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international conference on Network and Service Management

作者： Nashid Shahriar Reaz Ahmed Aimal Khan Shihabur Rahman Chowdhury Raouf Boutaba Jeebak Mitra David R. Cheriton School of Computer Science University of Waterloo Huawei Technologies Canada

ISBN: (纸本)9781509032365

Network visualization (NV) has evolved as a key enabling technology for offering the next generation network services. Recently, it is being rolled out in data center networks as a means to provide bandwidth guarantees to cloud applications. With increasing deployments of virtual networks (VNs) in commercial-grade networks with commodity hardware, VNs need to tackle failures in the underlying substrate network. In this paper, we study the problem of recovering a batch of VNs affected by a substrate node failure. the combinatorial possibilities of alternate embeddings of the failed virtual nodes and links of the VNs makes the task of finding the most efficient recovery both non-trivial and intractable. Furthermore, any recovery approach ideally should not cause any service disruption for the unaffected parts of the VNs. We take into account these issues to design a recovery approach for maximizing recovery and minimizing the cost of recovery and network disruption. We provide an integer Linear programming (ILP) formulation of our recovery scheme. We also propose a fast and scalable heuristic algorithm to tackle the computational complexity of the ILP solution. Evaluation results demonstrate that our heuristic performs close to the optimal solution and outperforms the state-of-the-art algorithm.

关键词： Substrates Bandwidth Heuristic algorithms Reliability Quality of service optimization Virtualization

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A hierarchical dispatch structure for distribution network pricing

A hierarchical dispatch structure for distribution network p...

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international conference on Environment and Electrical Engineering (EEEIC)

作者： Zhao Yuan Mohammad Reza Hesamzadeh Electricity Market Research Group KTH Royal Institute of Technology Stockholm Sweden

this paper presents a hierarchical dispatch structure for efficient distribution network pricing. the dispatch coordination problem in the context of hierarchical network operators are addressed. We formulate decentralized generation dispatch into a bilevel optimization problem in which main network operator and the connected distribution network operator optimize their costs in two levels. By using Karush-Kuhn-Tucker conditions and Fortuny-Amat McCarl linearization, the bilevel optimization problem is reduced into a mixed-integer linear programming (MILP) problem. Equivalence between proposed hierarchical dispatch and centralized dispatch is proved. the model is solved in GAMS platform. IEEE 14-bus meshed network and IEEE 13-node radial network are connected to be an illustrative example offering numerical dispatch results. three scenarios representing distributed generation (DGs) successive development stages are analyzed. Hierarchical dispatch achieves same results as traditional centralized dispatch in the three considered scenarios. Distribution network nodal prices are obtained. Intrinsic advantages of the proposed hierarchical dispatch are to reduce the dispatch complexity with increasing DGs penetration and provide distribution locational marginal prices (DLMP).

关键词： optimization Production Pricing Mathematical model Smart grids Complexity theory Indexes

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

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

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international Scientific-Technical conference on Actual Problems of Electronics Instrument Engineering

作者： Yuriy A. Mezentsev Igor V. Estraykh Novosibirsk State Technical University Novosibirsk Russia

ISBN: (纸本)9781509040704

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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Computation Task Scheduling and Offloading optimization for Collaborative Mobile Edge Computing

Computation Task Scheduling and Offloading Optimization for ...

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international conference on Parallel and Distributed Systems (ICPADS)

作者： Bin Lin Xiaohui Lin Shengli Zhang Hui Wang Suzhi Bi College of Electronic and Information Engineering Shenzhen University Shenzhen China Peng Cheng Laboratory Shenzhen China

