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MPSICA: An intelligent routing recovery scheme for heterogeneous wireless sensor networks

information Sciences 2015年 308卷 49-60页

作者： Ding, Yongsheng Hu, Yifan Hao, Kuangrong Cheng, Lijun Engineering Research Center of Digitized Textile and Apparel Technology Ministry of Education Donghua University Shanghai 201620 China College of Information Sciences and Technology Donghua University Shanghai 201620 China Shandong Computer Science Center (National Supercomputer Center in Jinan) Jinan 250014 China Shandong Provincial Key Laboratory of Computer Network Jinan 250014 China

To address the fault-tolerant recovery problem in a heterogeneous wireless sensor network consisting of several resource-rich supernodes, and a large number of energy-constrained ordinary sensor nodes, we propose a multi-particle-swarm immune cooperative algorithm (MPSICA) to provide intelligent routing recovery scheme. The MPSICA could maintain K disjoint paths from each source node to the nearest supernode and the available path from supernodes to the sink. Moreover, it could investigate the optimal alternative routing strategies, and solve the problem with cloning, high-frequency mutation, clone selection operations, which can improve the fault tolerant ability and reliability of inter-cluster and intra-cluster data transmission. Using this scheme, we can efficiently repair the broken path of intercluster supernodes or intracluster ordinary nodes network. Finally, we discuss the implementation of the MPSICA based fault-tolerant routing protocol and present the performance evaluation through experiments. The simulation results have verified that the MPSICA based protocol can provide reliable communication with intelligent bio-heuristic routing recovery scheme, thus extend the lifetime of WSNs. © 2015 Elsevier Inc. All rights reserved.

关键词： Heterogeneous sensor networks Immune cooperation Master-slave swarm Routing recovery

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An ant colony algorithm and improvement for the state transition diagram search

An ant colony algorithm and improvement for the state transi...

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2015 International Industrial Informatics and computer Engineering Conference(IIICEC 2015)

作者： Xiao Da Shengli Liu Yuefei Zhu Xiadong Wang Li Rui Computer network department Zheng Zhou Information Science University State Key Laboratory of Mathematical Engineering and Advanced Computing

Aiming at the state transition quick extraction problem for sequential logic chip,has desined a state transition graph extraction algorithm based on ant colony algorithm model,besides that,the ant colony algorithm model has been introduced in details,and according to the characteristics of the graph state transfer,the ant colony algorithm has been improved,has designed the state transition graph realization method in details oriented to the ant colony *** tests show that,the ant colony algorithm is designed in this paper can realize fast state transition graph extraction.

关键词： The state transition diagram Ant colony algorithm Sequential logic chip Shortest path Fast state test

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A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

A new logistic map based chaotic biogeography-based optimiza...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Changsha Hunan China School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China Department of Electrical Engineering CUNY New York NY USA Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Prefecture Japan School of Information Engineering Yangzhou University Yangzhou Jiangsu China School of Physics and Electronic Engineering Taizhou University Taizhou Zhejiang China School of Electronic Information Shanghai Dianji University Shanghai China School of Energy and Mechanical Engineering Nanjing Normal University Nanjing Jiangsu China Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University Quanzhou Fujian China

ISBN: (纸本)9781509034857

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： Genetic algorithms Optimization Clustering algorithms Particle swarm optimization Algorithm design and analysis Logistics Mathematical model

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On Efficient Feature Ranking Methods for High-Throughput Data Analysis

On Efficient Feature Ranking Methods for High-Throughput Dat...

