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Interference-graph and fuzzy C-means based resource allocation scheme in LTE-V2V communication networks

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2021年 142卷 153982-153982页

作者： Liu, Zhixin Wang, Yongkang Xie, Yuan-ai Yuan, Yazhou Chan, Kit Yan Yang, Yi Ma, Kai Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Hebei Peoples R China Curtin Univ Dept Elect & Comp Engn Perth WA 6102 Australia

In this paper, a framework is proposed to improve the effectiveness of the long-term-evolution vehicle-to-vehicle (LTE-V2V) communication system, where the uplink channel of the cellular user equipment (CUE) is reused by multiple V2V links. Since the orthogonal channels occupied by each CUEs are multiplexed by multiple V2V links, the serious interference is generated in the co-tier layer and cross-tier layer. In order to minimize the co-channel interference between CUE link and V2V links, an optimized resource sharing scheme is proposed. Firstly, Fuzzy C-means (FCM) algorithm is proposed to perform the clustering based on the geographical location characteristics of V2V links. In the FCM algorithm, the adjacent V2V links are grouped into a cluster to facilitate the solution of the channel allocation problem. Assuring the V2V links in the same cluster do not share the same channel, the adjacent V2V links are avoided to reuse the same channel. On this basis, the use of reasonable channel allocation scheme can effectively reduce the co-channel interference. Considering that the channel state information (CSI) of mobile links is slowly faded, the total system capacity is maximized by leveraging the CSI while the reliability can be guaranteed for all V2V links. The outage probability constraint is used to ensure the reliability of all V2V links. The channel assignment problem of V2V links is formulated as a weighted two-dimensional matching problem, and the interference bipartite graph is constructed. Finally, Kuhn Munkras (km) algorithm is introduced to allocate the uplink orthogonal channel of CUEs for the V2V links in the same class in order to maximize the total system capacity. Numerical simulation results show that the algorithm can improve the total system capacity.

关键词： Vehicular network Resource allocation FCM algorithm km algorithm Graph theory

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Suitability-based Task Assignment in Crowdsourcing Markets 13

Suitability-based Task Assignment in Crowdsourcing Markets

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13th IEEE International Conference on Services Computing (SCC) / 13th IEEE International Conference on Web Services (ICWS)

作者： Wang, Pengwei Chen, Zhen Zhang, Zhaohui Donghua Univ Sch Comp Sci & Technol Shanghai Peoples R China

ISBN: (纸本)9781728187891

Crowdsourcing web services has received much attention in recent years, which has been widely used in many fields, and provides important human computing services for the rapid development of AI. Crowdsourcing knowledge acquisition is one of the most important applications, which includes a series of work such as image annotation and picture classification. However, due to the differences in the difficulty of these tasks and the uncertainty of workers, how to make a reasonable task assignment while ensuring the completion of tasks becomes a big challenge. To this end, we introduce WordNet external knowledge base to help determine the difficulty of picture classification tasks. We refer to the e-sports rank mechanism and use dynamic update strategy to assess the actual ability of workers. A novel criterion affinity based on the weighted Euclidean distance with penalty factor is proposed to measure the suitability between tasks and workers. On this basis, the Kuhn-Munkres (km) algorithm is used to solve the weighted bipartite graph matching problem. Through comparative experiments, the effectiveness of our proposed method is verified.

关键词： crowdsourcing task assignment bipartite graph matching km algorithm

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An Improved km algorithm for Computing Structural Index of DAE System

An Improved KM Algorithm for Computing Structural Index of D...

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12th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)

作者： Zeng, Yan Wu, Xuesong Cao, Jianwen Chinese Acad Sci Inst Software Lab Parallel Software & Computat Sci Software Beijing 100190 Peoples R China

ISBN: (纸本)9780769550602

This paper proposes an improved km algorithm to computing the structural index of linear time-invariant Differential Algebraic Equation (DAE) systems. The problem is of practical significance in index reduction based on structural index of DAE system and combinatorial relaxation theory. This improved km algorithm combines greedy idea and classical km algorithm. It first computes matches as much as possible using greedy technology, and then call km algorithm to search the matches for the unmatched vertices during the step of greedy technology. The improved km algorithm reduces the running time bound by a factor of r, the number of matches searched using greedy algorithm. Generally, the time complexity is O(r(2) + (n - r)n(2)), the optimal time is O(n(2)).

