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A Methodology for the design of Self-Optimizing, Decentralized Content-Caching Strategies

IEEE-ACM TRANSACTIONS ON NETWORKING 2016年第5期24卷 2634-2647页

作者： Kvaternik, Karla Llorca, Jaime Kilper, Daniel Pavel, Lacra Univ Toronto Edward S Rogers Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada Alcatel Lucent Bell Labs Holmdel NJ 07733 USA

We consider the problem of efficient content delivery over networks in which individual nodes are equipped with content caching capabilities. We present a flexible methodology for the design of cooperative, decentralized caching strategies that can adapt to real-time changes in regional content popularity. This design methodology makes use of a recently proposed reduced consensus optimization scheme, in which a number of networked agents cooperate in locating the optimum of the sum of their individual, privately known objective functions. The outcome of the design is a set of dynamic update rules that stipulate how much and which portions of each content piece an individual network node ought to cache. In implementing these update rules, the nodes achieve a collectively optimal caching configuration through nearest-neighbor interactions and measurements of local content request rates only. Moreover, individual nodes need not be aware of the overall network topology or how many other nodes are on the network. The desired caching behavior is encoded in the design of individual nodes' costs and can incorporate a variety of network performance criteria. Using the proposed methodology, we develop a set of content-caching update rules designed to minimize the energy consumption of the network as a whole by dynamically trading off transport and caching energy costs in response to changes in content demand.

关键词： Adaptive algorithms algorithm design content distribution content-centric networking decentralized coordination control distributed algorithms distributed content caching distributed optimization energy-efficient ICTs intelligent networks meshed networks multiagent systems nearest-neighbor interactions reduced consensus optimization self-optimizing networks

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Natural language processing of online propaganda as a means of passively monitoring an adversarial ideology

Natural language processing of online propaganda as a means ...

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作者： Raven R. Holm Naval Postgraduate School

学位级别：硕士

Online propaganda embodies a potent new form of warfare; one that extends the strategic reach of our adversaries and overwhelms analysts. Foreign organizations have effectively leveraged an online presence to influence elections and distance-recruit. The Islamic State has also shown proficiency in outsourcing violence, proving that propaganda can enable an organization to wage physical war at very little cost and without the resources traditionally required. To augment new counter foreign propaganda initiatives, this thesis presents a pipeline for defining, detecting and monitoring ideology in text. A corpus of 3,049 modern online texts was assembled and two classifiers were created: one for detecting authorship and another for detecting ideology. The classifiers demonstrated 92.70% recall and 95.84% precision in detecting authorship, and detected ideological content with 76.53% recall and 95.61% precision. Both classifiers were combined to simulate how an ideology can be detected and how its composition could be passively monitored across time. Implementation of such a system could conserve manpower in the intelligence community and add a new dimension to analysis. Although this pipeline makes presumptions about the quality and integrity of input, it is a novel contribution to the fields of Natural Language Processing and Information Warfare.

关键词： data mining natural language processing machine learning algorithm design information warfare propaganda

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Reflections on Organization and Implementation of algorithm-design-based Courses

Reflections on Organization and Implementation of Algorithm-...

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7th International Conference on Computer Science and Education

作者： Shen, Wei Zhao, Danya Zheng, Xiaoling Capital Univ Econ & Business Coll Informat Beijing Peoples R China

ISBN: (纸本)9781467302395

algorithm design ability is the most fundamental and principal ability for students majoring in computer. algorithm design courses give stress over abstraction, practice and creativity of the knowledge. Therefore, the difficulty in teaching is also increased to certain extent. With aim at the features of algorithm design courses, the thesis proposes that the principle of overall arrangement, good foundation and making progresses gradually shall be observed in organizing the courses. Also, the methods for enhancing students' interests, cultivating the ability to analyze questions abstractly and solve actual problems during the implementation of courses are discussed in great detail. Finally, the guiding points in practical teaching are also summarized in the paper.

关键词： algorithm design Organization and implementation of teachin Computer specialty Practice

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design and application of a three-dimensional direction recognition algorithm based on a hardware platform

Design and application of a three-dimensional direction reco...

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2016 3nd International Conference on Energy Science and Applied Technology (ESAT 2016)

作者： Feng Lu Wei Xie Haoying Wu Danfeng Wang Key Laboratory of Fiber Optic Sensing Technology and Information Processing Ministry of Education College of Information Engineering Wuhan University of Technology

A robot with tactile sensors can perceive many physical features of the target object（***,softness,texture,temperature,stiffness）,which greatly improves situational awareness and real-time decision-making ability in unknown *** them,the recognition of three-dimensional direction plays a very important role in human–computer *** main aims of this paper are as follows:（1） a three-dimensional hardware platform was first built;（2） based on the hardware platform,the Sage–Husa adaptive Kalman filter algorithm was used to filter the data collected;（3） RBF（radial basis function） neural network algorithm was used to recognize the three-dimensional *** results indicated that in the three-dimensional direction recognition,the average error of nonlinear prediction based on the RBF neural network is 2.01 × 10,the average accuracy is 94.6%,and the highest accuracy rate is 97.6%.

