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Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

Computers, Materials & Continua 2021年第9期68卷 3147-3165页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin Bhawani Shankar Chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation CentreCyberjaya63000SelangorMalaysia National Center of Robotics and Automation Mehran University of Engineering&TechnologyJamshoroPakistan Department of Computer Science and Engineering Hanyang UniversitySeoul04763South Korea School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore Cloud Computing and Distributed Systems Laboratory The University of MelbourneMelbourneVIC 3053Australia Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology(BUET)Dhaka1205Bangladesh Department of Electronics and Communication Engineering JECRC UniversityVidhaniJaipur303905India Auckland Institute of Studies Mt AlbertAucklandNew Zealand

In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(DDoS)attacks that interfere with legitimate use of the *** ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of DDoS *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of DDoS *** goal of the model is to improve resistance to DDoS attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of DDoS attacks while managing the overall cost.

关键词： SDN automated controller placement SBC ILP DDoS attack

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Large margin multi-modal multi-task feature extraction for image classification

arXiv

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arXiv 2019年

作者： Luo, Yong Wen, Yonggang Tao, Dacheng Gui, Jie Xu, Chao School of Electronics Engineering and Computer Science Peking University Beijing China Division of Networks and Distributed Systems School of Computer Engineering Nanyang Technological University Singapore Centre for Quantum Computation & Intelligent Systems Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We therefore propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization and each sub-problem can be efficiently solved. Experiments on two challenging real-world image datasets demonstrate the effectiveness and superiority of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Feature extraction

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Cloning agent-based simulation on GPU 15

Cloning agent-based simulation on GPU

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3rd ACM Conference on SIGSIM-Principles of Advanced Discrete Simulation, SIGSIM-PADS 2015

作者： Li, Xiaosong Cai, Wentong Turner, Stephen John Parallel and Distributed Computing Center School of Computer Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781450335836

Simulation cloning is an efficient way to analyze multiple configurations in a parameter exploration task. This paper presents a generic approach to perform incremental agentbased simulation cloning and discusses its implementation on GPU. Compared with the incremental cloning of parallel and distributed simulation (PADS), cloning agent-based simulation (ABS) has new challenges due to the unique way how ABS is executed. In this paper, to support incremental cloning, mechanisms for both actively and passively cloning agents are proposed. A scheme to maintain the correct context of each cloned ABS instance is developed. In addition, a strategy to restrain the propagation of passive cloning in order to maximize computation sharing amongst cloned ABS instances is also investigated. The implementation of our proposed approach on GPU supports concurrent execution of agents within each simulation instance as well as concurrent execution of multiple simulation instances. Performance of the proposed approach is evaluated and analyzed using a case study of an agent-based evacuation simulation on a NVIDIA Quadro 2000 GPU. Our experiment results demonstrate that cloning can significantly speed up the overall parameter exploration task. The proposed approach achieves 2.4 to 5.1 times speedup for parameter exploration tasks containing 8 to 125 simulation instances that evaluate different parameter configurations. © 2015 ACM.

关键词： speedup agent-based simulation gpu cloning

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WPress: An Application-Driven Performance Benchmark for Cloud-Based Virtual Machines

WPress: An Application-Driven Performance Benchmark for Clou...

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International Conference on Enterprise distributed Object computing (EDOC)

作者： Amir Hossein Borhani Philipp Leitner Bu-Sung Lee Xiaorong Li Terence Hung Institute of High-Performance Computing (IHPC) Singapore s.e.a.l. software evolution & architecture lab University of Zurich Switzerland Parallel and Distributed Computing Center (PDCC) Nanyang Technological University Singapore

ISBN: (纸本)9781479954711

Approaching a comprehensive performance benchmark for on-line transaction processing (OLTP) applications in a cloud environment is a challenging task. Fundamental features of clouds, such as the pay-as-you-go pricing model and unknown underlying configuration of the system, are contrary to the basic assumptions of available benchmarks such as TPC-W or RUBiS. In this paper, we introduce a systematic performance benchmark approach for OLTP applications on public clouds that use virtual machines(VMs). We propose WPress benchmark, which is based on the widespread blogging software, WordPress, as a representative OLTP application and implement an open source workload generator. Furthermore, we utilize a CPU micro-benchmark to investigate CPU performance of cloud-based VMs in greater detail. Average response time and total VM cost are the performance metrics measured by WPress. We evaluate small and large instance types of three real-life cloud providers, Amazon EC2, Microsoft Azure and Rackspace cloud. Results imply that Rackspace cloud has better average response times and total VM cost on small instances. However, Microsoft Azure is preferable for large instance type.

