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IFIP Networking Conference (IFIP Networking)

作者： Banerjee, Bitan Seetharam, Anand Tellambura, Chintha Univ Alberta Dept Elect & Comp Engn Edmonton AB Canada SUNY Binghamton Comp Sci Dept Binghamton NY 13902 USA

ISBN: (纸本)9783901882944

Most caching strategies in information-centric networks (ICN) primarily focus on pushing popular content to the network edge. As such, these approaches make limited use of caches in the network core, reduce cache utilization due to content duplication and provide limited performance improvement. In this paper, we propose greedy Caching to determine the set of content to be cached at each network node. greedy Caching starts by caching the most popular content, calculated based on the total incoming request stream from users, at the network edge. The algorithm then recalculates the relative popularity of each piece of content based on the request miss stream from downstream nodes to determine the set of content to be cached in the network core. We perform exhaustive simulation in the Icarus simulator [1] using realistic Internet topologies (e.g., GARR, GEANT, and WIDE) and demonstrate that greedy Caching provides significant improvement in content download delay (referred to as latency) over state-of-the-art routing and caching strategies for ICN for a wide range of simulation parameters. Simulation results suggest an improvement of 5-28% in latency and 15-50% improvement in hit rate over state-of-the-art policies.

关键词： greedy algorithm caching information-centric networking latency hit rate hop count

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Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2018年第2期14卷 1-1页

作者： Gao, Honghao Zhang, Kang Yang, Jianhua Wu, Fangguo Liu, Hongsheng Shanghai Univ Ctr Comp Shanghai Peoples R China Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Zhejiang Univ Sci Tech Acad Hangzhou Zhejiang Peoples R China Hithink Royal Flush Informat Network Co Ltd Hangzhou Zhejiang Peoples R China State Grid Liaoning Elect Power Supply Co Ltd Fushun Power Supply Branch Fushun Peoples R China

Hybrid services use different protocols on various networks, such as WIFI networks, Bluetooth networks, 5G communications systems, and wireless sensor networks. Hybrid service compositions can be varied, representing an effective method of integrating into wireless scenarios context-aware applications that can sense mobility via changes in user location and combining services to support target functions. In this article, improved particle swarm optimization is introduced into the quality service evaluation of dynamic service composition to meet the mobility requirements of hybrid networks. First, this work classifies hybrid services into different task groups to generate candidate sets and then interface matching is used to compare the operations of candidate services with user requirements to select the appropriate services. Second, the service composition is determined by the particle swarm optimization simulation process, which aims to identify an optimal plan based on the calculated value from quality of service. Third, considering a change of service repository, when the quality of a composite service is lower than a predefined threshold, the local greedy algorithm and global reconfiguration method are adopted to dynamically restructure composite services. Finally, a set of experiments is conducted to demonstrate the effectiveness of the proposed method for determining the dynamic service composition, particularly when the scale of hybrid services is large. The method provides a technical reference for engineering practice that will fulfill mobile computing needs.

关键词： Hybrid service selection quality of service improved particle swarm optimization greedy algorithm dynamic service composition

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Anchored rectangle and square packings

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DISCRETE OPTIMIZATION 2017年 26卷 131-162页

作者： Balas, Kevin Dumitrescu, Adrian Toth, Csaba D. Calif State Univ Northridge Dept Math Los Angeles CA USA Moorpk Coll Math Dept Moorpark CA USA Univ Wisconsin Milwaukee Dept Comp Sci Milwaukee WI 53201 USA Tufts Univ Dept Comp Sci Medford MA 02155 USA

For points p(1),...,p(n) in the unit square [0,1](2), an anchored rectangle packing consists of interior-disjoint axis-aligned empty rectangles r(1),... ,r(n) subset of [0,1](2) such that point p(i), is a corner of the rectangle r(i) (that is, ri is anchored at p(i)) for i = 1, ..., n. We show that for every set of n points in [0,1](2), there is an anchored rectangle packing of area at least 7/12- O(1/n), and for every n is an element of N, there are point sets for which the area of every anchored rectangle packing is at most 2/3. The maximum area of an anchored square packing is always at least 5/32 and sometimes at most 7/27. The above constructive lower bounds immediately yield constant-factor approximations, of 7/12- epsilon for rectangles and 5/32 for squares, for computing anchored packings of maximum area in O(n log n) time. We prove that a simple greedy strategy achieves a 9/47-approximation for anchored square packings, and 1/3 for lower-left anchored square packings. Reductions to maximum weight independent set (MWIS) yield a QPTAS for anchored rectangle packings in exp(poly(epsilon(-1) log n)) time and a PTAS for anchored square packings in nO(1/epsilon) time. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Rectangle packing Anchored rectangle greedy algorithm Charging scheme Approximation algorithm

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Decentralized Task Allocation Using Local Information Consistency Assumptions

