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IFIP/IEEE Symposium on Integrated Network and Service Management (IM)

作者： Dimolianis, Marinos Pavlidis, Adam Kalogeras, Dimitris Maglaris, Vasilis Natl Tech Univ Athens Network Management & Optimal Design Lab NETMODE Sch Elect & Comp Engn Athens Greece

ISBN: (纸本)9783903176157

In this paper we propose a framework for mitigating detected multi-vector anomalies in typical enterprise networks via the distribution of Access Control Rules. Our distributed, non-proprietary approach takes advantage of the capabilities offered by all devices along an attack path enhancing their mitigation potential. These devices are organized into distinct defense stages and network operators express their defense preferences for specific attack types. Our mechanism automatically assigns generic mitigation rules to each stage. Subsequently, device-specific access control rules are generated and seamlessly distributed to the corresponding defense stages of the network substrate via commonly used protocols. The proposed mitigation schema models the rule assignment to defense stages as a generalized assignment problem. Items, i.e. generic mitigation rules, are assigned to bins, i.e. defense stages, based on capacity constraints and reward values guided by operator policies. Our approach considers reducing the GAP input size to enable reasonable execution of the resulting integer programming formulation. This is accomplished by aggregating malicious IP sources into prefixes and organizing rules into groups. The proposed mechanism is validated in a proof of concept prototype, used to mitigate realistic multi-vector attack scenarios.

关键词： Anomaly Mitigation Multi-Vector Attack DDoS generalized assignment problem Integer Programming

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Routing-aware Legal Hybrid Bonding Terminal assignment for 3D Face-to-Face Stacked ICs 24

Routing-aware Legal Hybrid Bonding Terminal Assignment for 3...

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33rd ACM International Symposium on Physical Design (ISPD)

作者： Liu, Siting Jiang, Jiaxi He, Zhuolun Wang, Ziyi Lin, Yibo Yu, Bei Chinese Univ Hong Kong Hong Kong Peoples R China Peking Univ Beijing Peoples R China Peking Univ Inst EDA Beijing Peoples R China

ISBN: (纸本)9798400704178

Face-to-face (F2F) stacked 3D IC is a promising alternative for scaling beyond Moore's Law. In F2F 3D ICs, dies are connected through bonding terminals whose positions can significantly impact routing performance. Further, there exists resource competition among all the 3D nets due to the constrained bonding terminal number. In advanced technology nodes, such 3D integration may also introduce legality challenges of bonding terminals, as the metal pitches can be much smaller than the sizes of bonding terminals. Previous works attempt to insert bonding terminals automatically using existing 2D commercial P&R tools and then consider inter-die connection legality, but they fail to take the legality and routing performance into account simultaneously. In this paper, we explore the formulation of the generalized assignment in the hybrid bonding terminal assignment problem. Our framework, BTAssign, offers a strict legality guarantee and an iterative solution. The experiments are conducted on 18 open-source designs with various 3D net densities and the most advanced bonding scale. The results reveal that BTAssign can achieve improvements in routed wirelength under all testing conditions from 1.0% to 5.0% with a tolerable runtime overhead.

关键词： 3D ICs Bonding Terminal Planning Routing generalized assignment problem Divide and Conquer

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Variable Neighborhood Search for Google Machine Reassignment problem

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Electronic Notes in Discrete Mathematics 2012年 39卷 209-216页

作者： Gavranović, Haris Buljubašić, Mirsad Demirović, Emir International University Sarajevo Bosnia and Herzegovina Faculty of Natural Sciences University of Sarajevo Bosnia and Herzegovina

We present a hybrid method to efficiently solve Google Machine Reassignment problem (MRP), the problem proposed at ROADEF/EURO Challenge 2012 competition. We study, implement, combine and empirically examine different local search neighborhoods to solve the set of available instances. Intensification and diversification of search is achieved through the suitable change of the objective function and sorting the processes. We present results obtained with the solver that respect the given computational time of 5 minutes. Some of the obtained results are proven to be optimal or near optimal. With the presented method we were ranked first at ROADEF/EURO Challenge 2012 competition. © 2012 Elsevier B.V.

关键词： generalized assignment problem Local Search Machine Reassignment Variable Neighborhood Search

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Resource assignment problem for Fleet Management Considering Outsourcing: Modelling and a Decomposition Approach 21st

Resource Assignment Problem for Fleet Management Considering...