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作者： Liao, Bo Jiang, Yan Liang, Wei Peng, Lihong Peng, Li Hanyurwimfura, Damien Li, Zejun Chen, Min Key Laboratory for Embedded and Network Computing of Hunan Province College of Information Science and Engineering Hunan University Changsha Hunan410082 China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China Department of Computer Science and Engineering Changsha Medical University Changsha Hunan410219 China

Efficient mining of high-throughput data has become one of the popular themes in the big data era. Existing biology-related feature ranking methods mainly focus on statistical and annotation information. In this study, two efficient feature ranking methods are presented. Multi-target regression and graph embedding are incorporated in an optimization framework, and feature ranking is achieved by introducing structured sparsity norm. Unlike existing methods, the presented methods have two advantages: (1) the feature subset simultaneously account for global margin information as well as locality manifold information. Consequently, both global and locality information are considered. (2) Features are selected by batch rather than individually in the algorithm framework. Thus, the interactions between features are considered and the optimal feature subset can be guaranteed. In addition, this study presents a theoretical justification. Empirical experiments demonstrate the effectiveness and efficiency of the two algorithms in comparison with some state-of-the-art feature ranking methods through a set of real-world gene expression data sets. © 2015 IEEE.

关键词： Convex optimization

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Tensor object classification via multilinear discriminant analysis network 40

Tensor object classification via multilinear discriminant an...

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Zeng, Rui Wu, Jiasong Senhadji, Lotfi Shu, Huazhong LIST Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing China INSERM U 1099 Rennes France Laboratoire Traitement du Signal et de l'Image Universit de Rennes 1 Rennes France France

ISBN: (纸本)9781467369978

This paper proposes an multilinear discriminant analysis network (MLDANet) for the recognition of multidimensional objects, knows as tensor objects. The MLDANet is a variation of linear discriminant analysis network (LDANet) and principal component analysis network (PCANet), both of which are the recently proposed deep learning algorithms. The MLDANet consists of three parts: 1) The encoder learned by MLDA from tensor data. 2) Features maps obtained from decoder. 3) The use of binary hashing and histogram for feature pooling. A learning algorithm for MLDANet is described. Evaluations on UCF11 database indicate that the proposed MLDANet outperforms the PCANet, LDANet, MPCA+LDA, and MLDA in terms of classification for tensor objects. © 2015 IEEE.

关键词： Deep learning LDANet MLDANet PCANet tensor object classification

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Position Prediction Social-Relationship-Based on Multi-order Markov Model

Position Prediction Social-Relationship-Based on Multi-order...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Yue Zou Sanfeng Zhang College of Software Engineering Southeast University Nanjing China Key Laboratory of Computer Network and Information Southeast University Nanjing China

Opportunistic network mobile user-nodes location prediction can help to collect the data, improve the dynamic network and help to decrease the problems which include the delay, low success rate, high storage space energy consume and so on, which are the results of the blindness in the process of delivery. In this paper, a mobile node location prediction algorithm base on the Multi-Order Markov prediction model as the initial forecast, and then use social-relationship which is closely linked to the node to optimize the algorithm. Experimental results show that the proposed algorithm is better than the single Multi-Order Markov model.

关键词： Markov processes Prediction algorithms Routing Predictive models Hidden Markov models Whales Delays

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Carriers Selection for Content Dissemination in Social Opportunistic networks

Carriers Selection for Content Dissemination in Social Oppor...

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International Conference on Collaborative Computing: networking, Applications and Worksharing (CollaborateCom)

作者： Yongqiang Dong Wang Yang Taieb Znati Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China Department of Computer Science School of Arts and Sciences Pittsburgh PA USA

