency with high qualityof-service, chronically and dynamically. Concretely, a joint optimization for long-term energy efficiency and achievable data rate maximization with interference mitigation is formulated for spatial small cell positioning, which models both cyber and physical characteristics of Smart Grid User Equipment (SGUE). A Temporal On-demand Small cell Powering and work-Offloading scheme (TOSPO) is proposed on top of the determined small cell positioning. TOSPO considers the real-time heterogeneous features and demands of SGUEs to maximize energy and cost efficiency, for both communication and computation perspectives. To evaluate the performance of 3xSD, spatial analysis, temporal analysis, and selected case study are simulated. Numerical results showcase that 3xSD is capable of providing both long-term and on-demand optimal energy efficiency and quality-of-service solution for microgrids, outperforming existing benchmarks in the literature.INDEX TERMS Small cells, smart grid, on-demand, energy efficiency, cyber-physical systems.

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“…This, however, is not a limitation on the distributions of users. We considered the protection zone of each transmitter to be the same as the coverage area of such transmitter [28], [29]. This implies that the signal generated by a typical transmitter is not strong enough outside its protection zone to satisfy the SINR requirement.…”

Section: System Modelmentioning

confidence: 99%

“…Similarly, the average throughput in the secondary network can be obtained by substituting (31) into (28). This is expressed as…”

Section: Analysis Of Throughputmentioning

confidence: 99%

Outage and Throughput Analysis of Cognitive Users in Underlay Cognitive Radio Networks With Handover

2020

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Interference characterization in cognitive networks with handover has received less attention in stochastic geometry-based interference management and control, especially in cognitive radio networks, because of the possibility of complicating the analysis of various performance metrics of interest, such as outage probability and throughput. However, because of the possible mobility that is observed in real practical systems, some of the receivers may be located outside the coverage regions of their paired transmitters. In order to ensure that any receiver located outside the coverage region of its paired transmitter continues to receive its required service from its paired transmitter while still achieving tractable analysis for various performance metrics of interest, we adopted multiuser diversity via packet relaying. With this approach, any secondary nodes waiting to transmit can be used to sustain coverage between any typical active transmitter and receiver pair, while reducing their own waiting period in the process. We obtained tractable analysis for outage probability, spectral efficiency and throughput and showed the effect of handover rate over the network performance. The outcomes of the numerical results show that the proposed approach is capable of improving the overall network performance by improving coverage and throughput among network users in the cognitive radio networks. INDEX TERMSHandover cost, handover rate, multiuser diversity, outage probability, throughput.

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Spatiotemporal Characterization of Users’ Experience in Massive Cognitive Radio Networks

Cited by 12 publications

References 32 publications

A Multi-User Tasks Offloading Scheme for Integrated Edge-Fog-Cloud Computing Environments

A Multi-User Tasks Offloading Scheme for Integrated Edge-Fog-Cloud Computing Environments

Spatiotemporal D2D Small Cell Allocation and On-Demand Deployment for Microgrids

Outage and Throughput Analysis of Cognitive Users in Underlay Cognitive Radio Networks With Handover

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