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检索条件"丛书名=Computer Communications and Networks"

共 4934 条记录，以下是271-280 订阅

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Cooperative Multi-Agent Deep Reinforcement Learning for Dynamic Virtual Network Allocation 30

Cooperative Multi-Agent Deep Reinforcement Learning for Dyna...

引用

30th International Conference on computer communications and networks (ICCCN)

作者： Suzuki, Akito Kawahara, Ryoichi Harada, Shigeaki NTT Corp NTT Network Technol Labs Tokyo Japan Toyo Univ Fac Informat Networking Innovat & Design Tokyo Japan

ISBN: (纸本)9780738113302

Network traffic and computing demand have been changing dramatically due to the growth of various types of network services, e.g., high-quality video delivery and operating system (OS) updates. To maximize the utilization efficiency of limited network resources, network resource control technology is required for smooth and quick operation when network demands change. We propose a dynamic virtual network (VN) allocation method based on cooperative multi-agent deep reinforcement learning (Coop-MADRL). This method can quickly optimize network resources even while network demands are drastically changing by learning the relationship between network demand patterns and optimal allocation by using deep reinforcement learning (DRL) in advance. The key idea is to use a multi-agent technique for a reinforcement learning (RL) based dynamic VN allocation method, which can reduce the number of candidate actions per agent and can improve the performance for VN allocation. Moreover, a cooperation technique improves the efficiency of VN allocation. From results of a simulation evaluation, Coop-MADRL can calculate effective allocation within 1 s, which reduces the maximum server and link utilization and drastically reduces the average constraint violation compared with that of the static VN allocation method.

关键词： Network functions virtualization Reinforcement Learning Network Control Dynamic Resource Allocation

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A Few-Shot Class-Incremental Learning Approach for Intrusion Detection 30

A Few-Shot Class-Incremental Learning Approach for Intrusion...

引用

30th International Conference on computer communications and networks (ICCCN)

作者： Wang, Tingting Lv, Qiujian Hu, Bo Sun, Degang Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China

ISBN: (纸本)9780738113302

Classic network intrusion detection methods usually are supervised machine learning models, which are obtained by offline training and can achieve good performance in the initial stage of system construction. However, with the rapid and diverse evolution of intrusion methods, the learned knowledge is no longer suitable for new types of attacks. In addition, existing incremental learning approaches lack rapid learning capabilities and are hard to avoid potential risks and reduce property losses when there are few new samples. This can be attributed to the few-shot class-incremental intrusion detection issue. To address this issue, we propose a learning strategy, named ID-FSCIL, which could respond to the increase in attack categories by extending the origin detection system. It fully mines new intrusion patterns from few samples with meta-learning and maximizes the model's generalization ability to deal with emerging attacks. Our evaluations show that ID-FSCIL significantly outperforms the state-of-the-art baselines on the NSL-KDD dataset under incremental learning settings.

关键词： intrusion detection few-shot incremental learning deep Neural networks meta-learning

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Epinoia: Intent Checker for Stateful networks 30

Epinoia: Intent Checker for Stateful Networks

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30th International Conference on computer communications and networks (ICCCN)

作者： Wang, Huazhe Sharma, Puneet Ahmed, Faraz Kang, Joon-Myung Qian, Chen Yannakakis, Mihalis Microsoft Redmond WA 98052 USA Hewlett Packard Labs Palo Alto CA USA UC Santa Cruz Santa Cruz CA USA Columbia Univ New York NY 10027 USA Google Mountain View CA 94043 USA

ISBN: (纸本)9780738113302

Intent-Based Networking (IBN) has been increasingly deployed in production enterprise networks. Automated network configuration in IBN lets operators focus on intents- i.e., the end to end business objectives-rather than spelling out details of the configurations that implement these objectives. Automation brings its own concerns as the administrators cannot rely on traditional network troubleshooting tools. This situation is further exacerbated in the case of stateful Network Functions (NFs) whose packet processing behavior depends on previously observed traffic patterns. To ensure that the network configuration and state derived from network automation matches the administrator's specified intent, we propose, Epinoia, a network intent checker for stateful networks. Epinoia relies on a unified model for NFs by leveraging the causal precedence relationships that exist between NF packet I/Os and states. Scalability of Epinoia is achieved by decomposing intents into sub-checking tasks and maintaining a causality graph between checked invariants. Epinoia checks for network-wide intent violations incrementally to reduce overhead in the event of network changes. Our evaluation results using real-world network topologies show that Epinoia can perform comprehensive checking within a few seconds per network with intent updates.

关键词： Automation Network topology Scalability Production Traffic control Tools Noise measurement

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Network Traffic Characteristics of IoT Devices in Smart Homes 30

Network Traffic Characteristics of IoT Devices in Smart Home...

