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In the dynamic landscape of social network analysis, the accurate prediction of implicit relationships presents a pivotal challenge. This paper introduces an innovative solution, the Relation Temporal Graph Convolutional Network with Confidence (R-CTGCN), specifically designed to address the intricate task of predicting implicit relations within evolving social networks. R-CTGCN unifies timestamp temporal embeddings, confidence metrics, and PFs within a comprehensive graph neural network framework, aiming to capture the evolving dynamics of networks and enhance predictive accuracy. Experimental evaluations conducted on diverse datasets, including Epinions and Enron, showcase R-CTGCN's superior performance compared to both baseline models and contemporary state-of-the-art methods. The emphasis on the roles of confidence and PFs underscores their significance in implicit relationship prediction. The outcomes contribute substantively to the understanding of predicting implicit relationships, positioning R-CTGCN as a robust tool tailored for complex social network scenarios. [ABSTRACT FROM AUTHOR]

With the continuous destruction of the data transmitted in the protection network system, data encryption is an important research object in the network security technology, and it is the core to ensure the correctness of the data transmitted in the network. Through further research and Analysis on the basic technologies of cryptography and data transmission, combined with several common data encryption algorithms and data communication methods, the Windows sock communication method and mixed encryption module of mixed encryption data transmission system are designed and studied. In this module, a pair of RSA keys are generated by the software system first, which are imported into the hybrid encryption process to encrypt the des keys randomly generated in the system, which optimizes the system design objectives and the main functions of the system. In this paper, through further careful and in-depth research on the two classical encryption algorithms DES (Data Encryption Standard) and RSA (Rivest-Shamir-Adleman), we propose and de-sign a method of heterogeneous network data security transmission based on hybrid encryption. The experiment is programmed by visual c++, and the mixed encryption data transmission system is simulated and tested. The experimental results show that the design and implementation of the hybrid encryption data transmission system overcomes the shortcomings of the previous systems, such as slow speed and difficult key transmission. [ABSTRACT FROM AUTHOR]

This paper is concentrated on the fixed/preassigned-time (FXT/PAT) synchronization of multilayered networks, in which the self-dynamics of nodes are heterogeneous and the synchronized state can be an arbitrary prescribed smooth orbit. Above all, the original network is augmented by involving the synchronized state as a virtual node, it is allowed to remove the topological connectivity limitations and reduce the conservatism of the synchronization conditions. Subsequently, several continuous control protocols have been developed to achieve FXT synchronization and some effective criteria are established by utilizing the theorem of FXT stability. Additionally, the relationship is revealed between the estimation of the synchronized time and the layer parameter. Moreover, the PAT synchronization is investigated for a preassigned synchronized time by proposing two control schemes with finite control gains. Eventually, the developed control designs and criteria are validated by some numerical simulations. • FXT/PT synchronization is considered for multilayer networks with a specified state. • The conservatism on topology and criteria is reduced by augmenting original network. • The relationship is revealed between the synchronized time and the layer parameter. [ABSTRACT FROM AUTHOR]

The synchronization problem of multi-agent systems with non-identical general agents under time-varying topologies and in the presence of external disturbances has not been solved for the introspective agents, i.e., agents have access to parts of their own states. This paper aims to tackle this problem. It is assumed that the time-varying topology switches among a certain amount of topologies with any a priori given dwell time and each topology contains a directed spanning tree. This paper proposes a family of distributed protocols for each agent only using relative information from its neighboring agents and some of its own states, such that synchronization can be achieved among agents while the effect of disturbances with finite power on the norm of all agents' output disagreement can be suppressed as much as possible. It should be emphasized that agents' controller states are exempted from the protocol design. [ABSTRACT FROM AUTHOR]

This paper focuses on a mobile edge‐computing‐enabled heterogeneous network. A battery level‐aware task‐scheduling framework is proposed to improve the energy efficiency and prolong the operating hours of battery‐powered mobile devices. The formulated optimization problem is a typical mixed‐integer nonlinear programming problem. To solve this nondeterministic polynomial (NP)‐hard problem, a decomposition‐based task‐scheduling algorithm is proposed. Using an alternating optimization technology, the original problem is divided into three subproblems. In the outer loop, task offloading decisions are yielded using a pruning search algorithm for the task offloading subproblem. In the inner loop, closed‐form solutions for computational resource allocation subproblems are derived using the Lagrangian multiplier method. Then, it is proven that the transmitted power‐allocation subproblem is a unimodal problem; this subproblem is solved using a gradient‐based bisection search algorithm. The simulation results demonstrate that the proposed framework achieves better energy efficiency than other frameworks. Additionally, the impact of the battery level‐aware scheme on the operating hours of battery‐powered mobile devices is also investigated. [ABSTRACT FROM AUTHOR]

