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Due to line-of-sight communication links and distributed deployment, Unmanned Aerial Vehicles (UAVs) have attracted substantial interest in agile Mobile Edge Computing (MEC) service provision. In this paper, by clustering multiple users into independent communities based on their geographic locations, we design a 5G-enabled UAV-to-community offloading system. A system throughput maximization problem is formulated, subjected to the transmission rate, atomicity of tasks and speed of UAVs. By relaxing the transmission rate constraint, the mixed integer non-linear program is transformed into two subproblems. We first develop an average throughput maximization-based auction algorithm to determine the trajectory of UAVs, where a community-based latency approximation algorithm is developed to regulate the designed auction bidding. Then, a dynamic task admission algorithm is proposed to solve the task scheduling subproblem within one community. Performance analyses demonstrate that our designed auction bidding can guarantee user truthfulness, and can be fulfilled in polynomial time. Extensive simulations based on real-world data in health monitoring and online YouTube video services show that our proposed algorithm is able to maximize the system throughput while guaranteeing the fraction of served users. [ABSTRACT FROM AUTHOR]

How to put fifth-generation (5G) into the commercial service by 2020 is still challenging. Since physical-layer network coding (PNC) does not bring unnecessary redundancy and offers satisfactory end-to-end services, it is promising to provide network services in 5G networks. Existing works on PNC mainly focus on the case that two packets are simultaneously sent by a node pair for information exchange, and the transmitted signals are superposed and encoded at a relay. To further exploit the potential performance improvement of PNC, this study aims at encoding multiple packets through jointly processing multiple superposed signals sent by diverse node pairs. Particularly, we formulate the problem of joint-encoding method design as a binary integer programming model and propose a low-complexity solution based on the idea of filling a Latin rectangle. We find that network throughput enhancement does not accompany the increasing number of coded node pairs, and some node pairs cannot be encoded together since they fail to decode the resulting encoded packet. Therefore, the decodability-based node pair grouping scheme is further investigated. Simulation results in various scenarios show that the proposed low-complexity scheme performs neck to neck to the optimum one with high computational complexity. [ABSTRACT FROM PUBLISHER]

Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the anomalous citations and ensure the fairness and accuracy of research outcome evaluation, we investigate the citation relationships between articles using the following factors: collaboration times, the time span of collaboration, citing times and the time span of citing to weaken the relationship of Conflict of Interest (COI) in the citation network. Meanwhile, we study a special kind of COI, namely suspected COI relationship. Based on the COI relationship, we further bring forward the COIRank algorithm, an innovative scheme for accurately assessing the impact of an article. Our method distinguishes the citation strength, and utilizes PageRank and HITS algorithms to rank scholarly articles comprehensively. The experiments are conducted on the American Physical Society (APS) dataset. We find that about 80.88% articles contain contributed citations by co-authors in 26,366 articles and 75.55% articles among these articles are cited by the authors belonging to the same affiliation, indicating COI and suspected COI should not be ignored for evaluating impact of scientific papers objectively. Moreover, our experimental results demonstrate COIRank algorithm significantly outperforms the state-of-art solutions. The validity of our approach is verified by using the probability of Recommendation Intensity. [ABSTRACT FROM AUTHOR]

Abstract: Physical-layer network coding (PNC) is a promising approach for wireless networks: it allows nodes to transmit simultaneously and encode packets by superposing signals at the physical layer, which can improve throughput. Because of the difficulty in scheduling simultaneous transmissions, we propose an opportunistic scheduling algorithm in the media access control (MAC) layer and analyze the achievable throughput of the Denoise-and-Forward (DF) PNC scheme for both symmetric and asymmetric channel statuses, where random errors may occur for both BPSK and QPSK modulation techniques. Simulation results show that our algorithm cannot only improve throughput but can also adapt to varying channel conditions. It is further revealed that for the same throughput, our algorithm is more power-efficient with an asymmetric channel status than with a symmetric channel status. [Copyright &y& Elsevier]