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Cognitive Context-aware Distributed Storage optimization in Mobile Cloud Computing: A Stable Matching based Approach 37

Cognitive Context-aware Distributed Storage Optimization in ...

引用

37th IEEE international conference on Distributed Computing Systems (ICDCS)

作者： Han, Dong Yan, Ye Shu, Tao Yang, Liuqing Cui, Shuguang Oakland Univ Dept Comp Sci & Engn Rochester MI 48309 USA Auburn Univ Dept Comp Sci & Software Engn Auburn AL 36849 USA Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA Univ Calif Davis Dept Elect & Comp Engn Davis CA 95616 USA

ISBN: (纸本)9781538617915

Mobile cloud storage (MCS) is being extensively used nowadays to provide data access services to various mobile platforms such as smart phones and tablets. For cross-platform mobile apps, MCS is a foundation for sharing and accessing user data as well as supporting seamless user experience in a mobile cloud computing environment. However, the mobile usage of smart phones or tablets is quite different from legacy desktop computers, in the sense that each user has his/ her own mobile usage pattern. therefore, it is challenging to design an efficient MCS that is optimized for individual users. In this paper, we investigate a distributed MCS system whose performance is optimized by exploiting the fine-grained context information of every mobile user. In this distributed system, lightweight storage servers are deployed pervasively, such that data can be stored closer to its user. We systematically optimize the data access efficiency of such a distributed MCS by exploiting three types of user context information: mobility pattern, network condition, and data access pattern. We propose two optimization formulations: a centralized one based on mixed-integer linear programming (MILP), and a distributed one based on stable matching. We then develop solutions to both formulations. Comprehensive simulations are performed to evaluate the effectiveness of the proposed solutions by comparing them against their counterparts under various network and context conditions.

关键词： Mobile communication Distributed databases optimization Context modeling Mobile handsets Encoding Cloud computing

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Transmission capacity margin assessment in power systems with uncertain wind integration

Transmission capacity margin assessment in power systems wit...

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IEEE international conference on Automation Science and Engineering (CASE)

作者： Yafei Yang Xuejiao Lei Qiaozhu Zhai Jiang Wu Xiaohong Guan Systems Engineering Institute MOE KLINNS Lab of Xi'an Jiaotong University China State Grid Energy Research Institute Beijing China Center for Intelligent and Networked Systems Tsinghua University Beijing China

High penetration of renewable resources will increase the risk of overloading transmission lines and the difficulty of controlling transmission grid in a safe operation. In this paper, a model for transmission capacity margin assessment (TCMA) is established to quantify the transmission security with uncertain wind generation. the basic formulation is reformulated as a two-stage non-differentiable programming model. It can be transformed into a mixed integer linear programming (MILP) by duality theory and specific linearization techniques. Furthermore, an effective procedure is developed to improve the transmission capacity margin by necessary wind curtailment. A detailed case study is performed on the IEEE 31-bus system and numerical results verify the effectiveness of this TCMA framework.

关键词： Security Wind power generation Uncertainty Power transmission lines programming Linearization techniques optimization

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A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem

A simulation-based benders' cuts generation for the joint wo...

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IEEE international conference on Automation Science and Engineering (CASE)

作者： Mengyi Zhang Andrea Matta Arianna Alfieri Giulia Pedrielli Department of Mechanical Engineering Politecnico di Milano Milan ITALY Department of Management Engineering Politecnico di Torino Turin ITALY School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA

the Discrete Event optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. this work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. the optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.

关键词： Workstations optimization Resource management Mathematical model Computational modeling Numerical models

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Data-based predictive optimization for by product gas system in steel industry

Data-based predictive optimization for by product gas system...

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IEEE international conference on Automation Science and Engineering (CASE)

作者： Jun Zhao Chunyang Sheng Wei Wang Witold Pedrycz Quanli Liu School of Control Science and Engineering Dalian University of Technology Dalian China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

In light of significant complexity of the byproduct gas system in steel industry (which limits an ability to establish its physics-based model), this study proposes a data-based predictive optimization (DPO) method to carry out real-time adjusting for the gas system. Two stages of the method, namely the prediction modeling and real-time optimization, are involved. At the prediction stage, the states of the optimized objectives, the consumption of the outsourcing natural gas and oil, the power generation and the tank levels, are forecasted based on a proposed mixed Gaussian kernel-based prediction intervals (PIs) construction model. the Jacobian matrix of this model is represented by a kernel matrix through derivation, which greatly facilitates the subsequent calculation. At the second stage, a rolling optimization based on a mathematical programming technique involving continuous and integer decision-making variables is developed via the prediction intervals.

关键词： optimization Jacobian matrices Predictive models Real-time systems Kernel Job shop scheduling Computational modeling

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Test wrapper algorithm for scan chain balance based on entropy increase hybrid differential evolution

Test wrapper algorithm for scan chain balance based on entro...

