Joint Optimization of Sensors Association and UAVs Placement in IoT Applications With Practical Network Constraints

Ahmed, Ashfaq; Naeem, Muhammad; Al-Dweik, Arafat

doi:10.1109/access.2021.3049360

Cited by 18 publications

(15 citation statements)

References 59 publications

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“…The considered use case comprises of a scenario in which multiple UAVs start from different positions but fly to the same destination on a 2-D plane subject to zone avoidance constraints. In [29], the authors have utilized an algorithm to investigate the maximization of computation efficiency problem in the multi-UAV assisted edge computing platform by jointly optimizing user association, computation and communication resource allocation along with trajectory scheduling of UAVs. The algorithm achieved better computation efficiency than the baseline solutions.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient UAV-Based Service Offloading Over Cloud-Fog Architectures

et al. 2022

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Unmanned Aerial Vehicles (UAVs) are poised to play a central role in revolutionizing future services offered by the envisioned smart cities, thanks to their agility, flexibility, and cost-efficiency. UAVs are being widely deployed in different verticals including surveillance, search and rescue missions, delivery of items, and as an infrastructure for aerial communications in future wireless networks. UAVs can be used to survey target locations, collect raw data from the ground (i.e., video streams), generate computing task(s) and offload it to the available servers for processing. In this work, we formulate a multi-objective optimization framework for both the network resource allocation and the UAV trajectory planning problem using Mixed Integer Linear Programming (MILP) optimization model. In consideration of the different stake holders that may exist in a Cloud-Fog environment, we minimize the sum of a weighted objective function, which allows network operators to tune the weights to emphasize/de-emphasize different cost functions such as the end-toend network power consumption (EENPC), processing power consumption (PPC), UAV's total flight distance (UAVTFD), and UAV's total power consumption (UAVTPC). Our optimization models and results enable the optimum offloading decisions to be made under different constraints relating to EENPC, PPC, UAVTFD and UAVTPC which we explore in detail. For example, when the UAV's propulsion efficiency (UPE) is at its worst (10% considered), offloading via the macro base station is the best choice and a maximum power saving of 34% can be achieved. Extensive studies on the UAV's coverage path planning (CPP) and computation offloading have been conducted, but none has tackled the issue in a practical Cloud-Fog architecture in which all the elements of the access, metro and core layers are considered when evaluating the service offloading in a distributed architecture like the Cloud-Fog.

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Section: Related Workmentioning

confidence: 99%

Energy Efficient UAV-Based Service Offloading Over Cloud-Fog Architectures

et al. 2022

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“…T He integration of Internet of Things (IoT) in various applications has been growing vastly in the last decade, which triggered the introduction of more specific applications such as Internet of Drones (IoD) [1]- [3] and Internet of Vehicles (IoV) [4]- [7], or even more advanced configurations that include both IoD and IoV as shown in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

“…For example, vehicles in IoV environment should perform vehicle-to-vehicle (V2V) and vehicle to infrastructure (V2I) connectivity to enable vehicles make certain critical decisions [8]. IoD applications have similar requirements because the drones typically have to collect and relay location-specific critical information [1]- [3]. Therefore, the received data should be verified for correctness before being used to make decisions.…”

Section: Introductionmentioning

confidence: 99%

A Power and Spectrum Efficient Uplink Transmission Scheme for QoS-Constrained IoT Networks

Yahya¹,

Al-Dweik²,

Iraqi³

et al. 2021

Preprint

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<div>Abstract—Non-orthogonal multiplexing (NOM) is a novel superposition coding inspired scheme that has been recently proposed for improving the power, spectrum efficiency and delay of wireless links with packet error rate (PER) constraints. Despite its efficiency, restricting the number of multiplexed packets to two limits the throughput improvement to 100%. Therefore, this work presents a novel NOM design with unlimited number of multiplexed packets by manipulating the repeated transmissions in automatic repeat request (ARQ) to enhance the power and spectrum efficiency by multiplexing new and repeated packets while taking into account the channel conditions and varying the power per packet in different transmissions. The proposed scheme employs an efficient heuristic algorithm to perform the power assignment and multiplexing decisions. Moreover, the complexity of the proposed NOM can be controlled by enforcing a limit on the maximum number of multiplexed packets per transmission, making it suitable for different types of Internet of Things (IoT) nodes with various computational capabilities. The obtained results demonstrate the effectiveness of proposed scheme, which offers up to 200% spectral efficiency improvement at moderate signal to noise ratios (SNRs), and up to 700% at high SNRs. Furthermore, the new scheme can reduce the transmission power consumption by up to 6 dB in the high SNR region.</div>

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“…For example, vehicles in IoV environment should perform vehicle-tovehicle (V2V) and vehicle to infrastructure (V2I) connectivity to enable vehicles make certain critical decisions [13]. IoD applications have similar requirements because the drones typically have to collect and relay location-specific critical information [1]- [4]. Therefore, the received data should be verified for correctness before being used to make decisions.…”

mentioning

confidence: 99%

A Power and Spectrum Efficient Uplink Transmission Scheme for QoS-Constrained IoT Networks

Yahya

Al-Dweik

Iraqi

et al. 2022

IEEE Internet Things J.

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Non-orthogonal multiplexing (NOM) is a novel superposition coding scheme that has been recently proposed to improve the throughput of wireless systems. However, restricting the number of multiplexed packets to two limits the throughput improvement of NOM to 100% in best case scenarios. Therefore, this work presents a generalized NOM (GNOM) design with unlimited number of multiplexed packets. In the multiplexing process, new and retransmitted packets due to automatic repeat request are combined while considering the impact of channel conditions on the power assigned per packet. The proposed GNOM employs an efficient heuristic algorithm to perform the power assignment and multiplexing decisions. Moreover, the complexity can be controlled by enforcing a limit on the maximum number of multiplexed packets per transmission, making it suitable for Internet of Things nodes with diverse computational capabilities and quality of service requirements. The obtained results demonstrate the effectiveness of proposed scheme, which offers up to 200% throughput improvement at moderate signal to noise ratios (SNRs), and up to 700% at high SNRs. Furthermore, the new scheme can reduce the transmission power consumption by up to 6 dB in the high SNR region.Index Terms-Internet of Things (IoT), Internet of Vehicles (IoV), Internet of Drones (IoD), automatic repeat request (ARQ), vehicle to infrastructure (V2I), vehicle-to-vehicle (V2V), nonorthogonal multiple access (NOMA), non-orthogonal multiplexing (NOM), throughput. I. INTRODUCTIONT He integration of Internet of Things (IoT) in various applications has been growing vastly in the last decade, which triggered the introduction of more specific applications such as Internet of Drones (IoD) [1]-[4] and Internet of Vehicles (IoV) [5]-[9], or even more advanced configurations that include both IoD and IoV. Human and machine-centric IoT applications include transportation, smart cities, healthcare, agriculture, environment, retail, and smart homes. These Hamad Yahya and Emad Alsusa are with the

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Joint Optimization of Sensors Association and UAVs Placement in IoT Applications With Practical Network Constraints

Cited by 18 publications

References 59 publications

Energy Efficient UAV-Based Service Offloading Over Cloud-Fog Architectures

Energy Efficient UAV-Based Service Offloading Over Cloud-Fog Architectures

A Power and Spectrum Efficient Uplink Transmission Scheme for QoS-Constrained IoT Networks

A Power and Spectrum Efficient Uplink Transmission Scheme for QoS-Constrained IoT Networks

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