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30th International Conference on computer communications and networks (ICCCN)

作者： Mainuddin, Md Duan, Zhenhai Dong, Yingfei Florida State Univ Dept Comp Sci Tallahassee FL 32306 USA Univ Hawaii Dept Elect Engn Honolulu HI 96822 USA

ISBN: (纸本)9780738113302

Understanding network traffic characteristics of IoT devices plays a critical role in improving both the performance and security of IoT devices, including IoT device identification, classification, and anomaly detection. Although a number of existing research efforts have developed machine-learning based algorithms to help address the challenges in improving the security of IoT devices, none of them have provided detailed studies on the network traffic characteristics of IoT devices. In this paper we collect and analyze the network traffic generated in a typical smart homes environment consisting of a set of common IoT (and non-IoT) devices. We analyze the network traffic characteristics of IoT devices from three complementary aspects: remote network servers and port numbers that IoT devices connect to, flow-level traffic characteristics such as flow duration, and packet-level traffic characteristics such as packet inter-arrival time. Our study provides critical insights into the operational and behavioral characteristics of IoT devices, which can help develop more effective security and performance algorithms for IoT devices.

关键词： Internet of Things IoT Devices Smart Homes IoT Security

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Efficient and Trustworthy Authentication in 5G networks Based on Blockchain 30

Efficient and Trustworthy Authentication in 5G Networks Base...

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30th International Conference on computer communications and networks (ICCCN)

作者： Liu, Jian Huang, Chin-Tser Univ South Carolina Columbia SC 29208 USA

ISBN: (纸本)9780738113302

The global coronavirus pandemic is reshaping our daily lives and has forced many people to work and socialize remotely. This trend also increases the demand for highly available and trustworthy Internet access. Compared with 4G networks, 5G mobile networks are designed to accommodate the increasing number of mobile devices with higher transfer speed, lower latency and improved security. The 5G standard in USA uses millimeter waves, which is much shorter than 4G LTE signals. The shorter wavelength means 5G can transfer data much faster than 4G, but it also results in a much shorter travel range. When a user is moving among 5G cells, repeated authentications will increase delay time which contradicts 5G objective. The blockchain technology has the advantage of better transparency, enhanced security and high efficiency. In this paper, we propose an efficient authentication approach for 5G network using blockchain technology to reduce repeated authentications and keep the cost low and practical. We will compare it with some existing protocols and analyze its security against several possible attacks.

关键词： 5G Authentication Blockchain Security

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Research on User Access Selection Mechanism Based on Maximum Throughput for 5G Network Slicing 30

Research on User Access Selection Mechanism Based on Maximum...

引用

30th International Conference on computer communications and networks (ICCCN)

作者： Lu, Yangguang Chen, Xin Xi, Ranran Chen, Ying Beijing Informat Sci & Technol Univ Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9780738113302

With the development of Internet of Things (IoT) and network technologies, traditional networks cannot cope with the growth of network traffic and the changes in service requirements. The 5-th Generation Mobile Communication (5G) technology improves network transmission performance. In the communication network, 5G combines Software Defined Network (SDN) and Network Function Virtualization (NFV), through the deployment of end-to-end network slicing, to meet the challenge of differentiated service requirements in the complex environment. In the mobile network, users need to choose appropriate slices for access. Its performance is related to the quality of service and determines the efficiency of system resources utilization. We research the problem of slice re-access and slice resource scheduling caused by user mobility in 5G network slicing architecture and propose a slice access mechanism based on maximum throughput. A slice access selection algorithm based on genetic algorithm (GA) is proposed. Related simulations and comparative tests are carried out to prove the effectiveness and superiority of the algorithm.

关键词： 5G network slicing handover NFV SDN genetic algorithm

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Online Partial Service Hosting at the Edge 30

Online Partial Service Hosting at the Edge

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30th International Conference on computer communications and networks (ICCCN)

作者： Narayana, V. S. Ch Lakshmi Agarwala, Mohit Karamchandani, Nikhil Moharir, Sharayu Indian Inst Technol Dept Elect Engn Mumbai Maharashtra India

ISBN: (纸本)9780738113302

We consider the problem of service hosting where an application provider can dynamically rent edge computing resources and serve user requests from the edge to deliver a better quality of service. A key novelty of this work is that we allow the service to be hosted partially at the edge which enables a fraction of the user query to be served by the edge. We model the total cost for (partially) hosting a service at the edge as a combination of the latency in serving requests, the bandwidth consumption, and the time-varying cost for renting edge resources. We propose an online policy called alpha-RetroRenting (alpha-RR) which dynamically determines the fraction of the service to be hosted at the edge in any time-slot, based on the history of the request arrivals and the rent cost sequence. As our main result, we derive an upper bound on alpha-RR's competitive ratio with respect to the offline optimal policy that knows the entire request arrival and rent cost sequence in advance. We conduct extensive numerical evaluations to compare the performance of alpha-RR with various benchmarks for synthetic and trace-based request arrival and rent cost processes, and find several parameter regimes where alpha-RR's ability to store the service partially greatly improves cost-efficiency.

