Joint flight scheduling and task allocation for secure data collection in UAV-aided IoTs

Wang, Zuyan; Tao, Jun; Gao, Yang; Xu, Yifan; Sun, Weice; Gao, Yu; Li, Wenqiang

doi:10.1016/j.comnet.2022.108849

Cited by 8 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Drone recharge operations plan trajectories according to locations and comparative operability of charging stations. A “secure data collection problem” is considered by Wang et al 29 where a “Cost‐Benefit Greedy algorithm” is proposed to track the eavesdroppers that may “intercept data uploading of legitimate nodes.”…”

Section: Related Workmentioning

confidence: 99%

UAV‐IoT collaboration: Energy and time‐saving task scheduling scheme

Banerjee

Gupta

et al. 2023

Int J Communication

View full text Add to dashboard Cite

SummaryUAVs are capable of providing significant potential to IoT devices through sensors, cameras, GPS systems, and so forth. Therefore, the smart UAV‐IoT collaborative system has become a current hot research topic. However, other concerns require in‐depth investigation and study, such as resource allocation, security, privacy preservation, trajectory optimization, intelligent decision‐making, energy harvesting, and so forth. Here, we suggest a task‐scheduling method that splits IoT devices into distinct clusters based on physical proximity and saves time and energy. Cluster heads can apply an auto regressive moving average (ARMA) model to predict intelligently the timestamp of the arrival of the next task and associated estimated payments. Based on the overall expected payment, a cluster head can smartly advise the UAV about its time of next arrival. According to the findings of the simulation, the proposed ETTS algorithm significantly outperforms Task TSIE and TDMA‐WS in terms of energy use (67%) and delays (36%).

show abstract

Section: Related Workmentioning

confidence: 99%

UAV‐IoT collaboration: Energy and time‐saving task scheduling scheme

Banerjee

Gupta

et al. 2023

Int J Communication

View full text Add to dashboard Cite

show abstract

“…To achieve these services and applications, it is the first step to build the connection between tasks (e.g., traffic monitoring tasks and travel recommendation tasks) and workers [11], [12]. Task allocation has become a promising paradigm to connect users [13], [14] since it can allocate tasks from requesters to suitable workers based on their task interests.…”

Section: Introductionmentioning

confidence: 99%

Towards Efficient and Privacy-Preserving Versatile Task Allocation for Internet of Vehicles

Zhao

Chen

Zhang

et al. 2022

IEEE Open J. Comput. Soc.

View full text Add to dashboard Cite

Nowadays, task allocation has attracted increasing attention in the Internet of Vehicles. To efficiently allocate tasks to suitable workers, users usually need to publish their task interests to the service provider, which brings a serious threat to users' privacy. Existing task allocation schemes either cannot comprehensively preserve user privacy (i.e., requester privacy and worker privacy) or introduce tremendous resource overhead. In this paper, we propose an efficient and privacy-preserving versatile task allocation scheme (PPVTA) for the Internet of vehicles. Specifically, we utilize the randomizable matrix multiplication technique to preserve requester privacy and worker privacy. Then, the polynomial fitting technique is leveraged to enrich the randomizable matrix multiplication to support versatile task allocation functions, such as threshold-based task allocation (PPVTA-I), conjunctive task allocation (PPVTA-II), and task allocation with bilateral access control (PPVTA-III). We formally analyze the security of our constructions to prove the security under the chosen-plain attack. Based on a prototype, experimental results demonstrate that our constructions have acceptable efficiency in practice.

show abstract

Enhancing air pollution mapping with autonomous UAV networks for extended coverage and consistency

Bakirci

2024

Atmospheric Research

View full text Add to dashboard Cite

Joint flight scheduling and task allocation for secure data collection in UAV-aided IoTs

Cited by 8 publications

References 35 publications

UAV‐IoT collaboration: Energy and time‐saving task scheduling scheme

UAV‐IoT collaboration: Energy and time‐saving task scheduling scheme

Towards Efficient and Privacy-Preserving Versatile Task Allocation for Internet of Vehicles

Enhancing air pollution mapping with autonomous UAV networks for extended coverage and consistency

Contact Info

Product

Resources

About