A Mobile Ad Hoc Network (MANET) is a dynamic wireless network that can be formed without the need for any pre-existing infrastructure in which each node can act as a router. Due to bandwidth constraint and dynamic topology of mobile ad hoc networks, multipath supported routing is a very important research issue. This paper proposes a Network Coding-based on-demand Multipath Routing algorithm in MANET (NCMR). It is typically proposed in order to increase the reliability of data transmission or to provide load balancing. In our simulation, we compare NCMR routing protocol with AODVM routing protocol, in terms of the packet delivery ratio, packet overhead, and average end-to-end delay when a packet is transmitted. The simulation results show that the NCMR routing protocol provide an accurate and efficient method of estimating and evaluating the route stability in dynamic MANETs.
Quadratic permutation polynomial (QPP) has good coding characteristics and parallel processing ability. Random linear network coding (RLNC) is an improved coding algorithm for wireless channel video streaming, which can improve the network throughput and network lifetime of mobile ad hoc network (MANET). In this paper, we study the characteristics of quadratic permutation polynomials (QPP) and RLNC by increasing the amount of available data to the users through the encode nodes. The paper proposes a quadratic permutation polynomials enhancement of a RLNC approach in MANETs (QPP-RLNC). QPP-RLNC algorithm can better control the complexity of encoding/decoding and restore the original data. The performance of QPP-RLNC algorithm, such as coding overhead, decoding delay, packet loss probability and network throughput, was experimentally studied by using network simulation (NS2) software. Simulation results show that the proposed QPP-RLNC algorithm can improve coding efficiency and network performance.
The financial technology (FinTech) has promoted the wide application of FinTech with the help of artificial intelligence, blockchain, cloud computing, data science and other new technologies. Trust evaluation has become a forward-looking issue for the rapid development of FinTech. The existing trust evaluation methods of FinTech do not consider the impact of the timeliness, reliability and non-invasive factors of trust on trust evaluation, which results in low accuracy of trust evaluation and incapability of effectively identifying malicious behaviors of users. Firstly, this paper introduces the blockchain technology to construct a four-layer architecture structure and multiple trust evaluation indicators based on blockchain service data. Secondly, the paper proposes a blockchain based FinTech trust evaluation mechanism (BFTEM), which utilizes blockchain to record relevant data and multiple trust parameters during the transmission process of each block, and verify the trust degree issued by the trust holder through the comprehensive trust value of the user. Finally, the block generation time, throughput, delayed response time and comprehensive trust value are experimentally studied through simulation experiments. Simulation experiments show that BFTEM mechanism can better improve the security and reliability of FinTech data, and has advantages in improving the accuracy of trust evaluation and expanding potential applications.
Updating geospatial data has recently become an important work for related fields. Constantly changing geospatial data are meaningless for all geospatial databases at all scales with problems in the representation condition and reasoning for new objects. We proposed an incremental updating strategy and method for geospatial data based on granular computing, to solve the problems in both static and dynamic conditions. We pointed out that proper representation of geospatial data at a given scale cannot be achieved unless the original data of geospatial objects satisfy the representation condition. With granular computing, we can implement the representation condition, with which new geospatial data can be inferred. In addition, we also introduced the method for a case.
To meet the required manufacturing accuracy of high-quality aberration-corrected holographic gratings, we propose a moiré alignment algorithm for the exposure system of holographic gratings. A model holographic grating exposure system is built with multiple degrees of freedom based on optical path function theory. The whole process algorithm is then derived, including the fourth-order orthogonal polynomial of the holographic gratings, fitted aberration coefficients, and an optimized Levenberg-Marquardt algorithm for the exposure system's recording parameters. Finally, the simulated alignment and error analysis of a 2400 gr/mm aberration-corrected holographic grating's exposure system are presented. The proposed moiré alignment algorithm for such exposure systems can effectively improve the alignment accuracy, ensuring better holographic grating aberration correction ability.
Network coding (NC) enables us to mix two or more packets into a single coded packet at relay nodes and improve performances in wireless networks. Intra-session sliding window network coding is used at the source nodes and inter-session network coding is employed at the relay node to combine the recovered source packets of source nodes. In this paper, we investigate the performance of the network-coded system in terms of the probability that the destination node will successfully recover the source packets of the source nodes. We propose a sliding window network coding in relay wireless networks (SWNC-RN). The performance of the SWNC-RN is studied using NS2 and evaluated in terms of the network throughput, decoding delay, packet transmission rate when data packet is transmitted. The simulations result shows that the SWNC-RN with our proposition can significantly improve the network throughput and achieves higher diversity order.
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