关键词： Partial service hosting edge computing competitive ratio online algorithms

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Storage Protection with Connectivity and Processing Restoration for Survivable Cloud Services 30

Storage Protection with Connectivity and Processing Restorat...

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30th International Conference on computer communications and networks (ICCCN)

作者： Natalino, Carlos Rostami, Ahmad Monti, Paolo Chalmers Univ Technol Dept Elect Engn SE-41296 Gothenburg Sweden Ericsson Res Farogatan 6 SE-16483 Stockholm Sweden Corp Res Robert Bosch GmbH D-70839 Gerlingen Germany

ISBN: (纸本)9780738113302

The operation and management of software-based communication systems and services is a big challenge for infrastructure and service providers. The challenge is mainly associated with the more significant number of configurable elements and the higher dynamicity in the software-based systems than the classical ones. On the other hand, the modularity and programmability in software-based networks enabled by technologies like Software-Defined Networking (SDN) and Network Function Virtualization (NFV) provide new opportunities for operators to realize advanced network and service management strategies beyond the classical techniques. In our work, we elaborate on these new opportunities and propose a novel strategy for the management of survivable cloud services. In particular, we leverage the flexibility of SDN and NFV to combine proactive protection and reactive restoration mechanisms, and we put forward a novel strategy for enhancing the survivability of cloud services. Through comprehensive evaluations, we demonstrate that the proposed strategy offers significant benefits in terms of availability and restorability of services while reducing, at the same time, the overhead caused by the relocation of cloud services in case of failures.

关键词： Software Defined Networking (SDN) Virtual Network Function (VNF) Cloud services Resiliency Protection Restoration Availability Service Relocation

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Influence Spread Control in Complex networks via Removal of Feed Forward Loops 30

Influence Spread Control in Complex Networks via Removal of ...

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30th International Conference on computer communications and networks (ICCCN)

作者： Roy, Satyaki Roy, Prithwiraj Nadendla, Venkata Sriram Siddhardh Das, Sajal K. Univ N Carolina Dept Genet Chapel Hill NC 27515 USA Missouri Univ Sci & Technol Dept Comp Sci Rolla MO 65409 USA

ISBN: (纸本)9780738113302

Selective removal of certain subgraphs called motifs based on the spread function value is one of the most powerful approaches to curb the overall influence spread in any complex network. In this paper, we first prove that any general spread function preserves both monotonicity and submodularity properties even under motif removal operations. Next, we propose a scoring mechanism as a novel spread function that quantifies the relative importance of a given motif within the overall influence spread dynamics on the complex network. We design a novel algorithm that eliminates motifs with high spread scores to curb influence spread. We evaluate the performance of our proposed spread control algorithm using simulation experiments in the context of 3-node motifs called feed forward loops (FFLs) in both real and synthetic network topologies. We demonstrate that high-scoring motifs intercept a high number of short paths from the pre-assigned source and sinks, because of which their elimination results in a significant effect on curbing the influence spread. Furthermore, we empirically evaluate the run-time and cost versus performance trade-off of the proposed algorithm.

关键词： Complex networks Influence Diffusion Motif Feed Forward Loop

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Combining Auto-Encoder with LSTM for WiFi-Based Fingerprint Positioning 30

Combining Auto-Encoder with LSTM for WiFi-Based Fingerprint ...

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30th International Conference on computer communications and networks (ICCCN)

作者： Liu, Yu-Ting Chen, Jen-Jee Tseng, Yu-Chee Li, Frank Y. Natl Yang Ming Chiao Tung Univ Coll Artificial Intelligence Taipei Taiwan Univ Agder UiA Dept Informat & Commun Technol N-4898 Grimstad Norway

ISBN: (纸本)9780738113302

Although indoor positioning has long been investigated by various means, its accuracy remains concern. Several recent studies have applied machine learning algorithms to explore wireless fidelity (WiFi)-based positioning. In this paper, we propose a novel deep learning model which concatenates an auto-encoder with a long short term memory (LSTM) network for the purpose of WiFi fingerprint positioning. We first employ an auto-encoder to extract representative latent codes of fingerprints. Such an extraction is proven to be more reliable than simply using a deep neural network to extract representative features since a latent code can be reverted back to its original input. Then, a sequence of latent codes are injected into an LSTM network to identify location. To assess the accuracy and effectiveness of our model, we perform extensive real-life experiments.

关键词： Auto-encoder LSTM WiFi RSSI fingerprint positioning indoor and outdoor environments

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