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international conference on Electronic Measurement and Instruments, ICEMI

作者： Deng Libao Zhang Baoquan Wang Sha Qiao Liyan School of Information and Electrical Engineering Harbin Institute of Technology at Weihai Weihai China Dept. of Automatic Test and Control Harbin Institute of Technology Harbin China

A well cores reused-based wrapper design is an important approach to minimize SOC test application time and test costs. the combinatorial optimization problem of core wrapper design has been proven to be a NP-hard problem. In this paper, a wrapper scan chain balance algorithm with entropy increase hybrid discrete differential evolution (EIHDE) is proposed to solve the core wrapper problem, which is inspired by thermodynamic system principle of entropy increase and outstanding global searching ability of Differential Evolution (DE). the proposed approach develops a cooperative mutation strategy based on entropy increase for the problem to preserving its interesting search mechanism for discrete domains. In the proposed model, two cooperative encode modes of individuals are introduced for standard differential mutation and the cooperative entropy increase mutation: integer encode mode and binary encode mode. EIHDE controls the search space by differential mutation, and search for superior individual in local space by entropy increase mutation. the combination of two kinds of mutation operations promotes the optimization ability considerably and achieves a better tradeoff between exploitation and exploration. the experimental results of the ITC'02 SOC test benchmarks show that EIHDE can achieve more balanced results compared with other algorithms.

关键词： IP networks Algorithm design and analysis Entropy optimization Sociology Statistics Binary codes

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Centerpoints: A Link Between optimization and Convex Geometry 1

引用

18th international conference on integer programming and combinatorial optimization (IPCO)

作者： Basu, Amitabh Oertel, Timm Johns Hopkins Univ Baltimore MD USA Cardiff Univ Cardiff S Glam Wales

ISBN: (数字)9783319334615

ISBN: (纸本)9783319334615;9783319334608

We introduce a concept that generalizes several different notions of a "centerpoint" in the literature. We develop an oracle-based algorithm for convex mixed-integer optimization based on centerpoints. Further, we show that algorithms based on centerpoints are "best possible" in a certain sense. Motivated by this, we establish several structural results about this concept and provide efficient algorithms for computing these points.

关键词： integer programming

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Mathematical and economic extrapolations on the model for optimal microgrid operation and its solution

Mathematical and economic extrapolations on the model for op...

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international conference on Electrical Machines, Drives and Power Systems (ELMA)

作者： Vesselina Trashlieva Electric Power Systems Department Technical University of Sofia Sofia Bulgaria

Mixed-integer linear programming problems represent a large group of models that are widely constructed for optimization problems in Electric Power Systems Operation. An economical and financial analysis is obligatory for the obtained solution as being a part of the effective system planning and operation. In this paper a formal approach to such analysis is given having a combinatorial problem with binary variables designing the different states in the microgrid. the numerical example includes a detailed post-solution analysis made with Matlab® and LPSolve.

关键词： Microgrids optimization Load modeling Sensitivity analysis Upper bound Production

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On Approximation Algorithms for Concave Mixed-integer Quadratic programming 1

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18th international conference on integer programming and combinatorial optimization (IPCO)

作者： Del Pia, Alberto Univ Wisconsin Inst Discovery Dept Ind & Syst Engn & Wisconsin Madison WI USA

ISBN: (数字)9783319334615

ISBN: (纸本)9783319334615;9783319334608

We describe an algorithm that finds an is an element of-approximate solution to a concave mixed-integer quadratic programming problem. the running time of the proposed algorithm is polynomial in the size of the problem and in 1/is an element of, provided that the number of integer variables and the number of negative eigenvalues of the objective function are fixed. the running time of the proposed algorithm is expected unless P = NP.

关键词： Approximation algorithms

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On one Problem of Financial Management optimization of Enterprise when Performing State Defense Order 13

On one Problem of Financial Management Optimization of Enter...

引用

13th international Scientific-Technical conference on Actual Problems of Electronics Instrument Engineering (APEIE)

作者： Mezentsev, Yuriy A. Estraykh, Igor V. Novosibirsk State Tech Univ Tech Sci 20 Prospekt K Marksa Novosibirsk 630073 Russia Novosibirsk State Tech Univ Dept Comp Sci Econ 20 Prospekt K Marksa Novosibirsk 630073 Russia

ISBN: (纸本)9781509040698

the original formal problem definition of financial management optimization of an enterprise at this conjuncture of financing the state defense order is suggested. the problem is shown to belong to the class of NP-hard problems of the mixed programming. the existing methods for solving this problem are considered and the properties of the program tools developed by the authors for searching for the best solutions are discussed.

关键词： Mixed integer programming financial management discrete profitability functions

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Resource provisioning for IoT application services in smart cities

Resource provisioning for IoT application services in smart ...

引用

international conference on Network and Service Management

作者： José Santos Tim Wauters Bruno Volckaert Filip De Turck Department of Information Technology IDLab Gent Belgium

In the last years, traffic over wireless networks has been increasing exponentially, due to the impact of Internet of things (IoT) and Smart Cities. Current networks must adapt to and cope with the specific requirements of IoT applications since resources can be requested on-demand simultaneously by multiple devices on different locations. One of these requirements is low latency, since even a small delay for an IoT application such as health monitoring or emergency service can drastically impact their performance. To deal with this limitation, the Fog computing paradigm has been introduced, placing cloud resources on the edges of the network to decrease the latency. However, deciding which edge cloud location and which physical hardware will be used to allocate a specific resource related to an IoT application is not an easy task. therefore, in this paper, an integer Linear programming (ILP) formulation for the IoT application service placement problem is proposed, which considers multiple optimization objectives such as low latency and energy efficiency. Solutions for the resource provisioning of IoT applications within the scope of Antwerp's City of things testbed have been obtained. the result of this work can serve as a benchmark in future research related to placement issues of IoT application services in Fog Computing environments since the model approach is generic and applies to a wide range of IoT use cases.

关键词： Logic gates Cloud computing Smart cities Bandwidth Wireless communication Edge computing optimization

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