关键词： DAE Index Reduction Structural Index Bipartite Graph Greedy km algorithm

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Dynamic tasks scheduling based on weighted bi-graph in Mobile Cloud Computing

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SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS 2018年 19卷 214-222页

作者： Wang, Tongxiang Wei, Xianglin Liang, Tao Fan, Jianhua Army Engn Univ PLA Nanjing 210007 Jiangsu Peoples R China Nanjing Telecommun Technol Res Inst Nanjing 210007 Jiangsu Peoples R China

The development of mobile computing and rapid growth of mobile applications have promoted the emergence of several edge-based computing paradigms, i.e. Fog computing, edge Computing, which can serve as the middle layer of end-user devices and the powerful cloud. As an implementation subtype of Fog computing, Mobile Cloud Computing (MCC) aims at leveraging limited resources available at network edge in order to enrich mobile applications and promote end-users' experience. Thus, an efficient resource allocation or scheduling scheme is vital for ensuring the effectiveness of MCC. In order to improve the performance of scheduling algorithm and promote its applications in practice, this paper proposes the Dynamic Tasks Scheduling algorithm based on Weighted Bi-graph model (DTSWB), which takes the dynamics of both tasks and providers into consideration. Specially, the scheduling problem is translated to be a maximum weighted bi-graph matching problem and an integer programming model is formulated. Then, the matching problem is solved by DTSWB, which mainly consists of four steps: state information collection of offloaded tasks and service providers, mapping relationship establishment, profit matrix determination and optimal matching based on Kuhn Munkras (km). At last, the effectiveness and validity of the proposed algorithm are verified by a series of simulations and the simulation results show that DTSWB achieves better performance than existing scheduling algorithms.

关键词： Mobile Cloud Computing Task scheduling Weighted bi-graph km algorithm

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Research on D2D Resource Allocation algorithm Based on Improved Fuzzy Clustering 10

Research on D2D Resource Allocation Algorithm Based on Impro...

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10th International Conference on Digital Image Processing (ICDIP)

作者： Liu, Mingshan Liu, Yang Zhou, Yuan Zhang, Wenbo Yu, Yanling Jilin Univ Coll Commun Engn Changchun 130022 Jilin Peoples R China

ISBN: (数字)9781510622005

ISBN: (纸本)9781510622005

D2D communication is widely considered as one of the key technologies in 5G communication systems. The introduction of D2D communication can improve system throughput and spectrum utilization in cellular systems. Considering the scenario that D2D users are larger than cellular users(concerts or gyms), aiming at the problem of co-channel interference caused by D2D users multiplexing uplink resources of cellular users, an improved resource allocation algorithm based on fuzzy clustering is proposed to effectively suppress interference. First, the D2D users are divided into several D2D user groups so that multiple D2D users can reuse the same CU user resources. Subsequently, on the basis of guaranteeing the QoS of cellular users and D2D users, an improved km algorithm is used to match the optimal multiplexing resources for each D2D user group. The simulation results show that the proposed algorithm can effectively reduce the interference between users, and the system throughput has been significantly improved.

关键词： D2D communication fuzzy clustering resource allocation km algorithm

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QoS-Based Channel and Power Optimization algorithm in D2D System 18

QoS-Based Channel and Power Optimization Algorithm in D2D Sy...

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18th IEEE International Conference on Communication Technology (IEEE ICCT)

作者： Tao, Jing Zhu, Qi Hu, Han Nanjing Univ Posts & Telecommun Jiangsu Key Lab Wireless Commun Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538676356

This paper considers the scenario of D2D users sharing cellular user uplink resources, and proposes an optimal resource allocation algorithm in order to improve the system capacity. The algorithm first uses fuzzy C-means (FCM) algorithm to cluster according to the geographic location of the D2D user, so that users in the cluster can not share the channel to restrain the interference between D2D pairs, then use the Kuhn-Munkras (km) algorithm to allocate cellular users' uplink channel for D2D users in the cluster, which means optimally match the D2D user with the cellular user. Finally, Considering the system capacity, the users' quality of service (Qos) requirements and the D2D users' transmit power, a non-cooperative game model is constructed to optimize the transmit power of D2D users and the existence of its Nash equilibrium is proved. Simulation results turn out that it can effectively promote the system capacity while guaranteeing the communication quality of each user.

关键词： device-to-device capacity FCM algorithm km algorithm game theory

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User Pairing and Channel Allocation for Full-Duplex Self-Organizing Small Cell Networks 9

User Pairing and Channel Allocation for Full-Duplex Self-Org...

