Unmanned Aerial Vehicle (UAV) into Mobile Edge Computing (MEC) systems can effectively expand their flexibility and coverage. The current research trend in UAV-assisted MEC is mainly focused on optimizing flight control and minimizing energy consumption. However, there is a lack of research on task scheduling in UAV-assisted MEC scenarios. This paper proposes a two-stage task scheduling method that minimizes the task processing cost while optimizing task execution order to reduce the execution time of tasks. The results of the study show that the proposed algorithm outperforms other baseline methods in terms of completing all tasks with the shortest execution time. This further validates the efficiency of the proposed algorithm and its potential for improving the system efficiency of UAV-assisted MEC.
Resource scheduling technology as an important means to achieve the optimal allocation of SAGIN resources, plays a vital role in Earth observation, emergency communications and other fields, through the in-depth understanding and analysis of the research status of the integrated network resource scheduling field, the current resource scheduling technology is not yet perfect, it is difficult to meet the multi-satellite collaboration, network topology real-time changes, massive users as the characteristics of the scheduling needs. Starting from the research point of multi-dimensional resources, this paper considers the synergy between resources, proposes a multi-dimensional resource vector model, and on this basis proposes a multi-dimensional resource collaborative optimization scheduling algorithm to achieve unified scheduling from the global perspective. In the simulation experiment, it is proved that the indicators such as the number of task completions, total tasks revenues, average revenue and scheduling decision-making time can be effectively improved, among which the number of task completions is increased by 10%-30%, the total tasks revenue is increased by 30%-60%, and the scheduling decision-making time is saved by about 30%.
The space-ground integrated network (SGIN) is a future communication network that integrates different dimensions networks to form a new network application scenario based on the terrestrial network and extended by satellite network. SGIN can cover natural spaces such as space, ground, ocean, etc., and can provide users with more diverse network services. As a new type of network, SGIN also faces the problem of network ossification in traditional network. In traditional network, network virtualization can overcome this problem effectively. However, most of the current researches are based on terrestrial network models or satellite network models, which cannot adapt to the dynamic and heterogeneous nature of SGIN. In order to meet the demand of SGIN for network virtualization, we establish a SGIN time evolution graph model and propose a virtual network embedding algorithm (CD-VNE). The algorithm selects the network sub community with the most abundant physical resources through community detection technology, which can reduce the consumption of link bandwidth resources and the risk of satellite link failure. The simulation results show that CD-VNE can increase the Revenue/Cost ratio and acceptance ratio.
Space-Air-Ground Integrated network (SAGIN) that integrates satellite system, air network and ground communication network has attracted extensive research interests in recent years, for its high value to practical services and its wide applications in communication. Nevertheless, it also faces many unprecedented challenges due to its heterogeneity, selforganization, time variability and other characteristics. In order to solve the problems of unstable inter-domain neighbor relationship, frequent routing update and slow routing convergence in space-air-ground integrated network, a link fault recovery method of space-air-ground integrated network based on time sequence link weight graph is proposed in this paper. This method is based on the infrastructure of software-defined network, and introduces time-varying characteristics, designs a dynamic model of link weight change, and proposes a link fault recovery method. The simulation results show that by considering link resources and node resources, compared with the link detection and recovery scheme of softwaredefined satellite network, this method can effectively solve the problem that it is unable to build an effective recovery path because of the unstable inter domain relationship in the space-air-ground integrated network, and can effectively find a recovery path with the lower path cost, low end-to-end delay and high reliability.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.