By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal serv...By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal servers,while the resource limita-tion of both computation and storage on satellites is the impor-tant factor affecting the maximum task completion time.In this paper,we study a delay-optimal multi-satellite collaborative computation offloading scheme that allows satellites to actively migrate tasks among themselves by employing the high-speed OISLs,such that tasks with long queuing delay will be served as quickly as possible by utilizing idle computation resources in the neighborhood.To satisfy the delay requirement of delay-sensi-tive task,we first propose a deadline-aware task scheduling scheme in which a priority model is constructed to sort the order of tasks being served based on its deadline,and then a delay-optimal collaborative offloading scheme is derived such that the tasks which cannot be completed locally can be migrated to other idle satellites.Simulation results demonstrate the effective-ness of our multi-satellite collaborative computation offloading strategy in reducing task complement time and improving resource utilization of the LEO satellite network.展开更多
The low earth orbit(LEO) satellite system provides a promising solution for the global coverage of Internet of Things(IoT) services.Confronted with the sporadic uplink transmission from massive IoT terminals, this wor...The low earth orbit(LEO) satellite system provides a promising solution for the global coverage of Internet of Things(IoT) services.Confronted with the sporadic uplink transmission from massive IoT terminals, this work investigates the grant-free access scheme and resource allocation algorithm for the beam-hopping(BH) based LEO satellite systems.To improve the packet success rate, the time slots are pre-allocated to each cell according to the number of terrestrial terminals and the probability of packet arrival.When the packets arrive, the terrestrial terminals perform contention-free or contention-based grant-free access with packet repetition in the time slots allocated to their cells.The analytical expression of the packet collision probability for the grant-free access scheme is derived to provide reference for the resource allocation.To reduce the computational complexity, a heuristic resource allocation algorithm is proposed to minimize the maximum cell packet collision probability in the system.Simulation results show that the proposed resource allocation scheme achieves lower packet collision probability and higher resource utilization ratio when compared with the uniform resource allocation scheme.展开更多
An integral method,combining support vector ma-chine (SVM) with remote-sensing analysis techniques,was ex-plored to monitor Hanoi’s dynamic change of land cover. The landsat thematic mapper (TM) image in 1993,the enh...An integral method,combining support vector ma-chine (SVM) with remote-sensing analysis techniques,was ex-plored to monitor Hanoi’s dynamic change of land cover. The landsat thematic mapper (TM) image in 1993,the enhanced the-matic mapper plus (ETM+) image in 2000,and the image with the charge-coupled device camera (CCD) on the China-Brazil earth resources satellite (CBERS) in 2008 were used. Six land-cover types,including built-up areas,woodland,cropland,sand,water body and unused land,were identified. The detected results showed visually the rapid urban expansion as well as land-cover change of Hanoi from 1993 to 2008. There were 12 637.54 hm2 cropland de-creased between 1993 and 2000,and 8 227.6 hm2 cropland de-creased between 2000 and 2008. Compared with cropland,wood-land firstly decreased and then increased,and the other types did not change significantly. The results indicate that CBERS dataset has the application potential in world resources researches.展开更多
基金This work was supported by the National Key Research and Development Program of China(2021YFB2900600)the National Natural Science Foundation of China(61971041+2 种基金62001027)the Beijing Natural Science Foundation(M22001)the Technological Innovation Program of Beijing Institute of Technology(2022CX01027).
文摘By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal servers,while the resource limita-tion of both computation and storage on satellites is the impor-tant factor affecting the maximum task completion time.In this paper,we study a delay-optimal multi-satellite collaborative computation offloading scheme that allows satellites to actively migrate tasks among themselves by employing the high-speed OISLs,such that tasks with long queuing delay will be served as quickly as possible by utilizing idle computation resources in the neighborhood.To satisfy the delay requirement of delay-sensi-tive task,we first propose a deadline-aware task scheduling scheme in which a priority model is constructed to sort the order of tasks being served based on its deadline,and then a delay-optimal collaborative offloading scheme is derived such that the tasks which cannot be completed locally can be migrated to other idle satellites.Simulation results demonstrate the effective-ness of our multi-satellite collaborative computation offloading strategy in reducing task complement time and improving resource utilization of the LEO satellite network.
基金Supported by the Science and Technology Innovation Action Plan of Shanghai (No. 21DZ2200200)the Science and Technology Cooperation Funding of Chengdu and CASthe National Key Research and Development Program of China (No. 2019YFB1803101)。
文摘The low earth orbit(LEO) satellite system provides a promising solution for the global coverage of Internet of Things(IoT) services.Confronted with the sporadic uplink transmission from massive IoT terminals, this work investigates the grant-free access scheme and resource allocation algorithm for the beam-hopping(BH) based LEO satellite systems.To improve the packet success rate, the time slots are pre-allocated to each cell according to the number of terrestrial terminals and the probability of packet arrival.When the packets arrive, the terrestrial terminals perform contention-free or contention-based grant-free access with packet repetition in the time slots allocated to their cells.The analytical expression of the packet collision probability for the grant-free access scheme is derived to provide reference for the resource allocation.To reduce the computational complexity, a heuristic resource allocation algorithm is proposed to minimize the maximum cell packet collision probability in the system.Simulation results show that the proposed resource allocation scheme achieves lower packet collision probability and higher resource utilization ratio when compared with the uniform resource allocation scheme.
基金Supported by the National Natural Science Foundation of China (70873117)
文摘An integral method,combining support vector ma-chine (SVM) with remote-sensing analysis techniques,was ex-plored to monitor Hanoi’s dynamic change of land cover. The landsat thematic mapper (TM) image in 1993,the enhanced the-matic mapper plus (ETM+) image in 2000,and the image with the charge-coupled device camera (CCD) on the China-Brazil earth resources satellite (CBERS) in 2008 were used. Six land-cover types,including built-up areas,woodland,cropland,sand,water body and unused land,were identified. The detected results showed visually the rapid urban expansion as well as land-cover change of Hanoi from 1993 to 2008. There were 12 637.54 hm2 cropland de-creased between 1993 and 2000,and 8 227.6 hm2 cropland de-creased between 2000 and 2008. Compared with cropland,wood-land firstly decreased and then increased,and the other types did not change significantly. The results indicate that CBERS dataset has the application potential in world resources researches.
