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IEEE Congress on Evolutionary Computation, CEC 2015

作者： Chen, Zong-Gan Du, Ke-Jing Zhan, Zhi-Hui Zhang, Jun Department of Computer Science Sun Yat-Sen University Guangzhou510275 China School of Advanced Computing Sun Yat-Sen University Guangzhou510275 China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Engineering Research Center of Supercomputing Engineering Software Ministry of Education China Key Laboratory of Software Technology Department of Guangdong Province China

ISBN: (纸本)9781479974924

Cloud computing resources scheduling is significant for executing the workflows in cloud platform because it relates to both the execution time and execution cost. In order to take both the time and cost into consideration, Rodriguez and Buyya have proposed a cost-minimization and deadline-constrained workflow scheduling model on cloud computing. Their model has great applicability but the solution of their particle swarm optimization (PSO) approach is not good enough and cannot meet a tight deadline condition. In this paper, we propose a genetic algorithm (GA) approach to solve this model. In order to tackle with the tight deadline condition, a dynamic objective strategy is further proposed to let GA focus on optimize the execution time objective to meet the deadline constraint when the feasible solution hasn't been obtained. After obtaining a feasible solution, the GA focuses on optimizing the execution cost within the deadline constraint. Therefore, the proposed dynamic objective GA (DOGA) has adaptive ability to the search environment to different objectives. We have conduct extensive experiments based on workflows with different scales and different cloud resources. Experimental results show that DOGA can find better solution with smaller cost than PSO does on different scheduling scales and different deadline conditions. DOGA approach is more applicable to be used in commercial activities. © 2015 IEEE.

关键词： Genetic algorithms

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POSTER: A hybrid approach for mobile security threat analysis 8

POSTER: A hybrid approach for mobile security threat analysi...

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8th ACM Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2015

作者： You, Wanqing Qian, Kai Guo, Minzhe Bhattacharya, Prabir Qian, Ying Tao, Lixin Department of Computer Science and Software Engineering Southern Polytechnic State University MariettaGA United States Department of Electrical Engineering and Computing Systems University of Cincinnati United States Department of Computer Science East China Normal University Shanghai China Dept. of Computer Science Pace University New York United States

ISBN: (纸本)9781450336239

Research on effective and efficient mobile threat analysis becomes an emerging and important topic in cybersecurity research area. Static analysis and dynamic analysis constitute two of the most popular types of techniques for security analysis and evaluation;nevertheless, each of them has its strengths and weaknesses. To leverage the benefits of both approaches, we propose a hybrid approach that integrates the static and dynamic analysis for detecting security threats in mobile applications. The key of this approach is the unification of data states and software execution on critical test paths. The approach consists of two phases. In the first phase, a pilot static analysis is conducted to identify potential critical attack paths based on Android APIs and existing attack patterns. In the second phase, a dynamic analysis follows the identified critical paths to execute the program in a limited and focused manner. Attacks shall be detected by checking the conformance of the detected paths with existing attack patterns. The method will report the types of detected attack scenarios based on types of sensitive data that may be compromised, such as web browser cookie.

关键词： Android application analysis Data path tracing Dynamic analysis Static analysis Symbolic execution

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Fitting Skeletal Object Models Using Spherical Harmonics Based Template Warping

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IEEE Signal Processing Letters 2015年第12期22卷 2269-2273页

作者： Tu, Liyun Yang, Dan Vicory, Jared Zhang, Xiaohong Pizer, Stephen M. Styner, Martin College of Computer Science Chongqing University Chongqing400044 China Department of Computer Science University of North Carolina Chapel HillNC27599 United States School of Software Engineering Chongqing University Chongqing400044 China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400044 China

We present a scheme that propagates a reference skeletal model (s-rep) into a particular case of an object, thereby propagating the initial shape-related layout of the skeleton-to-boundary vectors, called spokes. The scheme represents the surfaces of the template as well as the target objects by spherical harmonics and computes a warp between these via a thin plate spline. To form the propagated s-rep, it applies the warp to the spokes of the template s-rep and then statistically refines. This automatic approach promises to make s-rep fitting robust for complicated objects, which allows s-rep based statistics to be available to all. The improvement in fitting and statistics is significant compared with the previous methods and in statistics compared with a state-of-the-art boundary based method. © 2015 IEEE.

