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grouping algorithm for Partner Selection in Cooperative Transmission

WIRELESS PERSONAL COMMUNICATIONS 2011年第1期60卷 43-67页

作者： Ng, Cho Yiu Lok, Tat Ming Chinese Univ Hong Kong Dept Informat Engn Shatin Hong Kong Peoples R China

The partner selection problem for cooperative transmission is considered. Our objective is sum power minimization. We provide a simple optimal rate allocation algorithm for two cooperating node pairs and closed-form optimal rate allocations for some cases. With these results, we determine the partner for each node pair by Gabow's algorithm. For a large number of nodes, we propose the grouping algorithm which is near-optimal but reduces the communication and computational overhead. We show the significant improvement of power consumption by our scheme and the fast convergence of the grouping algorithm through simulations.

关键词： Cooperative transmission Sum power minimization Optimal rate allocation Partner selection grouping algorithm

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Handoff Minimization Through a Relay Station grouping algorithm With Efficient Radio-Resource Scheduling Policies for IEEE 802.16j Multihop Relay Networks

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2010年第5期59卷 2185-2197页

作者： Yang, Shun-Ren Kao, Chien-Chi Kan, Wai-Chi Shih, Tzung-Chin Natl Tsing Hua Univ Dept Comp Sci Hsinchu 300 Taiwan Natl Tsing Hua Univ Inst Commun Engn Hsinchu 300 Taiwan Synology Inc Taipei 10351 Taiwan

The IEEE 802.16j standard has been developed to provide performance enhancement to the existing IEEE 802.16e network by incorporating the multihop relay (MR) technology. However, frequent handoffs and low spectrum-utilization issues that were not encountered in IEEE 802.16e may be incurred in IEEE 802.16j. The relay station (RS) grouping is one optional mechanism in the IEEE 802.16j MR standard to overcome these problems. The concept of RS grouping is to group neighboring RSs together to form an RS group, which can be regarded as a logical RS with larger coverage. In this paper, we investigate RS grouping performance enhancement in terms of throughput and handoff frequency. This paper designs an RS grouping algorithm to minimize handoffs by utilizing a greedy grouping policy: RS pairs with higher handoff rates will have higher priority for selection. The simulation results show that the handoff frequency of the considered MR network can significantly be reduced, and suitable RS grouping patterns can be derived using our grouping algorithm. In addition, we propose two centralized scheduling policies, i.e., the throughput-first (TF) policy to maximize the system throughput and the delay-first (DF) policy to minimize the average packet delay. By integrating our RS grouping algorithm and centralized scheduling algorithms, the simulation results indicate that, for the case of fixed users, groupings with smaller group sizes can result in better throughput performance. However, when user mobility is considered, the throughput value increases as the group size increases. Furthermore, we also show that the DF policy can both minimize the average packet delay and provide the fairness property among users with different traffic loads.

关键词： grouping algorithm IEEE 802.16j multihop relay (MR) scheduling policy WiMAX

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Intelligent 3D packing using a grouping algorithm for automotive container engineering

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JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 2014年第2期1卷 140-151页

作者： Joung, Youn-Kyoung Do Noh, Sang Sungkyunkwan Univ Dept Syst Management Engn 300 Cheoncheon Dong Suwon Gyeonggi South Korea

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line- side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials;further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.

关键词： Packing 3D CAD model grouping algorithm Container engineering

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A grouping algorithm of HELPERS in PEER-TO-PEER VIDEO-ON-DEMAND SYSTEMS

A GROUPING ALGORITHM of HELPERS in PEER-TO-PEER VIDEO-ON-DEM...