关键词： Benchmark testing Cloud computing Time factors Servers Databases Blogs Publishing

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Spatial indexing in agent-based crowd simulation 6

Spatial indexing in agent-based crowd simulation

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6th International Conference on Simulation Tools and Techniques, SIMUTools 2013

作者： Othman, Nasri Bin Luo, Linbo Cai, Wentong Lees, Michael Parallel and Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore639798 Singapore

ISBN: (纸本)9781936968763

Crowd modeling and simulation has become a critical tool for understanding crowds and predicting their behaviours. This is accomplished by modelling the characteristics and behaviours of large groups of people, as well as their interactions. Agent-based crowd simulation may involve thousands of complex agents interacting in sophisticated ways, in close spatial proximity, with each other. A key challenge to the development of agent-based crowd simulation is the inherent complexity that is required to model all its necessary elements. A necessary feature of such a simulation is spatial indexing. This refers to the use of data structures to organize collections of simulation entities (e.g., agents and obstacles) in a manner which allows for efficient spatial querying. This is especially pertinent for large-scale crowd simulation with agents that sense their surrounding environment periodically, as the cost of spatial querying becomes computationally expensive if done naively. In this paper, we will describe our experience in improving the existing grid-based spatial indexing approach in our agent-based crowd simulation. Also, we will explore the integration of the adaptive spatial indices (e.g., R-tree and quad-tree) into our system. The performances of various spatial indexing techniques are examined in terms of efficiency and scalability. Copyright © 2013 ICST.

关键词： Decision trees

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Interactive scenario generation for mission-based virtual training

Interactive scenario generation for mission-based virtual tr...

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作者： Luo, Linbo Yin, Haiyan Cai, Wentong Lees, Michael Zhou, Suiping Parallel and Distributed Computing Centre School of Computer Engineering Nanyang Technological University Singapore Singapore School of Computing Teesside University Middlesbrough United Kingdom

For a virtual training system, how to effectively and quickly generate training scenarios has become a challenging issue. A scenario generation system is needed to produce scenarios that can meet different objectives and at the same time be customized for individuals. In this paper, we introduce a scenario generation framework for mission-based virtual training, which aims to generate scenarios from both trainer and trainee's perspective. The framework allows a trainer to direct the scenario generation process, so that the generated scenarios reflect the trainer's preferences over different mission objectives. It also considers how the scenarios could adapt to different trainees' skill levels. The representation of scenario beat is proposed, and the scenario generation process adopts a combinatorial optimization approach generating the sequence of scenario beats. The efficacy of the proposed framework is demonstrated through an empirical study of human players in a simple food distribution mission game. The results show that a trainee can achieve better performance improvement when playing the customized scenarios tailored to the trainee's skill level as compared with the uncustomized scenarios. Copyright © 2013 John Wiley & Sons, Ltd.

关键词： Combinatorial optimization

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GPU accelerated three-stage execution model for event-parallel simulation 13

GPU accelerated three-stage execution model for event-parall...

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2013 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, SIGSIM-PADS 2013

作者： Li, Xiaosong Cai, Wentong Turner, Stephen John Parallel and Distributed Computing Center School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)9781450319201

This paper introduces the concept of event-parallel discrete event simulation (DES) and its corresponding implementation on the GPU platform. Inspired by the typical spatial-parallel DES and time-parallel DES, the event-parallel approach on GPU uses each thread to process one of the N events, where N is the total number of events. By taking advantage of the high parallelism of GPU threads, this approach achieves greater speedup. The GPU architecture is adopted in the execution of the event-parallel approach, so as to take advantage of the parallel processing capability provided by the massively large number of GPU threads. A three-stage execution model composing of generating events, sorting events and processing events in parallel is proposed. This execution model achieves good speedup. Compared with the event scheduling approach on CPU, we achieve up to 22.80 speedup in our case study. © 2013 ACM.