关键词： Medical imaging

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Learning automaton based context oriented middleware architecture for precision agriculture

Learning automaton based context oriented middleware archite...

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International Conference on Computer, Information and Telecommunication Systems, IEEE CITS 2015

作者： Venkata Krishna, P. Sivanesan, S. Misra, Sudip Obaidat, Mohammad S. Department of Computer Science Sri Padmavathi Mahila Visvavidyalayam Tirupati India School of Computing Science and Engineering VIT University Vellore India School of Information Technology Indian Institute of Technology Kharagpur India Dept. of Computer Science and Software Engineering Monmouth University NJ United States

ISBN: (纸本)9781467369459

The continuous alteration of living landscape in earth due to the greatest impact of information technology has converted the whole earth into a small digital village. That means anyone could share information in any form with any other person residing anywhere in the earth. With the availability of information and communication technology like cloud computing, heterogeneous networking, crowd sensing, web services and data mining, anywhere and anytime information sharing is possible, but this will bring out lot of challenges like incompatibility in standards, data portability, data aggregation, data dissemination, differential context and communication overhead. The ICT has changed many aspects of human lifestyle, work places and living spaces. However, there is one sector namely agriculture which has been deprived of the real advantages of ICT. Hence, there exists a digital divide between farming industry and other industries. Farming industry consumes large amount of natural resources such as water, energy and fertilizers that could escalate issues such as global warming, soil degradation and depletion of ground water to the next level. To reduce the global warming effect, farming industry needs to be integrated with relevant technologies. This paper proposes ubiquitous context oriented middleware architecture for precision agriculture (LA-COMPa) to solve major issues such as waste of water, improper application of fertilizer, choice of wrong crops and season, poor yield and lack of marketing. © 2015 IEEE.

关键词： Middleware

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Security concerns and mitigation approaches for MOOC-based applications

Security concerns and mitigation approaches for MOOC-based a...

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International Conference for Internet Technology and Secured Transactions (ICITST)

作者： David Lebron Hossain Shahriar Rubana Yasmin Lupu Department of Computer Science College of Computing and Software Engineering Kennesaw State University Georgia USA Department of Information Technology College of Computing and Software Engineering Kennesaw State University Georgia USA

ISBN: (纸本)9781467383370

MOOCs have expanded educational access beyond the traditional scope and masses. Cloud computing, open source platforms and software frameworks have provided the MOOC elements to support the creation of cost effective infrastructures, minimizing costs with widespread accessibility. However, these foundational elements present security concerns, which include non-enforceable policies, system and software vulnerabilities and the ever-present human error. Mitigating the risks are crucial to effective implementation since exploitation and risk adversities are compounded by scale. This paper presents an exploratory study on the risks, issues and challenges related to MOOC platforms. We introduce some critical security concerns and their impact on end users and providers. We also provide guidelines and suggestions to mitigate these concerns.

关键词： Decision support systems Conferences Security Databases Data privacy Cloud computing

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Linguistic Comparison of Time Series using the End-Point Fit Algorithm

Linguistic Comparison of Time Series using the End-Point Fit...

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IEEE International Conference on Fuzzy Systems

作者： Rita Castillo-Ortega Nicolas Marin Carmen Martinez-Cruz Daniel Sanchez Department of Computer Science and A.I. University of Granada Department of Software and Computing Engineering University of Jaen

ISBN: (纸本)9781467374293

In this paper, we present an approach to linguistically describe two time series based on their domain values and trends. The Iterative End-Point Fit algorithm has been selected for obtaining a suitable segmentation of the series to be used in the description process. The comparison between series is performed by calculating the difference between values of two time series, which are defined on the same time domain. The resulting time series is described by several kind of summaries according to the way the difference is calculated and the permissible error. We have illustrated this proposal with several time series that represent the CO2 Emission in different countries.