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12th International Conference on Advanced Communication Technology (ICACT) - ICT for Green Growth and Sustainable Development

作者： Li, Xia Zou, Rua Zhao, Xinchao Yang, Fangchun Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Beijing Univ Posts & Telecommun Sch Sci Beijing Peoples R China

ISBN: (纸本)9788955191455

Peer-to-peer (P2P) content distribution effectively solves the problem of large-scale streaming media delivery. But the performance of a P2P system is primarily bottlenecked, because the upload bandwidth of the participating peers is limited. Using helpers in the P2P system utilizes upload bandwidth of those idle peers uninterested in the delivered content, which further improves the performance of P2P systems, and the feasibility and validity have been testified [1]. Aiming at the p2p video-on-demand system, this thesis designs a novel grouping algorithm of helpers. In order to make more rational and effective use of helpers, the algorithm divides the helpers into different groups according to the number of each video's users, thus reducing the average view delay of whole system and improving the utilization rate of the helpers, reinforcing watch experience for users of the system. Analysis and simulation results corroborate the effectiveness of the proposed algorithm in the paper.

关键词： P2P streaming media video-on-demand helpers grouping algorithm

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A QoE-based DASH Multicast grouping algorithm for Mobile Edge Computing

A QoE-based DASH Multicast Grouping Algorithm for Mobile Edg...

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IEEE/CIC International Conference on Communications in China (ICCC)

作者： Xu, Lei Tan, Xiaobin Li, Simin Wang, Shunyi Univ Sci & Technol China Dept Automat Sch Informat Sci & Technol AnHui Prov Key Lab Future Networks Hefei Anhui Peoples R China

ISBN: (纸本)9781728173276

Dynamic Adaptive Streaming over HTTP (DASH) can adaptively select the appropriate video bitrate for mobile users. Mobile Edge Computing (MEC) scenario is of great benefit to improve the performance of mobile networks by providing computing and storage capabilities. And the utilization of spectrum resources can be improved by multicast transmission, but the performance of the multicast transmission will be directly affected by the selected grouping algorithm. Therefore, we propose a grouping algorithm for DASH multicast in MEC to complete a more reasonable grouping of users, thereby improving the Quality of Experience (QoE) of mobile users. QoE is not only our optimization goal but also the grouping basis of the algorithm proposed in this paper. We dynamically group multiple users in the same Multicast Broadcast Single Frequency Network (MBSFN) area in three dimensions based on the three components of QoE. The simulation results show that the proposed grouping algorithm performs well in QoE and fairness.

关键词： DASH MEC Multicast grouping algorithm QoE

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A Regular Expression grouping algorithm Based on Simulated Annealing algorithm 8

A Regular Expression Grouping Algorithm Based on Simulated A...

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8th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC)

作者： Cai, Liangwei Mao, Zhiqiang Shenzhen Univ Coll Informat Engn Shenzhen Peoples R China

ISBN: (纸本)9781538657744

In order to solve the problem of large amount of memory space occupied by Deterministic Finite Automaton(DFA) states expansion in regular expression merge conversion, an important method is that it divides n regular expressions into m groups in an reasonable way. one grouping optimization algorithm based on improved simulated annealing algorithm (GRE-SAA) is proposed in this paper. We redefine the annealing procession and divide it into high temperature stage and low temperature stage with corresponding solution transformation strategy, and a grouping algorithm based on expansion coefficient is proposed. The proposed algorithm can significantly reduce the number of DFA states and reduce the number of groups as well as getting a more uniform grouping result compared with other algorithms.

关键词： DFA regular expression GRE-SAA expansion coefficient grouping algorithm

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A Novel Suboptimal SDMA grouping algorithm for Multiuser MIMO-OFDMA Systems 22

A Novel Suboptimal SDMA Grouping Algorithm for Multiuser MIM...

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22nd Iranian Conference on Electrical Engineering (ICEE)

作者： Majidzadeh, Mohammad Eslami, Mohsen Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

ISBN: (纸本)9781479944095

Wireless communication systems based on multiple input-multiple output (MIMO) in combination with orthogonal frequency division multiple access (OFDMA) and space division multiple access (SDMA) are flexible, spectrally efficient and of high capacity. These systems can allocate frequency, time, and space resources adaptively among mobile stations (MSs). In order to perform an effective resource allocation (RA), MSs must be organized into groups containig MSs with best average sum rate. Since frequency and time resources could be designed orthogonal, the problem of grouping remains only for the space resource. Complexity of the grouping algorithm is also an issue, especially when the number of MSs is high. In this paper, a novel suboptimal grouping algorithm is proposed. A new metric is also introduced to measure the efficiency of a RA strategy.

