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With the exponentially growing earth observation data of specific sensor-determined resolutions and update frequencies, earth observation has irreversibly arrived in the Big Data era, enabling new insights in science and engineering. With great opportunity comes great challenges regarding efficient and effective data management because earth observation data is of different scales and characterized by complexity in spatial relationships related to the real world. To overcome the challenges is crucial for, for instance, data mining, land surveying, and especially emergency mapping for disaster response. To improve the querying efficiency of big earth observation data, we proposed a novel data management approach: Global Multi-scale Grid Integer Coding and Spatial Indexing. Among our contributions are: (1) proposing Global Multi-scale Grid Integer Coding Model (GMGICM), which presents clustering property in both the scale dimension and spatial dimension, and theoretically facilitates an efficient querying; (2) deliberately applying GMGICM on multi-scale earth observation data spatial indexing, which results in one-dimensional data index, which can be queried using simple B-tree, inversion, and other one-dimensional indexes; (3) designing a strategy to assure the completeness of spatial querying, which is not well solved by existing grid-based coding models. The advantages of our proposed approach have been demonstrated with both simulated and real remote sensing data, with spatial operation 20 times as fast as Geohash and spatial querying 10 times as fast as Oracle Spatial on average. The proposed approach can be easily adapted for three or higher-dimensional earth observation data and bring potential benefit to all big earth observation data analytic projects.

Few-mode fiber (FMF), a mode multiplex technique, has been a candidate to provide high transmission capability in next-generation elastic optical networks (EONs), where the probabilistic shaping (PS) technology is widely used to approach Shannon limit. In this paper, we investigate a fast and accurate method of modulation format recognition (MFR) of received signals based on a transfer learning network (TLN) in PS-based FMF-EONs. TLN can apply the feature extraction ability of convolutional neural networks to the analysis of the constellations. We conduct experiments to demonstrate the effectiveness of the proposed scheme in FMF transmissions. Six modulation formats, including 16QAM, PS-16QAM, 32QAM, PS-32QAM, 64QAM and PS-64QAM, and four propagating modes, including LP01, LP11a, LP11b and LP21, are involved. In addition, comparisons of TLN with different structures of convolutional neural networks backbones are presented. In the experiment, the iterations of the TLN are one-tenth that of conventional deep learning network (DLN), and the TLN overcomes the problem of overfitting and requires less data than that of DLN. The experimental results show that the TLN is an efficient and feasible method for MFR in the PS-based FMF communication system.

In this paper, we propose a high-security orthogonal chirped division multiplexing passive optical network (OCDM-PON) based on three-dimensional (3D) encryption, including the encryption of bitstream, constellation, and subcarriers. Cascaded fractional-order chaotic mapping (CFCM) is used to generate three masking factors to achieve ultra-high-security encryption in three different dimensions. Logistic mapping is used to control the order of the scheme, which effectively increases the key space to 10152 and improves the security performance of the system. The experiment proves the feasibility of the encryption scheme on OCDM after 16 orthogonal amplitude modulation (16QAM). The encrypted 16QAM-OCDM signal transmits data at a rate of 56 Gb/s on a 2-km 7-core optical fiber, and simultaneously transmits the 16QAM orthogonal frequency division multiplexing (OFDM) signal under the same conditions. It is shown that OCDM-PON is 1.3 dB higher than OFDM-PON in terms of receiver sensitivity when the bit error rate (BER) is 10−3.

Two means of high speed optical sampling covering C band and L band based on sum frequency generation (SFG) in chirped periodically poled LiNbO 3 (CPPLN) waveguide are studied in this paper. For the first method, arbitrary waveband inside C and L band can be sampled by tuning pump wavelength and the bandwidth is controllable by choosing suitable waveguide length and chirped coefficient of CPPLN waveguide. For another, the broad bandwidth covering C band and L band can be obtained with a fixed pump. The numerical simulations based on coupled-wave equations are carried out. The NRZ sequences of 10 Gb/s and 640 Gb/s transmission rate are sampled in simulation. Distinct eye diagrams and quality factors (Q) are obtained by software-synchronized algorithm. The results show that the two means of the optical sampling both can cover C band and L band. SFG in CPPLN waveguide used for optical sampling system has a broad bandwidth and more flexible selectivity.

Smartphone applications are becoming increasingly popular. However, these applications can suffer limited power budgets or malfunctioned sensing issues from their host devices. Computation offloading addresses this issue by delegating local computation workloads to remote servers. In this paper, we present Cose Droid, a framework that supports dynamic computation- and sensing-offloading across different Android mobile devices. This enables Android applications to virtually "borrow" computation or sensing resources from other devices. We experimentally evaluated Cose Droid with real-world Android applications. The experimental results confirmed Cose Droid's effectiveness in on-demand offloading, as well as supporting sensor variety and spontaneous sensing recovery.

Conventional thermal noise phase jitter formula of GNSS receivers' digital phase-locked loop (DPLL) for carrier recovery, which implies that the phase jitter monotonously decreases with the coherent integration time (CIT), can not be used for high-sensitivity DPLL design effectively. Variance comparison between I · Q phase detector (PD) which is normalized by the total power and two-quadrant arctangent PD indicates that the I · Q PD performs better than the other when used for tracking weak signals. The new thermal noise phase jitter formula for 3rd-order carrier DPLL is derived based on the newly developed linear loop model. Analytical results show that there exists an optimal CIT for minimizing thermal noise phase jitter. Finally, the optimal CIT of 3rd-order carrier DPLL is given by numerical method, which can be used for high-sensitivity digital carrier tracking loop design directly.