Satellite Edge Computing for the Internet of Things in Aerospace

Wang, Yuxuan; Yang, Jun; Guo, Xiaojie; Qu, Zhi

doi:10.3390/s19204375

Cited by 65 publications

(49 citation statements)

References 28 publications

(32 reference statements)

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“…Intelligent satellites are suitable as space edge computing nodes [43][44] that reduces satellite to computing platform transmission latency. Wang et al [19] describes capabilities enabling the use of satellites as edge nodes. The intelligent satellite is used in edge computing to realize low latency data processing in satellite internet of things.…”

Section: Existing and Related Workmentioning

confidence: 99%

“…The shift to space of edge nodes reduces the long term reliance on earth's resources. However, this perspective is not considered in [19].…”

Section: Existing and Related Workmentioning

confidence: 99%

“…Siting data centres in space can reduce the water foot print [16][17][18][19]. The approach in [16,18] utilizes small satellites to realize space based data centres.…”

Section: Introductionmentioning

confidence: 99%

“…It is also challenging to upgrade the computing payload in small satellites being used as data centres. Outer space also hosts satellites, and spaceships [19][20][21]. Spaceships such as space habitats can support humans (making it easy to address faults) and host a larger computing payload.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Space Habitat Data Centers – For Future Computing

Periola¹,

Alonge²,

Ogudo³

2020

Preprint

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Data from sensor bearing satellites requires processing aboard terrestrial data centers that use water for cooling at the expense of high data transfer latency. The reliance of terrestrial data centers on water increases their water footprint and limits the availability of water for other applications. Therefore, data centers with low data transfer latency and reduced reliance on earth’s water resources are required. This paper proposes space habitat data centers (SHDCs) with low latency data transfer and that use asteroid water to address these challenges. The paper investigates the feasibility of accessing asteroid water and the reduction in computing platform access latency. Results show that the mean asteroid water access period is 319.39 days. The use of SHDCs instead of non-space computing platforms reduces access latency and increases accessible computing resources by (11.9% – 33.6%) and (46.7% – 77%) on average respectively.

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Section: Existing and Related Workmentioning

confidence: 99%

“…The shift to space of edge nodes reduces the long term reliance on earth's resources. However, this perspective is not considered in [19].…”

Section: Existing and Related Workmentioning

confidence: 99%

“…Siting data centres in space can reduce the water foot print [16][17][18][19]. The approach in [16,18] utilizes small satellites to realize space based data centres.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Space Habitat Data Centers – For Future Computing

Periola¹,

Alonge²,

Ogudo³

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Emerging heterogeneous cloud computing as a special type of the parallel computing manner is flexible to assign different forms of computing tasks according to algorithm structural characteristics. The heterogeneous computing structure based on CPU + FPGA is mainly used to solve the main problems of high performance, high efficiency, and big data processing, which show the great potential of accelerating the SKA's algorithm [22], as FPGA is good at parallel designing and combines the advantages of parallel processing ability and low energy consumption [23]. Therefore, this paper focuses on the faceting imaging algorithm accelerator implemented on the FPGA to realize the key phases computing in the SKA's data processing.…”

Section: Introductionmentioning

confidence: 99%

Accelerating Faceting Wide-Field Imaging Algorithm with FPGA for SKA Radio Telescope as a Vast Sensor Array

Song

Zhu

Nan

et al. 2020

Sensors

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The SKA (Square Kilometer Array) radio telescope will become the most sensitive telescope by correlating a huge number of antenna nodes to form a vast array of sensors in a region over one hundred kilometers. Faceting, the wide-field imaging algorithm, is a novel approach towards solving image construction from sensing data where earth surface curves cannot be ignored. However, the traditional processor of cloud computing, even if the most sophisticated supercomputer is used, cannot meet the extremely high computation performance requirement. In this paper, we propose the design and implementation of high-efficiency FPGA (Field Programmable Gate Array) -based hardware acceleration of the key algorithm, faceting in SKA by focusing on phase rotation and gridding, which are the most time-consuming phases in the faceting algorithm. Through the analysis of algorithm behavior and bottleneck, we design and optimize the memory architecture and computing logic of the FPGA-based accelerator. The simulation and tests on FPGA are done to confirm the acceleration result of our design and it is shown that the acceleration performance we achieved on phase rotation is 20× the result of the previous work. We then further designed and optimized an efficient microstructure of loop unrolling and pipeline for the gridding accelerator, and the designed system simulation was done to confirm the performance of our structure. The result shows that the acceleration ratio is 5.48 compared to the result tested on software in gridding parts. Hence, our approach enables efficient acceleration of the faceting algorithm on FPGAs with high performance to meet the computational constraints of SKA as a representative vast sensor array.

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Resource scheduling in mobile edge computing using improved ant colony algorithm for space information network

Wang

et al. 2022

Satell Commun Network

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Summary With the development of space information network (SIN), new network applications are emerging. Satellites are not only used for storage and transmission but also gradually used for calculation and analysis, so the demand for resources is increasing. But satellite resources are still limited. Mobile edge computing (MEC) is considered an effective technique to reduce the pressure on satellite resources. To solve the problem of task execution delay caused by limited satellite resources, we designed Space Mobile Edge Computing Network (SMECN) architecture. According to this architecture, we propose a resource scheduling method. First, we decompose the user tasks in SMECN, so that the tasks can be assigned to different servers. An improved ant colony resource scheduling algorithm for SMECN is proposed. The heuristic factors and pheromones of the ant colony algorithm are improved through time and resource constraints, and the roulette algorithm is applied to route selection to avoid falling into the local optimum. We propose a dynamic scheduling algorithm to improve the contract network protocol to cope with the dynamic changes of the SIN and dynamically adjust the task execution to improve the service capability of the SIN. The simulation results show that when the number of tasks reaches 200, the algorithm proposed in this paper takes 17.52% less execution time than the Min‐Min algorithm, uses 9.58% less resources than the PSO algorithm, and achieves a resource allocation rate of 91.65%. Finally, introducing dynamic scheduling algorithms can effectively reduce task execution time and improve task availability.

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Satellite Edge Computing for the Internet of Things in Aerospace

Cited by 65 publications

References 28 publications

Space Habitat Data Centers – For Future Computing

Space Habitat Data Centers – For Future Computing

Accelerating Faceting Wide-Field Imaging Algorithm with FPGA for SKA Radio Telescope as a Vast Sensor Array

Resource scheduling in mobile edge computing using improved ant colony algorithm for space information network

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