• Integrate technological similarity and complementarity for R&D partner selection. • Modeling R&D collaborations using heterogeneous networks. • Introduce a loss function tailored for multi-feature fusion. • Provide a framework for multi-feature fusion in R&D collaboration networks. Choosing the right partner is a key factor in the success of enterprise R&D cooperation, directly affecting innovation outcomes and market competitiveness. Technical similarity provides a common language and foundational understanding between enterprises, while technical complementarity offers opportunities for knowledge exchange and innovation. However, no previous research has effectively integrated these two features within a collaborator recommendation framework. This study aims to explore a method that combines technological similarity and complementarity for collaborator recommendations. We introduced the Technological Similarity and Complementarity Enhanced Collaborator Recommendation (TSCE-CR) model, which constructs a heterogeneous corporate collaboration network and designs a tailored loss function. This model effectively integrates features of technological similarity and complementarity, enabling the neural network to capture and elucidate the nonlinear and multidimensional relationships in corporate collaborations. Experimental validation on patent data in the field of artificial intelligence demonstrated that our TSCE-CR model excels in identifying potential collaborators, effectively confirming the critical role of technological complementarity in R&D collaboration. This research provides a flexible framework for future studies on collaborator recommendations and offers reliable decision-making support for enterprises in selecting R&D partners. [ABSTRACT FROM AUTHOR]

Heterogeneous network link prediction is a hot topic in the analysis of networks. It aims to predict missing links in the network by utilizing the rich semantic information present in the heterogeneous network, thereby enhancing the effectiveness of relevant data mining tasks. Existing heterogeneous network link prediction methods utilize meta-paths or meta-graphs to extract semantic information, heavily relying on the priori knowledge. This paper proposes a heterogeneous network link prediction based on network schema and cross-neighborhood attention method (HNLP-NSCA). The heterogeneous node features are projected into a shared latent vector space using fully connected layers. To resolve the issue of prior knowledge dependence on meta-path, the semantic information is extracted by using network schema structures uniquely in heterogeneous networks. Node features are extracted based on the relevant network schema instances, avoiding the problem of meta-path selection. The neighborhood interaction information of input node pairs is sensed via cross-neighborhood attention, strengthening the nonlinear mapping capability of the link prediction. The resulting cross-neighborhood interaction vectors are combined with the node feature vectors and fed into a multilayer perceptron for link prediction. Experimental results on four real-world datasets demonstrate that the proposed HNLP-NSCA mothed outperforms the baseline models. [ABSTRACT FROM AUTHOR]

Due to the increased demand for scarce wireless bandwidth, it has become insufficient to serve the network user equipment using macrocell base stations only. Network densification through the addition of low power nodes (picocell) to conventional high-power nodes addresses the bandwidth dearth issue, but unfortunately introduces unwanted interference into the network which causes a reduction in throughput. The purpose of this paper is to develop a model for controlling the interference between picocell and macrocell users of a cellular network so as to increase the overall network throughput. In order to achieve this, a reinforcement learning model was developed which was used in coordinating interference in a heterogeneous network comprising macrocell and picocell base stations. The learning mechanism was derived based on Q-learning, which consisted of agent, state, action, and reward. The base station was modeled as the agent, while the state represented the condition of the user equipment in terms of Signal to Interference Plus Noise Ratio. The action was represented by the transmission power level and the reward was given in terms of throughput. Simulation results showed that the trend of values of the learning rate (e.g., high to low, low to high, etc.) plays a major role in throughput performance. It was particularly shown that a multi-agent system with a normal learning rate could increase the throughput of associated user equipment by a whopping 212.5% compared to a macrocell-only scheme. [ABSTRACT FROM AUTHOR]

With the development of mobile communications and Internet of things (IoT), the Internet of vehicles (IoV) has become commonplace. To integrate the heterogenous IoV networks, this paper mainly explores the heterogenous network selection mechanism for the IoV. Considering the diversity of IoV networks, the authors proposed a heterogenous network selection algorithm based on comprehensive weight. Based on different service scenarios and user preferences, the proposed algorithm obtains the subjective weights of candidate networks, calculates the objective weights of judgement indices by entropy method, and combines the subjective and objective weights into a comprehensive weight. On this basis, the candidate networks were analyzed by the utility function (UF), and the optimal network was selected for access. The research results provide a reference for high-quality access to heterogenous networks. [ABSTRACT FROM AUTHOR]

