Related papers: Collaborative Satellite Computing through Adaptive…
We present the design of a Resource-Aware Task Allocator (RATA) and an empirical analysis in handling real-time tasks for processing on Distributed Satellite Systems (DSS). We consider task processing performance across low Earth orbit…
We develop an integrated Multi-Port Concurrent Communication Divisible Load Theory (MPCC-DLT) framework for relay-centric distributed satellite systems (DSS), capturing concurrent data dissemination, parallel computation, and result return…
Satellite-terrestrial integrated networks (STIN) are envisioned as a promising architecture for ubiquitous network connections to support diversified services. In this paper, we propose a novel resource slicing scheme with cross-cell…
Unmanned aerial vehicles (UAVs) are becoming a viable platform for sensing and estimation in a wide variety of applications including disaster response, search and rescue, and security monitoring. These sensing UAVs have limited battery and…
Satellite edge computing has become a promising way to provide computing services for Internet of Things (IoT) devices in remote areas, which are out of the coverage of terrestrial networks, nevertheless, it is not suitable for large-scale…
The advancements of remote sensing (RS) pose increasingly high demands on computation and transmission resources. Conventional ground-offloading techniques, which transmit large amounts of raw data to the ground, suffer from poor…
Distributed computing in the context of deep neural networks (DNNs) implies the execution of one part of the network on edge devices and the other part typically on a large-scale cloud platform. Conventional methods propose to employ a…
With the continuous increment of maritime applications, the development of marine networks for data offloading becomes necessary. However, the limited maritime network resources are very difficult to satisfy real-time demands. Besides, how…
The development of artificial intelligence (AI) provides opportunities for the promotion of deep neural network (DNN)-based applications. However, the large amount of parameters and computational complexity of DNN makes it difficult to…
In the next generation network, the satellite network will play a fundamental role, in overcoming the limitation of the terrestrial network. Nonetheless, the satellite-terrestrial network integration presents a number of problems due to the…
Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing…
Edge computing that enables satellites to process raw data locally is expected to bring further timeliness and flexibility to satellite-terrestrial networks (STNs). In this letter, we propose a three-layer edge computing protocol, where raw…
Computing tasks are ubiquitous in space missions. Conventionally, these tasks are offloaded to ground servers for computation, where the transmission of raw data on satellite-to-ground links severely constrains the performance. To overcome…
Computing at the edge is increasingly important since a massive amount of data is generated. This poses challenges in transporting all that data to the remote data centers and cloud, where they can be processed and analyzed. On the other…
The explosive growth in wireless service demand has prompted the evolution of integrated satellite-terrestrial networks (ISTNs) to overcome the limitations of traditional terrestrial networks (TNs) in terms of coverage, spectrum efficiency,…
With the current trend towards low Earth orbit mega-constellations with inter-satellite links, efficient routing in such highly dynamic space-borne networks is becoming increasingly important. Due to the distinct network topology,…
Devices within the marine Internet of Things (MIoT) can connect to low Earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) to facilitate low-latency data transmission and execution, as well as enhanced-capacity data storage.…
In this paper, we investigate the issue of satellite-terrestrial computing in the sixth generation (6G) wireless networks, where multiple terrestrial base stations (BSs) and low earth orbit (LEO) satellites collaboratively provide edge…
Deep neural network (DNN) partition is a research problem that involves splitting a DNN into multiple parts and offloading them to specific locations. Because of the recent advancement in multi-access edge computing and edge intelligence,…
Diffractive neural network (DNN), which can perform machine learning tasks based on the light propagation and diffraction, has recently emerged as a promising optical computing paradigm due to its high parallel processing speed and low…