Content dissemination in social opportunistic networks has attracted great interests in the field. Most of the researches in literature focused on the data forwarding and routing mechanisms in such network scenarios. There were few studies on the assignment of content originators. This paper is concerned about how to identify a small subset of users as content carriers through which the content can be disseminated more efficiently. The problem is modeled as a dominating set problem in bipartite graph, in which a minimum number of carriers are selected to cover all the venues with required probability, by using available location affinity information. The NP-complete property of the problem is pointed out, along with an exact exponential exhaustive algorithm. Then three polynomial heuristic algorithms are presented to solve the venue coverage problem. Among them, the adaptive metric-based algorithm chooses carriers based on dynamically calculated metric values. Several user-centric and expected contribution based metrics are discussed and examined. The submodular algorithm selects carriers greedily based on the estimation of marginal coverage gain from each user. The reduced-union algorithm asks each venue to select a candidate set separately based on its own individual affinity information. Then the candidate union set is reduced gradually by reasonable greedy method. Synthetized data and real trace experiment results show that the submodular algorithm can be applied in scenarios where coverage threshold is low and small number of carriers is required. In most cases we can rely on metric-based algorithm to solve the carriers selection problem. Among all the metrics, total affinity and proportional contribution perform more valuable than other metrics. Meanwhile, the adaptive operation in metric-based algorithm plays more important role than the metrics in seeking the most qualified carriers. When complete affinity information is not available, the reduced-union algo

关键词： Bipartite graph Algorithm design and analysis Routing Heuristic algorithms Delays network topology

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VCLT: An accurate trajectory tracking attack based on crowdsourcing in VANETs 15th

VCLT: An accurate trajectory tracking attack based on crowds...

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15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015

作者： Lin, Chi Liu, Kun Xu, Bo Deng, Jing Yu, Chang Wu Wu, Guowei School of Software Dalian University of Technology Dalian116621 China Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian116621 China Department of Computer Science University of North Carolina at Greensboro GreensboroNC27412 United States Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

ISBN: (纸本)9783319271361

We investigate trajectory tracking in Vehicular Ad hoc networks (VANETs) in this work. Previous tracking methods suffer from low accuracy, large overhead, and big error. In this paper, we propose a Vehicular Crowdsourcing Localization and Tracking (VCLT) scheme for mounting a trajectory tracking attack. In our scheme, crowdsourcing technique is applied to sample the location information of certain users. Then matrix completion algorithm is used to generate our predictions of the users’ trajectories. To alleviate the error disturbance of the recovered location data, Kalman filter technique is implemented and the trajectories of certain users are recovered with accuracy. At last, extensive simulations are conducted to show the performance of our scheme. Simulations results reveal that the proposed approach is able to accurately track the trajectories of certain users. © Springer International Publishing Switzerland 2015.

关键词： Kalman filters

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J G Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, Herm Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparity Department of Health and Social Care London United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierrasur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen Keskus University of Helsinki Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine University of Sydney Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics U

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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Gradient Compared lp-LMS Algorithms for Sparse System Identification

Gradient Compared lp-LMS Algorithms for Sparse System Identi...

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第27届中国控制与决策会议

作者： Yong Feng Jiasong Wu Rui Zeng Limin Luo Huazhong Shu School of Biological Science and Medical Engineering Southeast University Laboratory of Image Science and Technology the Key Laboratory of Computer Network and Information IntegrationSoutheast University

ISBN: (纸本)9781479970186

In this paper,we propose two novel p-norm penalty least mean square（l-LMS） algorithms as supplements of the conventional l-LMS algorithm established for sparse adaptive filtering recently.A gradient comparator is employed to selectively apply the zero attractor of p-norm constraint for only those taps that have the same polarity as that of the gradient of the squared instantaneous error,which leads to the new proposed gradient compared p-norm constraint LMS algorithm（lGC-LMS）.We explain that the lGC-LMS can achieve lower mean square error than the standard l-LMS algorithm theoretically and *** further improve the performance of the filter,the lNGC-LMS algorithm is derived using a new gradient comparator which takes the sign-smoothed version of the previous *** performance of the l NGC-LMS is superior to that of the lGC-LMS in theory and in ***,these two comparators can be easily applied to other norm constraint LMS algorithms to derive some new approaches for sparse adaptive *** numerical simulation results show that the two proposed algorithms achieve better performance than the standard LMS algorithm and l-LMS algorithm in terms of convergence rate and steady-state behavior in sparse system identification settings.

关键词： Least Mean Square Algorithm p Norm Constraint Sparse System Identification New Gradient Comparator

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