Cooperation between Telecommunications (Telco) operators has been limited both by regulation and competition in previous years. However, cooperation could not only allow an overall growth in quality of service (QoS) but also may benefit companies with under exploited nodes in their network infrastructure. This way, both fully deployed infrastructure by single Telco companies, as well as smaller companies with increasing service demand but low infrastructure deployment could potentially benefit from cooperation agreements. This article proposes a lexicographic mixed-integer linear optimization model for Telco cooperation composed by two phases: Phase 1 maximizes the number of services connected to the current infrastructure assuming cooperation between operators while Phase 2 minimizes the costs of connecting such services. We built a simple base scenario that allowed us to validate the intuition behind our model. Furthermore, to demonstrate the applicability of our lexicographic optimization model for cooperation between mobile operators, we present a real-world case study in a rural area in Colombia that allowed us to find the marginal costs of additional national roaming connections, as well as marginal profits under the cooperation schema. Our results could help mobile operators to benefit from cooperation and, since the model adapts to the local necessities of the company, cooperation could be restricted to any desired level. [ABSTRACT FROM AUTHOR]

Network traffic monitoring and analysis are useful and crucial because they allow networks to be better understood, more efficiently used, and more accurately evaluated. Heterogeneous networks are widely used because they enable public networks with improved coverage, capacity, and communication. This paper proposes a system design using both sFlow and NetStream technologies for traffic performance analysis in heterogeneous networks. This sFlow+NetStream design should enable the system to obtain network traffic data more comprehensively and accurately (compared with a system that uses only one of the two technologies) and to largely reduce the pressure on the monitoring and analysis system (compared with a system that uses traditional port mirroring technology). To verify the design objects, we built a test environment with an H3C router and an eNSP simulator and conducted experimental tests in it. The test results proved the aforementioned system design to be valid and feasible. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) links such as 28 GHz and 60 GHz propose high data rates and capacity needed in 5G Heterogeneous network (Hetnet) real-time system. The key factors in network planning of Hetnet are the locations and links of base stations, and their coverage, transmitted power, antenna angle, orientation etc. However, large-scale blockages like static buildings, human etc. affect the performance of urban Hetnets especially at mm Wave frequencies. A mathematical framework to model dynamic blockages is adapted and their impact on cellular network performance is analyzed. A machine learning approach based on Q-learning with Epsilon-Greedy algorithm is proposed to solve the blockage problem in such complex networks. The proposed results are evident and show the positive effect of increasing the base station density linearly with the blockage density to maintain the network connectivity. The performance of the proposed Epsilon- Greedy algorithm is compared with Epsilon-Soft algorithm. The performances of above said mmWave links are compared in terms of their coverage probability and throughput. The results show that an Epsilon-Greedy algorithm outperforms an Epsilon-Soft algorithm. [ABSTRACT FROM AUTHOR]

• We design a weighting scheme that considers and integrates citation relevance and author contribution in bibliometric networks. • We propose W-Rank algorithm based on the improved heterogeneous bibliometric networks for scientific article ranking. • We introduce a new perspective to interpret the bibliometric networks based on the practical meaning of the links between the papers, authors and journals. As the volume of scientific articles has grown rapidly over the last decades, evaluating their impact becomes critical for tracing valuable and significant research output. Many studies have proposed various ranking methods to estimate the prestige of academic papers using bibliometric methods. However, the weight of the links in bibliometric networks has been rarely considered for article ranking in existing literature. Such incomplete investigation in bibliometric methods could lead to biased ranking results. Therefore, a novel scientific article ranking algorithm, W-Rank, is introduced in this study proposing a weighting scheme. The scheme assigns weight to the links of citation network and authorship network by measuring citation relevance and author contribution. Combining the weighted bibliometric networks and a propagation algorithm, W-Rank is able to obtain article ranking results that are more reasonable than existing PageRank-based methods. Experiments are conducted on both arXiv hep-th and Microsoft Academic Graph datasets to verify the W-Rank and compare it with three renowned article ranking algorithms. Experimental results prove that the proposed weighting scheme assists the W-Rank in obtaining ranking results of higher accuracy and, in certain perspectives, outperforming the other algorithms. [ABSTRACT FROM AUTHOR]

Abstract The paper examines designing of a heterogeneous telecommunication network model, suitable for demands of transportation industry. The considered network simulation model comprises different transfer environments of modern voice and data systems, channel-forming elements and interfaces largely used in road and rail transport. The proposed heterogeneous network was built upon the SDH network (on the STM-1 level) with SDH/PDH switching equipment, radio-modems for cellular mobile communication networks, digital VoIP phones, utilizing IP/Ethernet connections to local computer networks. Heterogeneous network reflects the possibilities of modern telecommunication technologies and is used for experimental researches as a simulation model for automatic, telemechanics and communication systems in railway transport. [ABSTRACT FROM AUTHOR]

In order to optimize the network architecture, addressing mechanism, heterogeneous nodes and other functions of wireless sensor networks, this study begins with the issue of networking of large-scale heterogeneous networks. A layered distributed network architecture is proposed, which provides a powerful reference for the future architecture of wireless sensor networks. Based on this architecture, the resource addressing of the corresponding hierarchical network, and the scale and location deployment of heterogeneous nodes such as sink nodes are discussed separately, and corresponding strategies and algorithms are proposed. The research results show that the core idea of the addressing mechanism is data-centric, addressoriented addressing is transformed into service-oriented addressing. Therefore, the proposed LBA addressing algorithm is suitable for other hierarchically structured networks. In addition, although the sink node is taken as an example for research, it is also suitable for the deployment of other heterogeneous nodes such as sink nodes, relay nodes, and base stations. In summary, regardless of the number of nodes or the location of the deployment, energy-saving factors need to be considered. Energy-saving is also an indispensable technology in wireless sensor network technology. [ABSTRACT FROM AUTHOR]

