71,217 research outputs found
Survey of Inter-satellite Communication for Small Satellite Systems: Physical Layer to Network Layer View
Small satellite systems enable whole new class of missions for navigation,
communications, remote sensing and scientific research for both civilian and
military purposes. As individual spacecraft are limited by the size, mass and
power constraints, mass-produced small satellites in large constellations or
clusters could be useful in many science missions such as gravity mapping,
tracking of forest fires, finding water resources, etc. Constellation of
satellites provide improved spatial and temporal resolution of the target.
Small satellite constellations contribute innovative applications by replacing
a single asset with several very capable spacecraft which opens the door to new
applications. With increasing levels of autonomy, there will be a need for
remote communication networks to enable communication between spacecraft. These
space based networks will need to configure and maintain dynamic routes, manage
intermediate nodes, and reconfigure themselves to achieve mission objectives.
Hence, inter-satellite communication is a key aspect when satellites fly in
formation. In this paper, we present the various researches being conducted in
the small satellite community for implementing inter-satellite communications
based on the Open System Interconnection (OSI) model. This paper also reviews
the various design parameters applicable to the first three layers of the OSI
model, i.e., physical, data link and network layer. Based on the survey, we
also present a comprehensive list of design parameters useful for achieving
inter-satellite communications for multiple small satellite missions. Specific
topics include proposed solutions for some of the challenges faced by small
satellite systems, enabling operations using a network of small satellites, and
some examples of small satellite missions involving formation flying aspects.Comment: 51 pages, 21 Figures, 11 Tables, accepted in IEEE Communications
Surveys and Tutorial
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Formal and Informal Methods for Multi-Core Design Space Exploration
We propose a tool-supported methodology for design-space exploration for
embedded systems. It provides means to define high-level models of applications
and multi-processor architectures and evaluate the performance of different
deployment (mapping, scheduling) strategies while taking uncertainty into
account. We argue that this extension of the scope of formal verification is
important for the viability of the domain.Comment: In Proceedings QAPL 2014, arXiv:1406.156
Network-aware design-space exploration of a power-efficient embedded application
The paper presents the design and multi-parameter optimization of a networked embedded application for the health-care domain. Several hardware, software, and application parameters, such as clock frequency, sensor sampling rate, data packet rate, are tuned at design- and run-time according to application specifications and operating conditions to optimize hardware requirements, packet loss, power consumption. Experimental results show that further power efficiency can be achieved by considering also communication aspects during design space exploratio
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