SDSense: An Agile and Flexible SDN-Based Framework for Wireless Sensor Networks

Haque, Israat; Nurujjaman, Mohammad; Harms, Janelle; Abu-Ghazaleh, Nael

doi:10.1109/tvt.2018.2888622

Cited by 33 publications

(15 citation statements)

References 35 publications

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“…Different schemes and techniques have been proposed in the literature to enhance the flexibility and agility of future wireless networks [128]- [130]. From these proposals, novel technology has become a promising alternative for networks, which is called SDN [131].…”

Section: B Software-defined Network (Sdn)mentioning

confidence: 99%

Softwarization of UAV Networks: A Survey of Applications and Future Trends

et al. 2020

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Unmanned Aerial Vehicles (UAVs) have become increasingly important in assisting 5G and beyond 5G (B5G) mobile networks. Indeed, UAVs have all the potentials to both satisfy the ever-increasing mobile data demands of such mobile networks and provide ubiquitous connectivity to different kinds of wireless devices. However, the UAV assistance paradigm faces a set of crucial issues and challenges. For example, the network management of current UAV-assisted systems is time consuming, complicated, and carried out manually, thus causing a multitude of interoperability issues. To efficiently address all these issues, Software-Defined Network (SDN) and Network Function Virtualization (NFV) are two promising technologies to efficiently manage and improve the UAV assistance for the next generation of mobile networks. In the literature, no clear guidelines are describing the different use cases of SDN and NFV in the context of UAV assistance to terrestrial networks, including mobile networks. Motivated by this fact, in this survey, we guide the reader through a comprehensive discussion of the main characteristics of SDN and NFV technologies. Moreover, we provide a thorough analysis of the different classifications, use cases, and challenges related to UAV-assisted systems. We then discuss SDN/NFV-enabled UAV-assisted systems, along with several case studies and issues, such as the involvement of UAVs in cellular communications, monitoring, and routing, to name a few. We furthermore present a set of open research challenges, high-level insights, and future research directions related to UAV-assisted systems.

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Section: B Software-defined Network (Sdn)mentioning

confidence: 99%

Softwarization of UAV Networks: A Survey of Applications and Future Trends

et al. 2020

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“…Details are summarized as follows. A software defined WSN architecture was brought up in [20], dividing the control module into fast changing module and slow changing module. It implemented centralized resource scheduling to reduce congestion and achieve fair allocation of user.…”

Section: Related Workmentioning

confidence: 99%

“…7: end for 8: Replace C2-C3 with (20) to update P1. 9: while optimalitytolerance > θ | C7 is not satisfied do…”

Section: Dynamic Resource Allocation Strategymentioning

confidence: 99%

Resource Allocation in Wireless Powered Virtualized Sensor Networks

Zhong

2020

IEEE Access

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As an important technology for Internet of Things, wireless sensor networks have been receiving widespread attention in recent years. Traditional wireless sensor network deploys resources for specific applications, which causes the problem of low resource utilization. Additionally, the energy consumption brought by the diversification of application requirements has also raised the burden on sensor nodes. Therefore, based on the introduction of wireless energy transfer technology, this paper proposes a resource allocation strategy for virtualized wireless sensor networks. Specifically, physical resources are pooled by the the wireless sensor network service provider. Then, virtual sensor networks are built through network slicing technology to provide one-to-one services based on the application requirements and the current status of the physical sensor nodes. Furthermore, in order to minimize the overall network energy consumption, a system-friendly resource allocation strategy is proposed to optimize the jointly configurations of sensing frequency, time slot and transmission power. Simulation results validate that the proposed strategy can not only effectively save the network energy, but also meet the diverse personalized needs of applications.

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“…In the literature, related works about virtualized WSNs usually focus on network metric optimization, such as traffic throughput, energy efficiency, etc. In [ 12 ], an SDSense architecture was proposed to decompose the network functions into slow and fast changing components. Under the SDSense architecture, all the parameters of the sensors nodes could be reconfigured, such that the throughput of the considered WSN was improved.…”

Section: Related Workmentioning

confidence: 99%

“…The authors therein employed wireless network virtualization to enhance the diversity and the flexibility of the service operation and the system management, and proposed a robust energy-efficient resource allocation scheme to outage probability requirements of controllers and actuators. Works [ 12 , 13 , 14 , 15 , 16 ] have provided insightful results on performance optimization in virtualized WSN. However, latency analysis is absent in those works.…”

Section: Related Workmentioning

confidence: 99%

Stochastic Latency Guarantee in Wireless Powered Virtualized Sensor Networks

Wang

Zhong

et al. 2020

Sensors

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How to guarantee the data rate and latency requirement for an application with limited energy is an open issue in wireless virtualized sensor networks. In this paper, we integrate the wireless energy transfer technology into the wireless virtualized sensor network and focus on the stochastic performance guarantee. Firstly, a joint task and resource allocation optimization problem are formulated. In order to characterize the stochastic latency of data transmission, effective capacity theory is resorted to study the relationship between network latency violation probability and the transmission capability of each node. The performance under the FDMA mode and that under the TDMA mode are first proved to be identical. We then propose a bisection search approach to ascertain the optimal task allocation with the objective to minimize the application latency violation probability. Furthermore, a one-dimensional searching scheme is proposed to find out the optimal energy harvesting time in each time block. The effectiveness of the proposed scheme is finally validated by extensive numerical simulations. Particularly, the proposed scheme is able to lower the latency violation probability by 11.6 times and 4600 times while comparing with the proportional task allocation scheme and the equal task allocation scheme, respectively.

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SDSense: An Agile and Flexible SDN-Based Framework for Wireless Sensor Networks

Cited by 33 publications

References 35 publications

Softwarization of UAV Networks: A Survey of Applications and Future Trends

Softwarization of UAV Networks: A Survey of Applications and Future Trends

Resource Allocation in Wireless Powered Virtualized Sensor Networks

Stochastic Latency Guarantee in Wireless Powered Virtualized Sensor Networks

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