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2017年第2期14卷 103-122页

作者： Johnson, Luke B. Choi, Han-Lim Ponda, Sameera S. How, Jonathan P. MIT Dept Aeronaut & Astronaut 77 Mass AveRm 33-326 Cambridge MA 02139 USA Korea Adv Inst Sci & Technol Dept Aerosp Engn 291 Daehak RoBldg N7-2 Daejeon 34141 South Korea Alphabet Inc 1600 Amphitheater Parkway Mountain View CA 94043 USA

The information available to agents using decentralized task allocation algorithms plays an important role in how assignments can be constructed. The requirement that information be globally consistent across all agents can be leveraged to allow cooperation on coupled objectives. In environments where global information consistency assumptions are difficult to enforce, the alternative is to rely only on a local best estimate of the global information state, which is referred to here as local information consistency. algorithms that assume only this local information consistency will have reduced optimization capabilities compared to their global information assumption counterparts. Specifically, if objective functions are non-submodular, local information algorithms may produce arbitrarily bad allocations or, in the case of many algorithms, may not even converge. The key contribution of this paper is an algorithm termed bid warped consensus-based bundle algorithm that converges for all deterministic objective functions and has nontrivial performance guarantees for submodular and some non-submodular objective functions. Included in this paper is an analytical analysis of both convergence and performance of the algorithm, as well as a numerical comparison to several other competing local and global information approaches.

关键词： Consensus algorithm greedy algorithm Convergence Analysis K Capture

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Theoretical analysis of spectrum flattening in fiber laser oscillator

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OPTICS COMMUNICATIONS 2017年 383卷 460-466页

作者： Shi, Chen Wang, Xiaolin Zhou, Pu Wang, Zefeng Xu, Xiaojun Lu, Qisheng Natl Univ Def Technol Coll Optoelect Sci & Engn Changsha 410073 Hunan Peoples R China Hunan Prov Key Lab High Energy Laser Technol Changsha Hunan Peoples R China Hunan Prov Collaborat Innovat Ctr High Power Fibe Changsha Hunan Peoples R China

The flatness of laser spectrum is important in many applications. In this manuscript, a method of acquiring flattened spectrum directly from a fiber oscillator by optimizing the reflective spectrum of Fiber Bragg Gratings (FBG) was demonstrated and optimized result at wavelength around 1064 nm and 1080 nm was presented. An optimization path to alter the reflectivity of FBGs using greedy algorithm was interpreted by analyzing the single-trip gain inside the resonant cavity. Our method has a guiding significance of controlling the output spectrum of laser oscillator using FBGs. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Fiber laser Fiber Bragg grating Optimization greedy algorithm Spectrum flattening

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An Energy-Efficient Balancing Scheme in Wireless Sensor Networks

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WIRELESS PERSONAL COMMUNICATIONS 2017年第1期94卷 17-29页

作者： Kim, Hye-Young Kim, Jinsul Hongik Univ Sch Game Game Software 2639 Sejong Ro Jochiwon Eup 339701 Chungcheongnam South Korea Chonnam Natl Univ Dept Elect & Comp Engn Gwangju South Korea

A typical wireless sensor network is conceived as bring a very large collection of low-powered, homogeneous nodes that remain stativ post-deployment and forward sensed data to a single sink via multi-hop communication. During the recent years, many energy-efficient load balancing protocols have been proposed for wireless sensor networks. Because a wireless networks consists of a large number of nodes with limited resources, the load balancing protocol is one of the key issues which can be solve the tradeoff between the service capacity and energy efficience. Load balancing protocols typically employ only a network capacity oriented approach in the next hop node is selected on adjacent or network information. This approach draw into a large overhead when the accurate adjacent information is needed for efficient and reliable routing. When an application service is caused large interaction between the adjacent nodes, the previous load balancing protocols without considering this issue were re-allocated the adjacent nodes and the other adjacent is re-allocated another region. This is not efficient for network performance because the previous protocols are generated the large overhead by increased routing and overhead. So, we propose a user-oriented load balancing scheme for an energy-efficient load balancing in wireless networks which is based on allocate load on wireless sensor nodes proportionally to each of the agent's capacity and user-oriented approach. This proposed scheme is combined dynamic provisioning algorithm based on greedy graph and user oriented load balancing scheme for maintain of the performance and stability of distributed system in wireless sensor networks. We address the key functions for our proposed scheme and simulate the efficiency of our proposed scheme using mathematical analyze.

关键词： Load balancing User oriented Energy-efficient Wireless sensor networks greedy algorithm

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Selective cooperation with untrusted relays for physical-layer security in wireless multipair two-way relaying networks

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TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES 2018年第6期29卷 e3313-e3313页

作者： Zhao, Tantan Li, Guobing Lyu, Gangming Zhang, Guomei Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian 710049 Shaanxi Peoples R China

In this paper, the selective cooperation with untrusted relays is studied for wireless multipair two-way relay networks. We first investigate the feasibility of secure transmission in the presence of cooperative but untrusted relays and then formulate a general optimization problem of secrecy sum-rate maximization under the constraints of relay selection. By decomposing the original problem into solvable subproblems, we develop a low-complexity greedy algorithm for selective cooperation, in which the untrusted relays are selected as cooperators or the potential eavesdroppers according to the overall contributions to the secrecy sum rate. Simulation results reveal that the proposed greedy algorithm for selective cooperation with untrusted relays achieves performance gain both in instantaneous and average secrecy sum rate and that the algorithm can converge quickly with the iterations.

