An Efficient Mobile Cloud Service Model or Tactical Edge

Du, Bo; Shan, Nanliang; Zhang, Sha

doi:10.1007/978-3-030-29035-1_41

Cited by 2 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Simulation results show that DAPWTS outperforms the existing baseline approach by 30% in terms of energy consumption, deadline, and application failure in the system. Du et al [19] proposed an efficient tactical edge mobile cloud service model to solve the problems of military operations, limited device access, lack of edge tactical mobility, and edge information fusion processing capabilities in the tactical edge network environment. The model can provide flexible tactical edge information exchange and information processing capabilities.…”

Section: Related Workmentioning

confidence: 99%

A Dynamic Task Scheduling Algorithm for Airborne Device Clouds

Deng,

Zhai

2024

International Journal of Aerospace Engineering

View full text Add to dashboard Cite

The rapid development of mobile Internet has promoted the rapid rise of cloud computing technology. Mobile terminal devices have greatly expanded the service capacity of mobile terminals by migrating complex computing tasks to run in the cloud. However, in the process of data exchange between mobile terminals and cloud computing centers, on the one hand, it consumes the limited power of mobile terminals, and on the other hand, it results in longer communication time, which negatively affects user QoE. Mobile cloud can effectively improve user QoE by shortening the data transmission distance, reducing the power consumption, and shortening the communication time at the same time. In this paper, we utilize the property that genetic algorithm can perform global search seeking the global optimal solution and construct a dynamic task scheduling model by combining the device-cloud link. The task scheduling model based on genetic algorithm and random scheduling algorithm is compared through comparison experiments, which show that the assignment time of the task scheduling model based on genetic algorithm is shortened by 11.82% to 48.51% and the energy consumption is reduced by 22.28% to 47.52% under different load conditions.

show abstract

Section: Related Workmentioning

confidence: 99%

A Dynamic Task Scheduling Algorithm for Airborne Device Clouds

Deng,

Zhai

2024

International Journal of Aerospace Engineering

View full text Add to dashboard Cite

show abstract

“…There are also hybrid solutions 20 of autonomous intelligent combat systems for C2, including manned and unmanned systems. Solutions for modelling the tactical edge 21,22 for information processing and decision making in military operations have also drawn interest. Task scheduling in fog computing is an active area of research, with solutions that focus on parameters 23 such as response time, delay, latency, cost and load balancing.…”

Section: Proposed Solutionmentioning

confidence: 99%

Task Scheduling in Fog Node within the Tactical Cloud

Nair

Bhanu

2022

Def. Sc. J.

View full text Add to dashboard Cite

Fog computing architecture competent to support the mission-oriented network-centric warfare provides the framework for a tactical cloud in this work. The tactical cloud becomes situation-aware of the war from the information relayed by fog nodes (FNs) on the battlefield. This work aims to sustain the network of FNs by maintaining the operational efficiency of the FNs on the battlefield at the tactical edge. The proposed solution monitors and predicts the likely overloading of an FN using the long short-term memory model through a buddy FN at the fog server (FS). This paper also proposes randomised task scheduling (RTS) algorithm to avert the likely overloading of an FN by pre-empting tasks from the FN and scheduling them to another FN. The experimental results demonstrate that RTS with linear complexity has a schedulability measure 8% - 26% higher than that of other base scheduling algorithms. The results show that the LSTM model has low mean absolute error compared to other time-series forecasting models.

show abstract

An Efficient Mobile Cloud Service Model or Tactical Edge

Cited by 2 publications

References 3 publications

A Dynamic Task Scheduling Algorithm for Airborne Device Clouds

A Dynamic Task Scheduling Algorithm for Airborne Device Clouds

Task Scheduling in Fog Node within the Tactical Cloud

Contact Info

Product

Resources

About