In this paper, taking the positions of pico-cell base stations (PBSs) into consideration, a scheme of cell range expansion (CRE) for maximum sum rate is addressed in heterogeneous multi-input multi-output multi-user wireless networks. The optimal CRE bias obtained numerically by the proposed CRE scheme with inter-cell interference coordination (ICIC) allows us to maximize the sum rate while successfully maintaining the load balance between the macrocell base station and PBSs. Numerical results confirm that the proposed CRE scheme with ICIC can provide higher sum rate than conventional schemes and balanced load. [ABSTRACT FROM AUTHOR]

Predicting the occurrence of links or interactions between objects in a network is a fundamental problem in network analysis. In this work, we address a novel problem about tag co-occurrence relationship prediction across heterogeneous networks. Although tag co-occurrence has recently become a hot research topic, many studies mainly focus on how to produce the personalized recommendation leveraging the tag co-occurrence relationship and most of them are considered in a homogeneous network. So far, few studies pay attention to how to predict tag co-occurrence relationship across heterogeneous networks. In order to solve this novel problem mentioned previously, we propose a novel three-step prediction approach. First, image-tag bins are generated by utilizing the TF-IDF like method, which help reduce the search space. And then, weight path-based topological features are systematically extracted from the network. At last, a supervised model is used to learn the best weights associated with different topological features in deciding the co-occurrence relationships. Experiments are performed on real-world dataset, the Flickr network, with comprehensive measurements. Experimental results demonstrate that weight path-based heterogeneous topological features have substantial advantages over commonly used link prediction approaches in predicting co-occurrence relations in Flickr networks. [ABSTRACT FROM AUTHOR]

The heterogeneous network (HetNet) has been one of the key technologies in Long Term Evolution-Advanced (LTE-A) with growing capacity and coverage demands. However, the introduction of femtocells has brought serious co-layer interference and cross-layer interference, which has been a major factor affecting system throughput. It is generally acknowledged that the resource allocation has significant impact on suppressing interference and improving the system performance. In this paper, we propose a hybrid-clustering algorithm based on the Matérn hard-core process (MHP) to restrain two kinds of co-channel interference in the HetNet. As the impracticality of the hexagonal grid model and the homogeneous Poisson point process model whose points distribute completely randomly to establish the system model. The HetNet model based on the MHP is adopted to satisfy the negative correlation distribution of base stations in this paper. Base on the system model, the spectrum sharing problem with restricted spectrum resources is further analyzed. On the basis of location information and the interference relation of base stations, a hybrid clustering method, which takes into accounts the fairness of two types of base stations is firstly proposed. Then, auction mechanism is discussed to achieve the spectrum sharing inside each cluster, avoiding the spectrum resource waste. Through combining the clustering theory and auction mechanism, the proposed novel algorithm can be applied to restrain the cross-layer interference and co-layer interference of HetNet, which has a high density of base stations. Simulation results show that spectral efficiency and system throughput increase to a certain degree. [ABSTRACT FROM AUTHOR]

Cognitive radio technology is still the key technology of future mobile communication systems. Previous studies have focused on improving spectrum utilization and less energy consumption. In this paper, we propose an Overhead Reduced Scheme (ORS) for green cooperative spectrum sensing. Compared to traditional cooperative sensing scheme, ORS scheme divides the sensing time into three time slots and selects the best multi-mode user to report decisions. In consideration of reporting channel deviation, we derive closed-form expressions for detection probability and false alarm probability of ORS scheme based on Rayleigh fading channel. Simulation results show that ORS scheme can improve the perception accuracy while reducing the perceived delay and energy consumption in the process of perception, so as to realize the green communication. [ABSTRACT FROM AUTHOR]

Aiming at the problem of uplink co-channel interference in multi-user multi-input multi-output (MIMO) heterogeneous network, a reversed time division duplex (R-TDD)-based method is used to improve the performance of interference rejection combining (IRC) algorithm. This method overcomes the difficulty of IRC algorithm in obtaining the interference noise covariance matrix by utilizing the R-TDD transmission scheme. On the premise that the spectrum efficiency is guaranteed, through combining R-TDD with spatial modulation, the transmission complexity is significantly reduced and the uplink co-channel interference is effectively controlled, so as to improve the system performance. Simulation results demonstrate that the R-TDD-based scheme can improve the performance of IRC algorithm in terms of spectrum efficiency. [ABSTRACT FROM AUTHOR]