关键词： relay greedy algorithm secure transmission Privacy original problem wireless

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An improved geometric algorithm for indoor localization

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2018年第3期14卷 1-1页

作者： Yang, Junhua Li, Yong Cheng, Wei Northwestern Polytech Univ Sch Elect & Informat Xian 710129 Shaanxi Peoples R China

Indoor localization system using receive signal strength indicator from wireless access point has attracted lots of attention recently. Geometric method is one of the most widely used spatial graph algorithms to locate object in an indoor environment, but it does not achieve good results when it is applied to a limited amount of valid data, especially when using the trilateration method. On the other hand, localization based on fingerprint can achieve high accuracy but need to pay heavy manual labor for fingerprint database establishment. In this article, we propose a bilateral greed iteration localization method based on greedy algorithm in order to use all of the effective anchor points. Comparing to trilateration, fingerprint, and maximum-likelihood method, the bilateral greed iteration method improves the localization accuracy and reduces complexity of localization process. The method proposed, coupled with measurements in a real indoor environment, demonstrates its feasibility and suitability, since it outperforms trilateration and maximum-likelihood receive signal strength indicator-based indoor location methods without using any radio map information nor a complicated algorithm. Extensive experiment results in a Wi-Fi coverage office environment indicate that the proposed bilateral greed iteration method reduces the localization error, 63.55%, 9.93%, and 47.85%, compared to trilateration, fingerprint, and maximum-likelihood method, respectively.

关键词： Indoor localization Wi-Fi greedy algorithm trilateration K-NN

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PBC: Polygon-Based Classifier for Fine-Grained Categorization

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IEEE TRANSACTIONS ON MULTIMEDIA 2017年第4期19卷 673-684页

作者： Huang, Chao Li, Hongliang Xie, Yurui Wu, Qingbo Luo, Bing Univ Elect Sci & Technol China Sch Elect Engn Chengdu 611731 Peoples R China

Fine-grained categorization is a challenging task mainly due to two factors: first, objects share similar appearances between different categories;second, objects present significant pose variation within the same category. To address these challenges, we propose a method to automatically detect discriminative and pose-invariant regions, which is referred to as a polygon-based classifier (PBC). In the first stage, we generate a set of polygons that are composed of multiple parts. For each polygon, a classifier is trained based on deep features of a convolutional network. Then, a greedy algorithm is employed to select the discriminative and complementary polygon-based classifiers that deliver highest classification accuracy for fine-grained object categories. In the second stage, the confusing classes of the first stage are selected and employed to train the polygon-based classifiers. Then, a greedy algorithm is employed to select discriminative classifiers. For the test images, we use the classifiers trained in the first stage to obtain a coarse result. Then, the classifiers of the second stage are adopted to distinguish the confusing classes of the coarse result. In our experiments, the proposed approach is evaluated on three well-known fine-grained datasets. The experiments show that our approach outperforms the state-of-the-art methods.

关键词： Polygon-based classifier fine-grained categorization greedy algorithm coarse-to-fine method

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I/O-efficient calculation of H-group closeness centrality over disk-resident graphs

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INFORMATION SCIENCES 2017年 400卷 105-128页

作者： Zhao, Junzhou Wang, Pinghui Lui, John C. S. Towsley, Don Guan, Xiaohong Chinese Univ Hong Kong Dept Comp Sci & Engn Shatin Hong Kong Peoples R China Xi An Jiao Tong Univ MOE Key Lab Intelligent Networks & Network Secur Xian 710049 Peoples R China Univ Massachusetts Dept Comp Sci Amherst MA 01003 USA

We introduce H-group closeness centrality in this work. H-group closeness centrality of a group of nodes measures how close this node group is to other nodes in a graph, and can be used in numerous applications such as measuring the importance and influence of a group of users in a social network. When a large graph contains billions of edges that cannot reside entirely in a computer's main memory, computing and maximizing H-group closeness centrality both become challenging. In this work, we present a systematic solution for efficiently computing and maximizing H-group closeness centrality in large disk resident graphs, only using a common PC. Our solution leverages a probabilistic counting method to efficiently estimate H-group closeness with high accuracy, rather than exhaustively computing it in an exact fashion. Furthermore, we design an I/O-efficient greedy algorithm to find a node group that approximately maximizes H-group closeness centrality in a graph. Our algorithm exploits several appealing properties of the defined H-group closeness measure to reduce the computational cost of handling a disk-resident graph. Extensive evaluation on large real-world and synthetic graphs demonstrates the efficiency of our proposed method. For example, our proposed I/O-efficient greedy algorithm is about 300 times faster than a simple multi-pass method on the Twitter graph with 1.4 billion edges. This reduces the running time of identifying one group member from nearly an hour to less than 20 s on average. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Online social network Group centrality Disk-resident graph Submodularity greedy algorithm

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