关键词： intelligent robot Sage–Husa adaptive Kalman filter neural networks three-dimensional direction recognition algorithm design

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Optimal Rate Schedules with Data Sharing in Energy Harvesting Communication Systems

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SENSORS 2017年第12期17卷 2958-2958页

作者： Wu, Weiwei Li, Huafan Shan, Feng Zhao, Yingchao Southeast Univ Sch Comp Sci & Engn Nanjing 210018 Jiangsu Peoples R China Caritas Inst Higher Educ Sch Comp & Informat Sci Hong Kong 999077 Hong Kong Peoples R China

Despite the abundant research on energy-efficient rate scheduling polices in energy harvesting communication systems, few works have exploited data sharing among multiple applications to further enhance the energy utilization efficiency, considering that the harvested energy from environments is limited and unstable. In this paper, to overcome the energy shortage of wireless devices at transmitting data to a platform running multiple applications/requesters, we design rate scheduling policies to respond to data requests as soon as possible by encouraging data sharing among data requests and reducing the redundancy. We formulate the problem as a transmission completion time minimization problem under constraints of dynamical data requests and energy arrivals. We develop offline and online algorithms to solve this problem. For the offline setting, we discover the relationship between two problems: the completion time minimization problem and the energy consumption minimization problem with a given completion time. We first derive the optimal algorithm for the min-energy problem and then adopt it as a building block to compute the optimal solution for the min-completion-time problem. For the online setting without future information, we develop an event-driven online algorithm to complete the transmission as soon as possible. Simulation results validate the efficiency of the proposed algorithm.

关键词： wireless data transmission rate schedule data sharing energy-efficiency energy harvesting algorithm design

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Large-scale linear regression: Development of high-performance routines

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APPLIED MATHEMATICS AND COMPUTATION 2016年 275卷 411-421页

作者： Frank, Alvaro Fabregat-Traver, Diego Bientinesi, Paolo Rhein Westfal TH Aachen AICES D-52062 Aachen Germany

In statistics, series of ordinary least squares problems (OLS) are used to study the linear correlation among sets of variables of interest;in many studies, the number of such variables is at least in the millions, and the corresponding datasets occupy terabytes of disk space. As the availability of large-scale datasets increases regularly, so does the challenge in dealing with them Indeed, traditional solvers-which rely on the use of "black-box" routines optimized for one single OLS-are highly inefficient and fail to provide a viable solution for big-data analyses. As a case study, in this paper we consider a linear regression consisting of two-dimensional grids of related OLS problems that arise in the context of genome-wide association analyses, and give a careful walkthrough for the development of OLS-GRID, a high-performance routine for shared-memory architectures;analogous steps are relevant for tailoring OLS solvers to other applications. In particular, we first illustrate the design of efficient algorithms that exploit the structure of the OLS problems and eliminate redundant computations;then, we show how to effectively deal with datasets that do not fit in main memory;finally, we discuss how to cast the computation in terms of efficient kernels and how to achieve scalability. Importantly, each design decision along the way is justified by simple performance models. OLS-GRID enables the solution of 10(11) correlated OLS problems operating on terabytes of data in a matter of hours. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Linear regression Ordinary least squares algorithm design Out-of-core Parallelism Scalability

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Signal and interference alignment via message passing for MIMO interference channels

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TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES 2016年第3期27卷 392-407页

作者： Fouladgar, Ali Mohammad Simeone, Osvaldo Park, Seok-Hwan Sahin, Onur Shamai (Shitz), Shlomo New Jersey Inst Technol CWCSPR ECE Dept Newark NJ 07102 USA Samsung Elect Suwon Kyeonggi Do South Korea InterDigital Inc Melville NY 11747 USA Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

A novel algorithm for the design of linear precoding and equalisation in multiple-input multiple-output interference channels is proposed that is based on the minimisation of the interference-plus-signal leakage. The interference-plus-leakage criterion, unlike the more conventional interference leakage metric for interference alignment, considers not only the power of the interference caused to unintended receivers but also the power of the useful signal that is spilled' outside the receiving subspace of the intended receiver. The proposed algorithm tackles the problem via the application of the min-sum message passing algorithm to a factor graph constructed on the interference graph of the network. The scheme can be seen as a generalisation of a number of previously proposed algorithms, including the alternating optimisation schemes for interference leakage minimisation and interference-plus-signal leakage minimisation. The approach inherits the advantages of these schemes of returning unitary precoding and equalisation matrices, hence simplifying the task of low-rate feedback to the transmitters and receivers, and of allowing a distributed implementation. Numerical results show that the scheme provides advantages in terms of achievable sum-rate and convergence with respect to the mentioned existing related strategies. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： algorithm design Scheme Interference channels useful signal Factor Graph signals Power Disturbances Receivers Interference graphs multiple input multiple output systems

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Recent advances in metaheuristic algorithms: Does the Makara dragon exist?

