Timeliness Analysis of Service-Driven Collaborative Mobile Edge Computing in UAV Swarm

Chen, Jingran; Zhang, Qixun; Feng, Zhiyong

doi:10.1109/gcwkshps45667.2019.9024534

Cited by 6 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The analyzed papers that are devoted to UAV applications for smart cities can be subdivided into three groups: the papers related to general issues of UAV applications including different city services [1,2,[6][7][8][9][13][14][15][16][17][18][19][20][21][22][23][24], the papers related to dependability (reliability) issues of UAV applications [25][26][27][28][29][30][31][32][33], and the papers related to issues on queueing theory utilization for describing UAV functioning [34][35][36][37][38][39][40][41][42].…”

Section: State-of-the-artmentioning

confidence: 99%

“…This mechanism was modeled via the multi-class queueing theory and its implementation allowed efficiently utilizing the network bandwidth resource. To support the computation-intensive and latency-critical services for a UAV swarm, the enhanced collaborative computing model based on queueing theory was developed in [35]. The model allowed achieving the closed-form solution of the decision threshold.…”

Section: State-of-the-artmentioning

confidence: 99%

See 1 more Smart Citation

UAV Fleet as a Dependable Service for Smart Cities: Model-Based Assessment and Application

et al. 2022

View full text Add to dashboard Cite

The paper suggests a model-based approach to assessment and choice of parameters of unmanned aerial vehicle (UAV) fleets applied as one of the main services for Smart Cities and recommendations to assure their dependability. The principles of building and modeling a UAV Fleet as a Dependable Service (UAVFaaDS) for Smart Cities are formulated. Dependability issues for UAVFaaDS including a taxonomy of UAVF failures caused by equipment faults and attacks on assets were specified. The main results cover methodology, classification of UAVFaaDS models as models of queuing systems, and a set of queueing theory-based models for assessment of UAVFaaDS performance, and availability allowing for analysis and choice of fleet parameters. The efficiency of UAVFaaDS is assessed by the probability of successful delivery of services. The proposed modeling base and algorithms provide a choice of appropriate models for analysis and synthesis of UAVFaaDS, grounding of parameters of UAV fleets considering operation modes, and maintenance policy. The application of the developed models and algorithms during the synthesis of UAVFaaDS allows choosing the appropriate parameters of the fleet and ensuring the dependability of services, as well as service of orders with a probability of 0.9–0.99 depending on the requirements. Two cases of UAVFaaDS application for delivery of medicines in normal and emergence modes, models’ development, and recommendations for their utilization are discussed.

show abstract

Section: State-of-the-artmentioning

confidence: 99%

Section: State-of-the-artmentioning

confidence: 99%

UAV Fleet as a Dependable Service for Smart Cities: Model-Based Assessment and Application

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The research and development on UAV swarm-enabled edge computing are still in its infancy, and there have been very limited related studies [4], [6], [7]. The authors in [4] studied the response delay minimization issue for a swarm of three-dimensional distributed UAVs through joint optimization of communications and computation resources.…”

Section: Introductionmentioning

confidence: 99%

“…A service-driven collaborative MEC model was further investigated in [7] to support computation-intensive and delay-critical services in UAV swarm. To provide a comprehensive understanding and promote the in-depth research, in this paper, we provide an overview on UAV swarm-enabled edge computing.…”

Section: Introductionmentioning

confidence: 99%

Unmanned Aerial Vehicle Swarm-Enabled Edge Computing: Potentials, Promising Technologies, and Challenges

Wu¹,

Zhou²,

Wang³

et al. 2022

Preprint

View full text Add to dashboard Cite

Unmanned aerial vehicle (UAV) swarm enabled edge computing is envisioned to be promising in the sixth generation wireless communication networks due to their wide application sensories and flexible deployment. However, most of the existing works focus on edge computing enabled by a single or a small scale UAVs, which are very different from UAV swarm-enabled edge computing. In order to facilitate the practical applications of UAV swarm-enabled edge computing, the state of the art research

show abstract

Swarm of Unmanned Aerial Vehicles as a Multi-State Queueing System with Non-Controlled and Controlled Degradation

Kliushnikov

Fesenko

Fedorenro

et al. 2022

2022 12th International Conference on Dependable Systems, Services and Technologies (DESSERT)

View full text Add to dashboard Cite

Timeliness Analysis of Service-Driven Collaborative Mobile Edge Computing in UAV Swarm

Cited by 6 publications

References 13 publications

UAV Fleet as a Dependable Service for Smart Cities: Model-Based Assessment and Application

UAV Fleet as a Dependable Service for Smart Cities: Model-Based Assessment and Application

Unmanned Aerial Vehicle Swarm-Enabled Edge Computing: Potentials, Promising Technologies, and Challenges

Swarm of Unmanned Aerial Vehicles as a Multi-State Queueing System with Non-Controlled and Controlled Degradation

Contact Info

Product

Resources

About