关键词： Graphics processing unit

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Application Layer Multicast in P2P distributed Interactive Applications

Application Layer Multicast in P2P Distributed Interactive A...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yusen Li Wentong Cai Xueyan Tang Parallel and Distributed Computing Center Nanyang Technological University Singapore

By sharing resources among peers in peer-to-peer network, application layer multicast (ALM) has been shown an efficient way to improve the scalability and reduce the latency of communication. To deploy ALM in peer-to-peer distributed interactive applications (DIAs), the property of many-to-many communication of DIA demands multiple multicast trees to be constructed in the overlay. Therefore, how to efficiently allocate resources among multiple trees to maximize the benefit is an important and challenging issue. In this paper, we study the problem of building ALM trees with minimum total end-to-end delay to receivers in peer-to-peer DIAs with resource constraints on network bandwidth. The end-to-end delay from a sender to receivers in a multicast tree consists of the link delay as well as the packet queuing delay at intermediate peers, while the latter is often ignored or not well studied in the previous work. In this paper, we explicitly establish the relationship between the queuing delay at peers and the topology of multicast trees in peer-to-peer DIAs. Based on the relationship, the above mentioned problem is defined and we prove that it is NP-complete. We present a centralized heuristic algorithm to obtain an approximate solution. Moreover, distributed algorithms are also investigated to refine the topology in practical systems with dynamic changes. Extensive experiments were conducted by simulations to evaluate the proposed algorithms and results are reported in the paper.

关键词： Peer-to-peer computing Bandwidth Delays Receivers Heuristic algorithms Vegetation Buildings

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Diversity-driven self-adaptation in evolutionary algorithms

Diversity-driven self-adaptation in evolutionary algorithms

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International Conference on Advances in Intelligent Control and Computer Engineering

作者： Zeng, Fanchao Decraene, James Low, Malcolm Yoke Hean Zhou, Suiping Cai, Wentong Parallel and Distributed Computing Centre School of Computer Engineering Nanyang Technological University Nanyang Avenue Singapore 639798 Singapore

ISBN: (纸本)9789400702851

Pareto-based multi-objective optimization problems (MOPs) are currently best solved using evolutionary algorithms. Nevertheless, the performance of these nature-inspired stochastic search algorithms still depends on the suitability of their parameter settings with respect to specific optimization problems. The tuning of the parameters is a crucial task which concerns resolving the contrary goals of convergence and diversity. To address this issue, we propose a diversity-driven self-adaptive mechanism (SAM) for the simulated binary crossover. This novel technique exploits and optimizes the balance between exploration and exploitation during the evolutionary process. This "explore first and exploit later" approach is addressed through the automated and dynamic adjustment of the distribution index of the simulated binary crossover (SBX) operator. We conducted a series of experiments where SAM is applied to the Non-dominated Sorting Genetic Algorithm to solve the Sphere, Rastrigin, and ZDT optimization problems. Our experimental results have shown that our proposed self adaptation mechanism can produce promising results for both single and multi-objective problem sets. © 2011 Springer Science+Business Media B.V.

关键词： Stochastic systems

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Determining optimal update period for minimizing inconsistency in multi-server distributed virtual environments 11

Determining optimal update period for minimizing inconsisten...

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15th IEEE/ACM International Symposium on distributed Simulation and Real Time Applications, DS-RT 2011

作者： Li, Yusen Cai, Wentong Parallel and Distributed Computing Center Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)9780769545530

The primary task of distributed virtual environments (DVEs) is to maintain a consistent view of the virtual world among all users. Multi-server architecture has been shown to have good scalability to support a large population of users in DVEs. However, some of the servers' resources like CPU, memory and network bandwidth can still get saturated as the scale of DVE increases. In this case, state updates cannot be disseminated timely and the consistency of the virtual world cannot be guaranteed. In this paper, we investigate how to efficiently use the limited resources for state update to minimize inconsistency in multi-server DVEs. Using time-space inconsistency metric, we firstly prove that periodic state update will result in minimal inconsistency for each replica. Then, in order to determine the optimal update periods for replicas to minimize the total time-space inconsistency of the DVE, we formulate the problem as a convex optimization problem with inequality constraints. Finally, an interior point method is adopted to solve the problem and the performance is evaluated using simulation results. © 2011 IEEE.

关键词： Virtual reality

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