In this paper, an improved utility-based cross-layer dynamic subcarrier allocation (DSA) algorithm is proposed for single carrier frequency division multiple access (SC-FDMA) system, which adopts adaptive service rate control (ASRC) to eliminate the service rate waste and improve the spectral efficiency in heterogeneous network including non-real-time traffic and real-time traffic. In this algorithm, furthermore, a first in first out (FIFO) queuing model with finite space is established on the cross-layer scheduling framework. Simulation results indicate that by taking the service rate constraint as the necessary condition for optimality, the ASRC algorithm can effectively eliminate the service rate waste without compromising the scheduling performance. Moreover, the ASRC algorithm is able to further improve the quality of service (QoS) performance and transmission throughput by contributing an attractive performance trade-off between real-time and non-real-time applications. [ABSTRACT FROM AUTHOR]

Existing cellular network gives us the large network coverage as well as network capacity but in many cases it fails to achieve predicted data rates for the seamless wireless communication. Moreover there is a tremendous increase in wireless device users so the data rates and network capacity offered by conventional cellular network is not sufficient. So the effort to suppress base-stations power consumption are desperately needed and for that heterogeneous cellular network has been introduced. This paper provides the complete analysis of energy efficient wireless systems for heterogeneous cellular network as it has been pointed out to be one of the key network architectures that help to increase system capacity and reduce power consumption. Heterogeneous network with coordinated multi-point has received significant attention as a way of achieving energy efficiency and to improve the network handling capacity in heterogeneous cellular network. Usually in communication those users which are on the edge of the cells always suffer with the low data rates and low capacity. Moreover they get interference from the adjacent cells. To mitigate these problems and achieve higher energy efficiency Heterogeneous network with coordinated multi-point came out as one of the best solutions. In this paper heterogeneous network is considered with the Voronoi tessellation and between the cells coordinated multi-point technique is applied and compared with the non- coordinated multipoint scenario. Heterogeneous network is the integrated part of the beyond 4G wireless network for better energy efficiency. [ABSTRACT FROM AUTHOR]

In Heterogeneous Network (HetNet), the femtocell (HeNB) has been deployed by the telecommunication industries to provide extensive coverage as well as capacity in an indoor. These HeNBs are Customer Premise Equipment (CPE) which is randomly used in co-channel with macrocell (MeNB) and causes the Co-Tier Interference (CTI) in OFDMA. The effect of CTI in OFDMA systems can lead the system throughput degradation and service disruption. Because of quick direct changing features in Rayleigh channel, it is compulsory to succeed the satisfactory performance. The signal-to-interference noise ratio (SINR) is arbitrary which drives the highest capacity to be an irregular variable. However, this paper derives the expressions of outage probabilities based on the hybrid Genetic Algorithm (GA) with biogeography based dynamic subcarrier allocation (HGBBDSA) algorithm is implemented in reducing the outage probability. The outage probability countenance is expressed for the moment-generating function of the total SINR at the receivers end. The simulation results demonstrate that the HGBBDSA can lessen the outage to 45 % than existing methods. [ABSTRACT FROM AUTHOR]

Aiming at the user quality of experience (QoE) problem in the LTE-A heterogeneous network integrating IEEE802.11ad, a layered admission control strategy is proposed for heterogeneous network based on QoE. The core of the strategy is vertically layering the access categories priority and horizontally layering the resource allocation based on the layered access categories priority. A dynamic access categories priority scheme is introduced centering on the admission control strategy to build the power allocation model for minimizing the transmit power of base station as well as maximizing the overall QoE. The impact of different network coverage in the heterogeneous network on user QoE is further analyzed and the resource reservation method combined with users’ access priority is studied. Simulation results show that the layered admission control strategy, compared with the conventional ones, can significantly enhance the average QoE of heterogeneous networks. [ABSTRACT FROM AUTHOR]

This paper proposes a new interference mitigation scheme for device-to-device (D2D) communications underlaying a cellular network. The object of the proposed scheme is to determine the number of data streams, a precoding matrix, and a decoding matrix of D2D networks so as to maximize the system capacity given the number of data streams of a cellular network while satisfying the constraint of the inter-system interference from D2D networks to the cellular network. Unlike existing interference mitigation schemes based on the interference alignment technique, the proposed scheme operates properly regardless of the number of data streams of a cellular network and moreover it does not require changing the precoding and decoding matrices of a cellular network. The simulation results demonstrate that the proposed scheme significantly increases the system capacity by mitigating the intraand inter-system interference. [ABSTRACT FROM AUTHOR]