关键词： Resource allocation grouping algorithm SDMA OFDMA MIMO

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A novel geometric-based bistatic range grouping algorithm for multi-target localization in distributed MIMO radar

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 253卷

作者： Kang, Seyoung Shin, Hyuksoo Chung, Wonzoo Korea Univ Dept Comp Sci & Engn Seoul South Korea Agcy Def Dev ADD Daejeon South Korea Korea Univ Dept Artificial Intelligence Seoul South Korea

In this paper, a novel bistatic range grouping algorithm is proposed in order to localize multiple targets in distributed multiple -input multiple -output (MIMO) radar systems. In a distributed MIMO radar, target localization is performed based on bistatic ranges, the distances between antennas through a target, without directional information, and grouping bistatic ranges with respect to the target is a crucial step to estimate multiple targets efficiently. In contrast to the existing grouping schemes that use tentative target estimation or complicated joint bistatic range grouping and target estimation, the proposed algorithm uses only the geometric property of bistatic ranges, resulting in computationally efficient and robust grouping algorithm without noise enhancement, especially for realistic noisy environments where other existing grouping algorithms often fail. The performance of the proposed scheme is confirmed by evaluating the probability of miss detection and the probability of false alarm through numerical simulations for various environments including indirect paths and blocked paths. The root mean square error performance of the multi -target localization using the proposed bistatic grouping algorithm is also presented for realistic noisy environments.

关键词： Distributed multiple-input multiple-output (MIMO) radar Multi-target localization Bistatic range (BR) grouping algorithm

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Efficient Regular Expression grouping algorithm Based on Label Propagation

Efficient Regular Expression Grouping Algorithm Based on Lab...

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2015 4th National Conference on Electrical,Electronics and Computer Engineering(NCEECE 2015)

作者： Xi Chen Shuqiao Chen Ming Mao National Digital Switching System Engineering & Technology Research Center

ISBN: (纸本)9781510819085

Regular expression grouping is the practical way to address the state explosion problem of Deterministic Finite Automaton(DFA). Previous grouping algorithms have poor grouping time, and difficult to meet application needs. In this work, we present an efficient regular expression grouping algorithm based on label propagation. Through the deterministic initial grouping and based on similarity of the propagation process to achieve faster convergence. Experimental results show that. Compared with other algorithms, GBLP algorithm has the minimum total number of states and grouping time for the same number of groups.

关键词： regular expression deep packet inspection grouping algorithm label propagation

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Comparison of grouping algorithms to increase the sample size for statistical process control

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SN APPLIED SCIENCES 2020年第5期2卷 935页

作者： Greipel, Jonathan Simon Nottenkaemper, Gina Schmitt, Robert Heinrich Prod Engn Cluster Campus Blvd 30 D-52074 Aachen Germany Rhein Westfal TH Aachen Chair Prod Metrol & Qual Management Lab Machine Tools & Prod Engn WZL Aachen Germany

In this study, we present and compare four grouping algorithms to combine samples from low volume production processes. This increases their sample sizes and enables the application of Statistical Process Control (SPC) to low volume production processes. To develop the grouping algorithms, we define different grouping criteria and a general grouping process. To identify which algorithm is optimal, we deduct following requirements on the algorithms from real production datasets: their ability to handle different amount of characteristics and sample sizes within each characteristic as well as being able to separate characteristics possessing distributions with different spreads and locations. To check the fulfillment of these requirements, we define two performance indices and conduct a full-factorial Design of Experiments. We achieve the performance indices for each algorithm by using simulations with artificial data incorporating the aforementioned requirements. One index rates the achieved group sizes and the other one the compactness within groups and the separation between groups. To validate the applicability of grouping algorithms within SPC, we apply real production data to the grouping algorithms and control charts. The result of this analysis shows that the grouping algorithm based on cluster analysis and splitting exceeds the other algorithms. In conclusion, the grouping algorithms enable the application of SPC to small sample sizes. This provides companies, which produce in low volumes, with new means of reducing scrap, generating process knowledge and increasing quality.

关键词： grouping algorithm SPC Low volume production Pooling of data algorithm performance

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