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21st International Conference on Computational Science and Its Applications (ICCSA)

作者： Monnerat, Filipe Dias, Joana Alves, Maria Joao Univ Coimbra CeBER Av Dias da Silva 165 P-3004512 Coimbra Portugal Univ Coimbra Fac Econ Av Dias da Silva 165 P-3004512 Coimbra Portugal Univ Fed Vicosa Vicosa MG Brazil Univ Coimbra INESC Coimbra Rua Silvio LimaPolo 2 P-3030290 Coimbra Portugal

ISBN: (纸本)9783030869762;9783030869755

Many institutions have to manage internal and external resources to assure the realization of working trips. In this work we consider two different types of resources: vehicles and drivers. The assignment of these resources to trips is interlinked, since the number of drivers will depend on the number of assigned vehicles, and also on other characteristics of the trip itself. Furthermore, it is possible to improve the use of resources if they can be shared between compatible trips: trips that have compatible origin and destination pairs and are also compatible regarding the realization time periods. Instead of considering internal resources only, this work presents a new model where the possibility of outsourcing is also considered. This problem can be interpreted as an extension of the generalized assignment problem, that is known to be NP-hard. An optimization approach is also proposed, based on the decomposition of the problem. Computational tests were performed to assess the solutions produced by the model and the behaviour of the decomposition approach. The computational results show that the developed model is capable of representing in a faithful way the problem, and the algorithmic approach presents a better performance when compared with a general solver applied to the whole problem.

关键词： Combinatorial optimization generalized assignment problem Fleet management Outsourcing

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Applying Algorithm Selection – a Case Study for the Generalised assignment problem

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Electronic Notes in Discrete Mathematics 2018年 69卷 205-212页

作者： Degroote, Hans González-Velarde, José Luis De Causmaecker, Patrick Department of Computer Science CODeS & Imec KU Leuven Belgium Tecnologico de Monterrey Monterrey Mexico

Many combinatorial optimisation problems are NP-Hard. Yet in practice high quality solutions are often obtained by (meta)heuristics. These work well in some cases, but not in others, indicating a potential for algorithm selection. In this extended abstract is discussed how to apply algorithm selection to a combinatorial optimisation problem and which challenges arise when doing so. The generalised assignment problem is used as case study. © 2018 Elsevier B.V.

关键词： Automatic Algorithm Selection Combinatorial Optimisation Generalised assignment problem generalized assignment problem Meta-learning

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M3AT: Monitoring Agents assignment Model for Data-Intensive Applications 28

M3AT: Monitoring Agents Assignment Model for Data-Intensive ...

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28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)

作者： Kashansky, Vladislav Kimovski, Dragi Prodan, Radu Agrawalt, Prateek Marozzo, Fabrizio Iuhaszl, Gabriel Justyna, Marek Garcia-Blas, Javier Univ Klagenfurt Inst Informat Technol Klagenfurt Austria South Ural State Univ Sch Elect Engn & Comp Sci Chelyabinsk Russia Lovely Profess Univ Phagwara India Univ Calabria DIMES Dept Calabria Italy West Univ Timisoara Timisoara Romania Poznan Supercomp & Networking Ctr Poznan Poland Univ Carlos III Madrid Dept Comp Sci & Engn Madrid Spain

ISBN: (纸本)9781728165820

Nowadays, massive amounts of data are acquired, transferred, and analyzed nearly in real-time by utilizing a large number of computing and storage elements interconnected through high-speed communication networks. However, one issue that still requires research effort is to enable efficient monitoring of applications and infrastructures of such complex systems. In this paper, we introduce an Integer Linear Programming (ILP) model called M3AT for optimized assignment of monitoring agents and aggregators on large-scale computing systems. We identified a set of requirements from three representative data-intensive applications and exploited them to define the model's input parameters. We evaluated the scalability of M3AT using the Constraint Integer Programing (SCIP) solver with default configuration based on synthetic data sets. Preliminary results show that the model provides optimal assignments for sub-systems composed of up to 200 monitoring agents with complex I/O policies, while keeping the number of aggregators constant and demonstrates variable sensitivity with respect to the scale of monitoring data aggregators and limitation policies imposed.