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JOURNAL OF SUPERCOMPUTING 2016年第10期72卷 3764-3786页

作者： Fong, Simon Wang, Xi Xu, Qiwen Wong, Raymond Fiaidhi, Jinan Mohammed, Sabah Univ Macau Dept Comp & Informat Sci Zhuhai Macau Peoples R China Univ New South Wales Sch Comp Sci & Engn Sydney NSW 2052 Australia Lakehead Univ Dept Comp Sci Thunder Bay ON Canada

Metaheuristic algorithms (MHs) have a long history that can be traced back to genetic algorithms and evolutionary computing in the 1950s. Since February 2008, with the birth of the Firefly algorithm, MHs started to receive attention from researchers around the globe. Variants and new species of MH algorithms have bloomed like sprouts after rain. However, the necessity for creating more new species of such algorithms is questionable. It can be observed that these algorithms are fundamentally made up of several widely used core components. By explaining these components, the underlying design for a collection of the so-called modern MH optimisation algorithms is revealed. In this paper, the core components in some of the more popular MH algorithms are reviewed, thereby debunking the myths of their novelty, and perhaps dampening claims that something really 'new' is invented simply by branding an MH search method with the name of another living creature. Counterintuitive experimentations have shown that by taking snapshots, anyone can show some improvements of an MH over another in some situation. Mixing certain components up indeed adds advantage over the original MH. The same goes to extending MH with slight functional modification. This work also serves as a general guideline and a reference for any algorithm architect who wants to create a new MH algorithm in the future.

关键词： Metaheuristics Search methods Swarm intelligence algorithm design

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Joint Flow Routing and DoF Allocation in Multihop MIMO Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2016年第3期15卷 1907-1922页

作者： Qin, Xiaoqi Yuan, Xu Shi, Yi Hou, Y. Thomas Lou, Wenjing Midkiff, Scott F. Virginia Polytech Inst & State Univ Blacksburg VA 24061 USA Intelligent Automat Inc Rockville MD 20855 USA

Recently, degree-of-freedom (DoF)-based models have been widely used to study MIMO network performance. Existing DoF-based models differ in their interference cancellation (IC) behavior and many of them suffer from either loss of solution space or possible infeasible solutions. To overcome these limitations, a new DoF-based model, which employs an IC scheme based on node-ordering was proposed. In this paper, we apply this new DoF IC model to study a throughput maximization problem in a multihop MIMO network. The problem formulation involves joint consideration of flow routing and DoF allocation and falls in the form of a mixed-integer linear program (MILP). Our main contribution is an efficient polynomial time algorithm that offers a competitive solution to the MILP through a series of linear programs (LPs). The algorithm employs a sequential fixing framework to obtain an initial feasible solution and then improves the solution by exploiting: 1) the impact of node ordering on DoF consumption for IC at a node and 2) route diversity in the network. Simulation results show that the solutions obtained by our proposed algorithm are competitive and feasible.

关键词： Network throughput optimization algorithm design multi-hop MIMO networks

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Joint power and subcarrier allocation for multicarrier full-duplex systems

Joint power and subcarrier allocation for multicarrier full-...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yan Sun Derrick Wing Kwan Ng Robert Schober Institute for Digital Communications Friedrich-Alexander-University Erlangen-Nurnberg (FAU) Germany School of Electrical Engineering and Telecommunications The University of New South Wales Australia

ISBN: (纸本)9781509041183

In this paper, we investigate resource allocation for multicarrier communication systems employing a full-duplex base station for serving multiple half-duplex downlink and uplink users simultaneously. We study the joint power and subcarrier allocation design for the maximization of the weighted sum throughput of the system. The algorithm design is formulated as a mixed combinatorial non-convex optimization problem and obtaining the globally optimal solution may require prohibitively high computational complexity. Therefore, a low computational complexity suboptimal iterative algorithm exploiting successive convex approximation is proposed to obtain a locally optimal solution. Simulation results confirm that the proposed suboptimal algorithm obtains a substantial improvement in system throughput compared to various existing baseline schemes.

关键词： Configuration design full-duplex system Subcarriers duplex system algorithm design COMMUNICATION SYSTEMS weight sums optimal solution Resource utilization Joints Joints complexity classes

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