resource allocation strategy
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2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Linhong Li ◽  
Kaifan Huang ◽  
Xiaofan Yang

With the prevalence of online social networks, the potential threat of misinformation has greatly enhanced. Therefore, it is significant to study how to effectively control the spread of misinformation. Publishing the truth to the public is the most effective approach to controlling the spread of misinformation. Knowledge popularization and expert education are two complementary ways to achieve that. It has been proven that if these two ways can be combined to speed up the release of the truth, the impact caused by the spread of misinformation will be dramatically reduced. However, how to reasonably allocate resources to these two ways so as to achieve a better result at a lower cost is still an open challenge. This paper provides a theoretical guidance for designing an effective collaborative resource allocation strategy. First, a novel individual-level misinformation spread model is proposed. It well characterizes the collaborative effect of the two truth-publishing ways on the containment of misinformation spread. On this basis, the expected cost of an arbitrary collaborative strategy is evaluated. Second, an optimal control problem is formulated to find effective strategies, with the expected cost as the performance index function and with the misinformation spread model as the constraint. Third, in order to solve the optimal control problem, an optimality system that specifies the necessary conditions of an optimal solution is derived. By solving the optimality system, a candidate optimal solution can be obtained. Finally, the effectiveness of the obtained candidate optimal solution is verified by a series of numerical experiments.


Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 256
Author(s):  
Artur Kierzkowski ◽  
Tomasz Kisiel

The purpose of this paper was to develop a simulation model to perform a sensitivity analysis of the energy consumption of an airport baggage handling system to a change in resource allocation strategy. This is a novel approach as this aspect has not been considered until now. This aspect, in turn is very important in terms of sustainability. The paper presents the detailed structure of the model and the data on which it operates. It is universal and can be the basis for analyzing any structure of the baggage handling system in the landside of any airport. An example analysis has shown that even up to 35% benefits can be gained by using the model. Three scenarios were analyzed in the model (dedicated check-in desks scenario, common desks scenario and mixed strategy scenario). However, the model is not limited to these strategies and any resource allocation is possible. The model is useful both for planning a new system as well as optimizing an existing system during its operation.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xuefei E ◽  
Zhonggui Ma ◽  
JunFeng Huang

In recent years, service isolation and service miniaturization have become very popular. The large services are dismantled into multiple low-cost and simple small services to improve the scalability and disaster tolerance of the entire services. A service network composed of unmanned aerial vehicles (UAVs) and MEC servers is proposed in this paper, which aims at decoupling multiple services of the SWIPT-MEC network. In this network, UAVs take charge of energy transmission and calculation task scheduling and MEC servers are focused on task calculation. To meet the resource requirements of the ground nodes (GNs) in the network, we designed a distributed iterative algorithm to solve the resource allocation decision problem of GNs and used the modified expert bat algorithm to complete the UAV’s trajectory planning in a two-dimensional space. The results show that the algorithm can formulate a more fair resource allocation strategy, and its performance is improved by 7% compared with the traditional bat algorithm. In addition, the algorithm in this paper can also adapt to changes in task length and has a certain degree of stability.


2021 ◽  
Author(s):  
Ying He ◽  
Yuhang Wang ◽  
Qiuzhen Lin ◽  
Jianqiang Li ◽  
Victor C. Leung

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