Abstract
This article investigates the distributed data storage problem with compressed sensing in the space information network. Since there exists a performance-energy trade-off, most existing strategies focus only on improving the compressed sensing construction performance or reducing the energy consumption, respectively. In order to achieve a better balance, a novel and efficient strategy, referred to as distributed storage strategy based on compressed sensing, is proposed in this article. Unlike other strategies which require source packets visiting the entire network, the proposed strategy is a “one-hop” method since information exchange is only performed between neighbors. Therefore, the compressed sensing measurement matrix depends heavily on the degree of each space node. We prove that the proposed strategy guarantees the compressed sensing reconstruction performance under both sparse orthonormal basis and dense orthonormal basis. Simulation results validate that, compared with the representative CStorage strategy and compressive data persistence strategy, the proposed strategy consumes the least energy and computational overheads, while almost without sacrificing the compressed sensing reconstruction performance.
Highlights
The space information network (SIN) was proposed to solve the problems that different space systems’ built separately and inconvenience in cooperation
Detailed theoretical analysis and extensive simulations are provided to evaluate the proposed strategy compared with other representative strategies; the results show that the distributed storage strategy based on compressed sensing (DSSCS) strategy guarantees the compressed sensing (CS) reconstruction performance under both sparse orthonormal basis and dense orthonormal basis (e.g. discrete cosine transform (DCT) basis), while improving the energy efficiency
In section ‘‘Proposed DSSCS strategy,’’ we propose the DSSCS strategy to achieve the balance between CS reconstruction performance and energy efficiency
Summary
The space information network (SIN) was proposed to solve the problems that different space systems’ built separately and inconvenience in cooperation It can provide communication, navigation, and remote sensing service simultaneously using various space platforms, for example, satellites, aerial vehicles, highaltitude platforms (HAPs), and terrestrial terminals.[1,2] Unlike traditional wireless networks, the network status of SIN was changing dynamically due to the distinguishing characteristics such as self-organizing and large scale.[3] In our prior work,[4] we divided the SIN into a series of hierarchical autonomous system (AS) networks based on the property of space nodes.
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More From: International Journal of Distributed Sensor Networks
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