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9th International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Zhang, Qi Du, Qingwei Zhu, Kun Nanjing Univ Aeronaut & Astronaut Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538620625

This paper proposes a duplex mode selection strategy in a full-duplex (FD) self-organized small cell network. We aim to maximize the sum rate of small cell base stations (SBSs) subject to the quality of service (QoS) of the macro users (MUEs) and the small cell users (SUEs). For this formulated problem, two stages for this selection is considered: user pairing and channel allocation. In the first stage, we propose km algorithm based algorithm for user pairing, while, present a Q-learning based channel allocation to optimize the network performance. Simulation results are provided to validate our proposed scheme by comparing with the scheme in half-duplex (HD) mode and based on other algorithms.

关键词： Small cell Duplex mode km algorithm Interference management Q-learning Self-organization

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A Sort Method to Enhance Significant Spectral Components of Test Set 12

A Sort Method to Enhance Significant Spectral Components of ...

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12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Zhou, Yingbo Kuang, Jishun Hunan Univ Coll Informat Sci & Engn Changsha Hunan Peoples R China

ISBN: (纸本)9781509040933

A sort method is proposed to enhance the significant spectral components of test set. In the field of integrated circuit testing, to calculate significant spectral components, it's necessary to do spectrum analysis for the test set. In this paper, a bipartite graph and weight matrix are constructed based on the test set and its significant spectral components. Therefore, the problem of enhancement of significant spectrum components is transformed into a bipartite graph matching problem that can be solved by km(Kuhn-Munkras) algorithm. After the order adjustment of the test set according to the matching relationship, the correlation between the significant component and test set has been increased, and the significant spectral components are enhanced. Finally, the experimental results on the test set of the ISCAS-89 benchmark circuits show that the coefficients of the sorted test have increased by 9.47% on average, and the incompatible bits between the test set and its significant spectral components have effectively reduced by 14.18% on average.

关键词： spectrum analysis the significant components bipartite graph match km algorithm correlation

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A Sort Method to Enhance Significant Spectral Components of Test Set

A Sort Method to Enhance Significant Spectral Components of ...

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International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery

作者： Yingbo Zhou Jishun Kuang College of Information Science & Engineering Hunan University

ISBN: (纸本)9781509040940

A sort method is proposed to enhance the significant spectral components of test set. In the field of integrated circuit testing, to calculate significant spectral components, it's necessary to do spectrum analysis for the test set. In this paper, a bipartite graph and weight matrix are constructed based on the test set and its significant spectral components. Therefore, the problem of enhancement of significant spectrum components is transformed into a bipartite graph matching problem that can be solved by km (Kuhn-Munkras) algorithm. After the order adjustment of the test set according to the matching relationship, the correlation between the significant component and test set has been increased, and the significant spectral components are enhanced. Finally, the experimental results on the test set of the ISCAS-89 benchmark circuits show that the coefficients of the sorted test have increased by 9.47% on average, and the incompatible bits between the test set and its significant spectral components have effectively reduced by 14.18% on average.

关键词： Spectrum analysis The significant components Bipartite graph match km algorithm Correlation

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STUDIES ON CENTROID TYPE-REDUCTION algorithmS FOR GENERAL TYPE-2 FUZZY LOGIC SYSTEMS

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2015年第6期11卷 1987-2000页

作者： Chen, Yang Wang, Dazhi Ning, Wu Northeastern Univ Inst Power Syst & Power Drives 3-11 Wenhua Rd Shenyang 110819 Liaoning Peoples R China Liaoning Univ Technol Coll Sci Guta Dist 121001 Jinzhou Peoples R China Liaoning Univ Technol Coll Elect & Informat Engn Guta Dist 121001 Jinzhou Peoples R China

Generally speaking, Karnik-Mendel algorithm is a standard way to calculate the centroid and perform type-reduction (TR) for interval type-2 fuzzy sets and systems. In this paper, an efficient centroid type-reduction strategy for general type-2 fuzzy sets is introduced based on Karnik-Mendel (km) algorithm, enhanced Karnik-Mendel (Ekm) algorithm, enhanced iterative algorithm+stopping condition (EIASC). The strategy uses the result of alpha-plane representation, performs the centroid type-reduction on each alpha-plane, and expands type-reduction algorithms for general type-2 fuzzy logic systems. Simulations performed and compared by each of three types of algorithms show that they usually need only several resolution of alpha values such that the defuzzified values converge to real values. Compared with the exhaustive computation method, the method can tremendously decrease the computation complexity from exponential into linear. So it provides the potential application value for general type-2 fuzzy logic systems.

关键词： General type-2 fuzzy logic systems alpha-plane km algorithm Ekm algorithm EIASC

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