ISBN: (数字)9781728190747

ISBN: (纸本)9781728183824

Mobile edge computing (MEC) platform allows its subscribers to utilize computational resource in close proximity to reduce the computation latency. In this paper, we consider two users each has a set of computation tasks to execute. In particular, one user is a registered subscriber that can access the computation service of MEC platform, while the other unregistered user cannot directly access the MEC service. In this case, we allow the registered user to receive computation offloading from the unregistered user, compute the received task(s) locally or further offload to the MEC platform, and charge a fee that is proportional to the computation workload. We study from the registered user's perspective to maximize its total utility that balances the monetary income and the cost on execution delay and energy consumption. We formulate a mixed integer non-linear programming (MINLP) problem that jointly decides the execution scheduling of the computation tasks (i.e., the device where each task is executed) and the computation/communication resource allocation. To tackle the problem, we first derive the closed-form solution of the optimal resource allocation given the integer task scheduling decisions. We then propose a reduced-complexity approximate algorithm to optimize the combinatorial computation scheduling decisions. Simulation results show that the proposed collaborative computation scheme effectively improves the utility of the helper user compared with other benchmark methods, and the proposed solution method approaches the optimal solution within 0.1% average performance gap with significantly reduced complexity.

关键词： Processor scheduling Simulation Collaboration Scheduling Resource management Task analysis optimization

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Compact Representation of Time-Index Job Shop Problems Using a Bit-Vector Formulation

Compact Representation of Time-Index Job Shop Problems Using...

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IEEE international conference on Automation Science and Engineering (CASE)

作者： Sabino Francesco Roselli Kristofer Bengtsson Knut Åkesson Department Electrical Engineering Chalmers University of Technology Göeborg Sweden

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

the Job Shop Scheduling Problem (JSP) is a combinatorial optimization problem where jobs visit single-capacity machines while minimizing a cost function, typically the makespan. the problem can be extended to fit typical industrial scenarios such as flexible assembly shop floors or for coordinating fleets of automated vehicles. General purpose optimizers can handle extended versions of the problem that typically arise in industrial problems. Mixed integer Linear programming (MILP) solvers and recently optimizing Satisfiability Modulo theory (SMT) solvers can be used as general solvers for JSP problems. there exist different formulations of JSP problems, among them the time-index (TI) model. the TI offers the advantage of providing strong lower bounds, though its drawback is the model *** this paper we present a new formulation of the TI model suitable for optimizing SMT-solvers that support bit-vector theories. the new formulation is significantly more compact than the standard TI formulation and is thus reducing one of the major issues with the TI *** benchmark two different optimizing SMT solvers supporting bit-vector theories, comparing the standard formulation of the TI to the new formulation on a set of benchmark instances. the computational analysis shows that the new formulation outperforms the standard one, being up to twice faster and regardless of the solver employed; moreover the model generated with the new formulation is considerably smaller than with the standard formulation.

关键词： Mathematical model Standards Upper bound Computational modeling Benchmark testing optimization Analytical models

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An Incremental Planning Strategy-Based Genetic Algorithm for Integrated Scheduling and Routing optimization in Smart Manufacturing

An Incremental Planning Strategy-Based Genetic Algorithm for...

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international conference on Control and Automation (ICCA)

作者： Jiarong Yao Yao Guo Jiangpeng Li Rong Su Keck Voon Ling Boon Siew Han Hong Yee Alvin Wong School of Electrical and Electronic Engineering Nanyang Technological University Singapore Centre for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Schaeffler Hub for Advanced Research (SHARE@NTU) Nanyang Technological University Singapore

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Production scheduling has always been an important topic in smart manufacturing especially integrated with dispatching and routing of automatic guided vehicle or autonomous mobile robots, which is generally modeled as a nondeterministic polynomial-hard integer programming problem. However, most existing studies solve this combinatorial optimization problem through decomposition, namely dealing with scheduling and routing separately, or just assuming a fixed predefined distance matrix for routing, which sacrifices the solution quality for shorter time of decision making. As for metaheuristic solution for such integrated models, the need for effective and efficient searching rules is urgent, so that the heuristics can be more fit for specific purpose and scenarios. thus, in this paper, an integrated scheduling and routing model is proposed oriented towards the optimization of production scheduling and fleet management in smart manufacturing environment. A genetic algorithm (GA) is used to solve this problem based on incremental planning (IP) strategy which makes effect through ensemble of two local search operators considering the time windows and alternative paths for every transportation task of AGVs. the effectiveness of the proposed method is validated through a simulation case study with horizontal comparison. Results showed that the IP strategy can improve the solution quality and traffic load imbalance of the factory layout, by reducing the makespan and working time of AGV by about 11.5% and 9% respectively. About 80% of the tasks obtained a shorter makespan by adopting an alternative path, showing the ability of traffic load balancing among layout elements when the problem scale increases.