Structured measurements have been widely used to measure the impact of scholarly entities based on scholarly networks. Existing methods use heterogeneous scholarly networks and the PageRank algorithm to quantify the impact of scientific collaboration. However, by ignoring important higher-order relationships in citation networks, the impact of scientific collaboration is quantified by relying on first-order relationships, which leads to indistinguishable self-citations. In this paper, to address these shortcomings, we propose a Motif-based Scientific Collaboration Impact Rank framework, named as MSCIRank, which leverages the triangular motifs from the reconstructed collaboration-citation networks and integrates the first-order and higher-order relationships in the PageRank algorithm to quantify the impact of scientific collaboration and scholarly papers. MSCIRank consists of two models, i,e, linear and non-linear. Extensive experiments have demonstrated the effectiveness of MSCIRank. The experimental results show that MSCIRank is better than SCIRank in identifying Nobel Prize papers in terms of Recall. The MSCIRank model can weaken or strengthen the impact of self-citation. Linear MSCIRank is consistent with Pareto's principle, while non-linear MSCIRank is inconsistent. In addition, the average impact of pairs of co-authors with high impact in the linear MSCIRank is much higher than that in the non-linear MSCIRank. [ABSTRACT FROM AUTHOR]

Several research studies have been conducted on multi-label classification algorithms for text and images, but few have been conducted on multi-label classification for users. Moreover, the existing multi-label user classification algorithm does not provide an effective representation of users, and it is difficult to use directly in social media scenarios. By analyzing complex social networks, this paper aims to achieve multi-label classification of users based on research in single-label classification. Considering the limitations of existing research, this paper proposes a user topic classification method based on heterogeneous networks as well as a user multi-label classification method based on community detection. The model is trained using the ML-KNN multi-label classification algorithm. In actual scenarios, the algorithm is more effective than existing multi-label classification methods when applied to multi-label classification tasks for social media users. According to the results of the analysis, the algorithm has a high level of accuracy in classifying different theme users into a variety of different scenarios using different theme users. Furthermore, this study contributes to the advancement of classification research by expanding its perspective. • The existing researches on multi-label classification algorithms mostly focus on the fields of text and images, and there are few researches on multi-label classification for users. • The existing multi-label user classification algorithm does not achieve effective representation of users. • The paper realizes multi-label classification of users on the basis of single-label classification research. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) play a critical role by regulating their targets in post-transcriptional level. Identification of potential miRNA-disease associations will aid in deciphering the pathogenesis of human polygenic diseases. Several computational models have been developed to uncover novel miRNA-disease associations based on the predicted target genes. However, due to the insufficient number of experimentally validated miRNA-target interactions as well as the relatively high false-positive and false-negative rates of predicted target genes, it is still challenging for these prediction models to obtain remarkable performances. The purpose of this study is to prioritize miRNA candidates for diseases. We first construct a heterogeneous network, which consists of a disease similarity network, a miRNA functional similarity network and a known miRNA-disease association network. Then, an unbalanced bi-random walk-based algorithm on the heterogeneous network (BRWH) is adopted to discover potential associations by exploiting bipartite subgraphs. Based on 5-fold cross validation, the proposed network-based method achieves AUC values ranging from 0.782 to 0.907 for the 22 human diseases and an average AUC of almost 0.846. The experiments indicated that BRWH can achieve better performances compared with several popular methods. In addition, case studies of some common diseases further demonstrated the superior performance of our proposed method on prioritizing disease-related miRNA candidates. [ABSTRACT FROM AUTHOR]

Combining Wi-Fi and LTE data transmission technologies we can obtain an integrated solution that provides full end-to-end data transmission channel. This article compares goodputs of two LTE routers, which connect multiple WLAN access points (including Wi-Fi access controller) with the remote FTP server. Handover impact on data channel goodput is measured between wireless access points. Experimental data obtained by taking measurements under field conditions using real hardware, which imitates realistic two rank heterogeneous wireless network. The obtained results are very valuable, as they can be used as source data to develop mathematical network models as well as to tune network simulation software. The article also contains a mathematical model, which allows analyzing the impact on the data channel goodput at several competing vehicles which try to gain access to data channel via wireless access points. Experimental data is used in mathematical model. Obtained results supplement previous research and in this case the results show hardware's impact on channel goodput. [ABSTRACT FROM AUTHOR]

Introduction of Femtocells in heterogeneous network enhances the capacity, indoor coverage of the existing macrocell based network. It also allows high-speed data services for the multi-media application and software. However, in dense co-channel deployment scenarios femtocells cause severe interference to the neighbouring cells users. In this paper, a downlink-power-control scheme is presented for femtocell with no overhead signalling exchange with the macrocell. The femtocell adjusts the transmit power subject to home user equipment (HUE) measurements. The minimum level of transmit power is determined by the target Signal to Interference and Noise Ratio (SINR) of femtocell user that is set according to the required Quality of Service (QoS) of the femtocell users. The system level simulations confirm that, the proposed scheme reduces the outage probability of the nearby macrocell user equipment (MUE) up to 16.7% compared to fixed power setting, while maintaining the spectral efficiency of femtocell users. Furthermore, the transmit power can be reduced by 52.6% which leads to power effective solution of the interference scenario. [ABSTRACT FROM AUTHOR]

