In this letter, a greedy routing strategy is proposed for resource scheduling in Earth observation mission to achieve the maximum throughput and improve the energy efficiency. Resource time-expanded graph (RTEG) is introduced to depict the time-evolving topology and resources of satellite networks. Based on RTEG, an energy efficient resource allocation algorithm (EERA) is designed to reduce the total energy consumption and maximize the throughput in data transmission by properly scheduling the transceiver resource, storage resource and power resource of satellites. Simulation results show that EERA achieves preferred energy efficiency when reaching the maximum throughput.

360-degree videos, as a type of media that offers highly immersive experiences, often result in significant bandwidth waste due to incomplete views by users. This places a heavy demand on streaming systems to support high-bandwidth requirements. Recently, tile-based streaming systems combined with viewport prediction have become popular to improve bandwidth efficiency. However, since the viewport prediction is only reliable in the short term, maintaining a long buffer to avoid rebuffering is challenging. We propose JUST360 , a joint utility based two-tier 360-degree video streaming system in this paper. To better improve the accuracy of utility evaluation, a utility model incorporates image quality and prediction accuracy is proposed to evaluate the contribution of each tile so that longer buffer and bandwidth efficiency can coexist. The optimal bitrate allocation strategy is determined by using model predictive control (MPC) to dynamically select the tiles according to their characteristics. Experiments show that our method successfully achieves higher PSNR and less rebuffering. Compared with other state-of-the-art methods, our proposed method can outperform the other methods by 3%-20% in terms of QoE.

With the development of the data-sharing system in recent years, financial management systems and their privacy have sparked great interest. Existing financial data-sharing systems store metadata, which include a hash value and database index on the blockchain, and store high-capacity actual data in the center database. However, current data-sharing systems largely depend on centralized systems, which are susceptible to distributed denial-of-service (DDoS) attacks and present a centralized attack vector. Furthermore, storing data in a local center database has a high risk of information disclosure and tampering. In this paper, we propose the ChainMaker Privacy Computing (CPC) system, a new decentralized data-sharing system for secure financial data, to solve this problem. It provides a series of financial data information and a data structure rather than actual data on the blockchain to protect the privacy of data. We utilize a smart contract to establish a trusted platform for the local database to obtain encrypted data. We design a resource catalog to provide a trusted environment of data usage in the privacy computing system that is visible for members on the blockchain. Based on cipher-policy attribute-based encryption (CP-ABE), We design a CPC-CP-ABE algorithm to enable fine-grained access control through attribute based encryption. Finally, We propose an efficient scheme that allows authenticated data-sharing systems to perform Boolean searches on encrypted data information. The results of experiment show that the CPC system can finish trusted data sharing to all organizations on the blockchain.

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency.

The circulation of digital assets has become increasingly crucial in today’s digital economy, reflecting both its growing importance and the challenges it faces. Blockchain technology, with its inherent symmetry, has emerged as a transformative force in facilitating digital asset circulation, addressing various issues related to security, efficiency, and transparency. This paper aims to advance the development of digital asset circulation technologies by focusing on four key blockchain-based technologies: smart contracts, consensus algorithms, cross-chain technology, and decentralized exchanges. These technologies embody symmetry in their structure and operation, ensuring balanced and secure asset management across decentralized networks. This paper reviews the evolution of these key technologies, highlighting their contributions to the digital asset ecosystem. It explores effective application cases and analyzes the current challenges each technology faces. Additionally, this paper provides insights into potential future developments and directions to address these challenges and enhance the overall efficiency and reliability of digital asset circulation.

360-degree videos usually require extremely high bandwidth and low latency for wireless transmission, which hinders their popularity. A tile-based viewport adaptive streaming scheme, which involves accurate viewport prediction and optimal bitrate adaptation to maintain user Quality of Experience (QoE) under a bandwidth-constrained network, has been proposed by researchers. However, viewport prediction is error-prone in long-term prediction, and bitrate adaptation schemes may waste bandwidth resources due to failing to consider various aspects of QoE. In this paper, we propose a synergistic temporal-spatial user-aware viewport prediction scheme for optimal adaptive 360-Degree video streaming (SPA360) to tackle these challenges. We use a user-aware viewport prediction mode, which offers a white box solution for Field of View (FoV) prediction. Specially, we employ temporal-spatial fusion for enhanced viewport prediction to minimize prediction errors. Our proposed utility prediction model jointly considers viewport probability distribution and metrics that directly affecting QoE to enable more precise bitrate adaptation. To optimize bitrate adaptation for tiled-based 360-degree video streaming, the problem is formulated as a packet knapsack problem and solved efficiently with a dynamic programming-based algorithm to maximize utility. The SPA360 scheme demonstrates improved performance in terms of both viewport prediction accuracy and bandwidth utilization, and our approach enhances the overall quality and efficiency of adaptive 360-degree video streaming.