关键词： Job shop scheduling Layout Telecommunication traffic Routing Dispatching Planning IP networks

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Advanced Energy Storage Management in Distribution Network

Advanced Energy Storage Management in Distribution Network

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Hawaii international conference on System Sciences

作者： Guodong Liu Oguzhan Ceylan Bailu Xiao Michael Starke Ben Ollis Daniel King Philip Irminger Kevin Tomsovic Power & Energy Syst. Group Oak Ridge Nat. Lab. Oak Ridge TN USA

ISBN: (纸本)9781509019816

With increasing penetration of distributed generation (DG) in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative mixed integer quadratic constrained quadratic programming model to optimize the operation of a three phase unbalanced distribution system with high penetration of Photovoltaic (PV) panels, DG and energy storage (ES) is developed. the proposed model minimizes not only the operating cost, including fuel cost and purchasing cost, but also voltage deviations and power loss. the optimization model is based on the linearized sensitivity coefficients between state variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DG and ES). To avoid slow convergence when close to the optimum, a golden search method is introduced to control the step size and accelerate the convergence. the proposed algorithm is demonstrated on modified IEEE 13 nodes test feeders with multiple PV panels, DG and ES. Numerical simulation results validate the proposed algorithm. Various scenarios of system configuration are studied and some critical findings are concluded.

关键词： Voltage regulation distributed generation (DG) linearization multiobjective optimization sensitivity coefficients unbalanced distribution network

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Critical5G-Net: Addressing Critical Node Impact on Lifetime and Latency in IoT Networks

Critical5G-Net: Addressing Critical Node Impact on Lifetime ...

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international conference on the Network of the Future (NOF)

作者： Behnam Ojaghi Ricard Vilalta Raül Muñoz CTTC Barcelona Spain

ISBN: (数字)9798350377767

ISBN: (纸本)9798350377774

In 5G networks, massive Internet of things (IoT) devices pose challenges like network management and security. Such networks are vulnerable to natural phenomena and attacks due to the lack of physical protection and insufficient security mechanisms. this paper examines that not all nodes are equally affected by their incapacitation; some critical nodes deteriorate the most in the network performance when incapacitated. Our study investigates the effects of eliminating critical nodes on two critical network performance metrics, namely lifetime and latency, using the Mixed integer programming (MIP) framework. Numerical evaluations prove that these critical nodes significantly impact lifetime and latency, and their identification is essential for adjusting the service tolerance and improving network maintenance. For example, in a disk-shaped network topology scenario with 100 nodes, if two critical nodes are removed, the lifetime can decrease by 56% when minimum latency is enforced by allowing a 24% latency increase; such lifetime deterioration can be reduced to 13%.

关键词： Performance evaluation Wireless sensor networks Pedestrians Network topology optimization models Minimization Real-time systems Internet of things Security Protection

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 1996年 1084卷

作者： Cunningham, William H. McCormick, S. thomas Queyranne, Maurice University of Waterloo Department of Combinatorics and Optimization WaterlooON Canada University of British Columbia VancouverBC Canada

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Preface

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3064卷 4-4页

作者： Nemhauser, George Bienstock, Daniel School of Industrial and Systems Engineering AtlantaGA United States Columbia University Department of IEOR 500West 120th Street New YorkNY United States

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