The interference is the most important problem in LTE or LTE-Advanced networks. In this paper, the interference was investigated in terms of the downlink signal to interference and noise ratio (SINR). In order to compare the different frequency reuse methods that were developed to enhance the SINR, it would be helpful to have a generalized expression to study the performance of the different methods. Therefore, this paper introduces general expressions for the SINR in homogeneous and in heterogeneous networks. In homogeneous networks, the expression was applied for the most common types of frequency reuse techniques: soft frequency reuse (SFR) and fractional frequency reuse (FFR). The expression was examined by comparing it with previously developed ones in the literature and the comparison showed that the expression is valid for any type of frequency reuse scheme and any network topology. Furthermore, the expression was extended to include the heterogeneous network; the expression includes the problem of co-tier and cross-tier interference in heterogeneous networks (HetNet) and it was examined by the same method of the homogeneous one. [ABSTRACT FROM AUTHOR]

Distributed monitoring and control systems are mandatory for the efficient management of the distribution grid, due to the growing presence of renewable energy sources. Time synchronization among devices deployed in distribution grid plays a key role, since a common time reference is essential to correlate power quality and high sampling frequency measure, and generally coordinate any distributed actions. The design and the deployment of a time synchronization system over an existing heterogeneous network is investigated in the paper. The Network Time Protocol (NTP) has been chosen due to its backward compatibility, the good security level, and the intrinsically robust hierarchy. Several NTP synchronization architectures have been proposed and then applied to a real (operating) distribution grid, both at Medium Voltage (MV) and Low Voltage (LV). The experimental validation was carried out during several weeks on the live system. The results in the MV grid highlight the trade-off existing between synchronization accuracy and availability: the synchronization accuracy over MV Broadband Power Line (BPL) links decreases from 20 ms to 50 ms when a more reliable architecture, from the point of view of time synchronization, is used. On the other hand, experimental results show as end-nodes connected on LV grid by means of BPL have a mean offset typically below 50 ms, and a synchronization accuracy on the order of 150 ms. These results are due to the limitation of the synchronization protocol deployed in the LV end-nodes and to scalability issues of power line communication networks when the number of nodes increases. [ABSTRACT FROM AUTHOR]

To solve the topology structure of a greenhouse environment-monitoring system and the ductility of joints, this study presents a design of a greenhouse-monitoring system based on the ZigBee wireless sensor network (WSN). The hardware and software designs of the network node are provided, and the process of the ZigBee network coordinator is elucidated. The system uses the microcontroller unit PIC18F4620CC2420 wireless transceiver module to send and receive data. Data from temperature and humidity sensors are collected using an inter-integrated circuit bus through the ZigBee network transmission to the monitoring platform. Test results show that the system has the advantages of having a simple structure, flexible nodes, and low power consumption. It can effectively monitor the temperature and humidity in a wireless environment. WSNs considerably help in greenhouse environment monitoring. The use of advanced technology to control greenhouse temperature and humidity can satisfy the optimum growth environment of greenhouse crops and effectively improve the yield and quality of crops. The application of WSNs in greenhouse monitoring is significant to the development of modern and precision agriculture in China. [ABSTRACT FROM AUTHOR]

In this paper, we attempt to use the rating information to adjust linkage-weight between nodes to improve effectiveness of product recommendation. As we all known, sometimes we purchase goods or watch a movie do not really mean we like or we would purchase them again. Thus, it is necessary to take the relationship of nodes into account, which we use linkage-weight to indicate. However, most of prior work only consider the existence of linkages, ignoring the remarkable meaning of linkage between nodes. To evaluate our algorithm, we compare both the original link prediction local path index and simplified linkage-weight index (-1,0,1) to our index and our results achieve significantly better performance. [ABSTRACT FROM AUTHOR]

Recently, people have been able to connect with different types of networks anytime, anywhere using advanced network technologies. In order to properly distribute wireless network resources among different clients, this work proposed a user mobility prediction algorithm, which takes the coverage of different kinds of base stations, and the volatile mobility of pedestrians, vehicles, and mass transportation, into consideration. In addition, a novel bandwidth utilization optimization technique is proposed in the algorithm to allocate bandwidth more efficiently. The Hybrid Genetic Algorithm, which combines the Genetic Algorithm and local searches to improve the frequency of finding a Pareto set, is used to realize the optimization problem as well. Compared with our previous work and the other four methods in the literature, the simulation results show that our proposed work can achieve desirable performance by network utilization, throughput, and QoS quality in the heterogeneous wireless networks. [ABSTRACT FROM AUTHOR]