关键词： Time series End Point series (mathematics) Permissible error TIME-DOMAIN Linguistics

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Radiation constrained wireless charger placement

Radiation constrained wireless charger placement

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Haipeng Dai Yunhuai Liu Alex X. Liu Lingtao Kong Guihai Chen Tian He State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu CHINA Third Research Institute of Ministry of Public Security Shanghai CHINA Shanghai key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China Computer Science and Engineering University of Minnesota Minneapolis MN USA Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781467399548

Wireless Power Transfer has become a commercially viable technology to charge devices because of the convenience of no power wiring and the reliability of continuous power supply. This paper concerns the fundamental issue of wireless charger placement with electromagnetic radiation (EMR) safety. Although there are a few wireless charging schemes consider EMR safety, none of them addresses the charger placement issue. In this paper, we propose PESA, a wireless charger Placement scheme that guarantees EMR SAfety for every location on the plane. First, we discretize the whole charging area and formulate the problem into the Multidimensional 0/1 Knapsack (MDK) problem. Second, we propose a fast approximation algorithm to the MDK problem. Third, we optimize our scheme to improve speed by double partitioning the area. We prove that the output of our algorithm is better than (1 - ϵ) of the optimal solution to PESA with a smaller EMR threshold (1 - ϵ/2)Rt and a larger EMR coverage radius (1 + ϵ/2)D. We conducted both simulations and field experiments to evaluate the performance of our scheme. Our experimental results show that in terms of charging utility, our algorithm outperforms the prior art by up to 45.7%.

关键词： Safety Wireless communication Wireless sensor networks Approximation algorithms Partitioning algorithms Inductive charging Aggregates

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Renumber coevolutionary multiswarm particle swarm optimization for multi-objective workflow scheduling on cloud computing environment 15

Renumber coevolutionary multiswarm particle swarm optimizati...

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17th Genetic and Evolutionary Computation Conference, GECCO 2015

作者： Li, Hai-Hao Chen, Zong-Gan Zhan, Zhi-Hui Du, Ke-Jing Zhang, Jun Department of Computer Science Sun Yat-sen University Guangzhou510275 China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education P.R. China Collaborative Innovation Center of High Performance Computing National University of Defense Technology Changsha 410073 China Engineering Research Center of Supercomputing Engineering Software Ministry of Education P.R. China

ISBN: (纸本)9781450334884

Resources scheduling is a significant research topic in cloud computing, which is often modeled as a cost-minimization and deadline-constrained workflow scheduling model. This is a constrained single objective problem that to minimize the overall workflow execution cost while meeting deadline constraints. In this paper, we offer a new horizon to convert this single-objective problem to a multi-objective problem and present coevolutionary multiswarm particle swarm optimization (CMPSO) to find the non-dominated solutions with different execute cost and time. Meanwhile, the renumber strategy is adopted in CMPSO to make the learning efficient. CMPSO is compared with a renumber PSO (RNPSO) by setting the execute time in the CMPSO's nondominated solutions as the deadline constraint of RNPSO. Results show that CMPSO not only offers many non-dominated solutions with different prices and execute time, but also obtains better solution than RNPSO under a same deadline. Copyright is held by the owner/author(s).

关键词： Cloud computing

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FlexCloud: A Flexible and Extendible Simulator for Performance Evaluation of Virtual Machine Allocation

FlexCloud: A Flexible and Extendible Simulator for Performan...

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IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

作者： Minxian Xu Guozhong Li Wutong Yang Wenhong Tian Department of Computing and Information System University of Melbourne School of Information and Software Engineering University of Electronic Science and Technology of China

Cloud Data centers aim to provide reliable, sustainable and scalable services for all kinds of applications. Resource scheduling is one of keys to cloud services. To model and evaluate different scheduling policies and algorithms, we propose FlexCloud, a flexible and scalable simulator that enables users to simulate the process of initializing cloud data centers, allocating virtual machine requests and providing performance evaluation for various scheduling algorithms. FlexCloud can be run on a single computer with JVM to simulate large scale cloud environments with focus on infrastructure as a service, adopts agile design patterns to assure the flexibility and extensibility, models virtual machine migrations which is lack in the existing tools, provides user-friendly interfaces for customized configurations and replaying. Comparing to existing simulators, FlexCloud has combined features for supporting public cloud providers, load-balance and energy-efficiency scheduling. FlexCloud has advantage in computing time and memory consumption to support large-scale simulations. The detailed design of FlexCloud is introduced and performance evaluation is provided.

关键词： Cloud computing Computational modeling Load modeling Virtual machining Resource management Scheduling algorithms

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