关键词： Monitoring systems high performance computing aggregation systems control data-intensive systems generalized assignment problem SCIP optimization suite

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Learning Automata for Multi-Access Edge Computing Server Allocation with Minimal Service Migration

Learning Automata for Multi-Access Edge Computing Server All...

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IEEE International Conference on Communications (IEEE ICC) / Workshop on NOMA for 5G and Beyond

作者： Mukhopadhyay, Atri Ruffini, Marco Trinity Coll Dublin CONNECT Ctr Comp Sci & Stat Dublin Ireland

ISBN: (纸本)9781728150895

Multi-access edge computing nodes are being developed in support of next generation applications, which require high capacity, high reliability and low latency. One important problem that the research community has recently focused on is the allocation strategy of applications to the different MEC server nodes. In our approach, rather than focusing on maximizing usage of resources, we focus on the minimization of migration events, which can create significant service downtime to applications that need low latency and high reliability, in addition to increasing traffic congestion in the underlying network. This paper introduces a priority induced service migration minimization (PrISMM) algorithm, which aims at minimizing service migration for both high and low priority services, through the use of learning automata. We carry out extensive simulations and produce results showing its effectiveness in reducing the mean service downtime of lower priority services and the mean admission time of the higher priority services.

关键词： generalized assignment problem learning automata multi-access edge computing service migration

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A Novel Mechanism Using Genetic Algorithm for Selecting Class Officers

A Novel Mechanism Using Genetic Algorithm for Selecting Clas...

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International Conference on Information and Business Intelligence (IBI 2011)

作者： Chen, Rong-Chang Lin, Tzu-Han Natl Taichung Inst Technol Dept Logist Engn & Management Taichung Taiwan

ISBN: (纸本)9783642290862

In this paper, we propose a novel mechanism based on genetic algorithm (GA) for selecting class officers. This mechanism not only considers the service willingness of students, but also considers support rating from others. The proposed mechanism was applied to a junior class of a famous university in Taiwan and the results show that students give high positive scores to the proposed approach and consider it very interesting.

关键词： Genetic algorithm generalized assignment problem class officer

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GAPG: a Heuristic Greedy Algorithm for Grouping Storage Scheme in Blockchain

GAPG: a Heuristic Greedy Algorithm for Grouping Storage Sche...

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IEEE/CIC International Conference on Communications in China (ICCC)

作者： Li, Dapeng Dai, Jinsen Jiang, Rui Wang, Xiaoming Xu, Youyun Nanjing Univ Posts & Telecommun Natl Engn Res Ctr Commun & Networking Nanjing Peoples R China

ISBN: (纸本)9781728187556

The decentralization and immutability of blockchain make it have a wide application prospect, however, as the number of transactions increases, the storage cost of each node will also increase. So blockchain will be facing the bottleneck of insufficient scalability. Consensus Unit(CU) is one of grouping storage scheme for improving the scalability of blockchain, which organizes different nodes into one cluster and allocates all the blocks of the whole chain to the nodes in each cluster. In this paper, we propose an optimization problem that assigning blockchain data to nodes and minimized the total query cost, this is a variant of generalized basic probability assignment problem, so we propose a heuristic algorithm named GAPG to solve this problem. Numerical results demonstrate that the proposed algorithm is superior to random assignment and greedy algorithms for clusters with a large number of nodes.

关键词： Scalability of blockchain Consensus Unit generalized assignment problem

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Coupling land use allocation models with raster GIS

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Journal of Geographical Systems 1999年第2期1卷 137-153页

作者： Cromley, Robert G. Hanink, Dean M. Department of Geography U-148 University of Connecticut Storrs CT 06269-2148 United States

As geographic information systems (GIS) have moved from information storage and retrieval operations towards more decision support functions, there is a need for more integration of spatial analytical modules that can assist in locational decisions. This paper presents a methodology for coupling land use allocation models with a raster GIS. For raster systems, the integration of any decision module has been limited by the size of raster datasets that may contain hundreds of thousands of pixels. Therefore, decision heuristics have been used rather than exact methods such as mathematical programming models. For the problem of land use allocation, the special structure of the generalized assignment problem is used here to handle large scale datasets. The advantage of the mathematical programming approach is the additional information associated with the dual variables and opportunity costs that can be used in subsequent sensitivity analyses. © Springer-Verlag 1999.

关键词： generalized assignment problem Geographic information systems Land use allocation Multiobjective analysis

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