Backpressure based scheduling has been considered as a promising technique for improving the throughput of a wide range of communication networks. However, this scheduling technique has not been well studied for heterogeneous wireless networks. In this paper, we propose a virtual-queue based backpressure scheduling (VQB) algorithm for heterogeneous multi-hop wireless networks. The VQB algorithm introduces a simple virtual queue for each flow at a node for backpressure scheduling, whose length depends on the cache size of the node. When calculating flow weights and making scheduling decisions, the length of a virtual queue is used instead of the length of a real queue. We theoretically prove that VQB is throughput-optimal. Simulation results show that the VQB algorithm significantly outperforms a classical backpressure scheduling algorithm in heterogeneous multi-hop wireless networks in terms of the packet delivery ratio, packet delivery time, and average sum of the queue lengths of all nodes per timeslot. [ABSTRACT FROM AUTHOR]

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Efficient handover optimization and intelligent mobility management mechanism are the key requirements for designing next generation wireless network. Therefore, a dynamic Multiple Attribute decision based on Priority of Traffic classes (MAPT) for Constant Bit rate (CBR) and Variable Bit Rate (VBR) are proposed in this paper to optimize the handover operations. The IEEE 802.21 Media Independent Handover (MIH) standard provides an associated service to MAPT for achieving seamless handover. Simulation results prove that the proposed work resourcefully minimizes the vertical handover delay, packet loss, jitter and thus improves the throughput for both real time and non- real time applications. [ABSTRACT FROM AUTHOR]

In this paper we describe a novel approach that combines dynamic spectrum allocation and transmission power optimization for the secondary network users in an heterogeneous cognitive radio network. The proposed approach builds upon reinforcement learning and convex optimization procedures. Furthermore, the several key components, i.e. inter-cell interference, path loss, and fading have been considered when designing the power optimization algorithm. Simulation results show that the proposed approach improves the QoS of the system by up to 10 dB in terms of SINR and by up to 4% in terms of spectral efficiency while maintaining the average dissatisfaction probability close to that of the non-optimized approach. [ABSTRACT FROM AUTHOR]

Time reversal (TR) beamforming, considered as one of most prominent linear precoders, has showed the feasibility in conventional communications. In this paper, we propose the TR-based transmit optimization for heterogeneous networks (HetNets) where multiple femtocells apply TR precoders over frequency selective channels, with the signal-to-inference-plus-noise ratio (SINR) and interference constraints at single-antenna femtocell user devices. In multi-femtocell network environments, we exhibit that TR outperforms the well-known zero-forcing beamforming. Particularly, we focus on the practical case of imperfect channel estimation at femtocell base stations. The robust optimization methodology is hence devised by taking into account the average effect of channel estimation error (CEE) on system performance. Under the assumption of estimation error in time-varying channels, we derive the exact closed-form expressions of the desired signal, inter-symbol interference (ISI), inter-user interference (IUI), co- and cross-layer interference terms, respectively. These derivations allow us to tackle the proposed robust algorithm by convex optimization techniques. In final, numerical results are shown to confirm the validation of our proposal. [ABSTRACT FROM AUTHOR]

This paper presents a proposed system for controlling the real time application (Video conferencing) in heterogeneous operating systems dealing with transferring streams of audio-video data with real time constraints among heterogeneous operating systems. This system provides integration between multimedia technologies as well as real time technologies via using suitable network protocols. The principle has included reading and analyzing the video data in linux either from a normal video file or from a direct broadcast via using camera and a microphone. The data are scheduled by means of real time technique and transferred to other computers operated with windows for displaying video frames and audio sample. This work achieves lip synchronization rate in video displaying by 95%. [ABSTRACT FROM AUTHOR]

Integrated WiMAX and WiFi networks is of great potential for the future due to the wider coverage of WiMAX and the high data transport capacity of WiFi. However, seamless and secure handover (HO) is one of the most challenging issues in this field. In this paper, we present a novel vertical HO authentication scheme with privacy preserving for WiMAX-WiFi heterogeneous networks. Our scheme uses ticket-based and pseudonym-based cryptographic methods to secure HO process and to achieve high efficiency. The formal verification by the AVISPA tool shows that the proposed scheme is secure against various malicious attacks and the simulation result indicates that it outperforms the existing schemes in terms of communication and computation cost. [ABSTRACT FROM AUTHOR]

Quick, accurate damage monitoring is strongly required for damage assessment in the aftermath of a large natural disaster. Wireless sensor networks are promising technologies to acquire damage information in a citywide area. The wireless sensor networks, however, would be faced with difficulty to collect data in real-time and to expand the scalability of the networks. This paper discusses a scheme of network architecture to cove a whole city in multi-tier heterogeneous networks, which consist of wireless sensor networks, access networks and a backbone network. We first review previous studies for citywide damage monitoring, and then discuss the feature of multi-tier heterogeneous networks to cover a citywide area. [ABSTRACT FROM AUTHOR]