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

共 4934 条记录，以下是251-260 订阅

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WiFresh: Age-of-Information from Theory to Implementation 30

WiFresh: Age-of-Information from Theory to Implementation

引用

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

作者： Kadota, Igor Rahman, Muhammad Shahir Modiano, Eytan Columbia Univ Dept Elect Engn New York NY 10027 USA MIT Lab Informat & Decis Syst LIDS Cambridge MA 02139 USA

ISBN: (纸本)9780738113302

Emerging applications, such as smart factories and fleets of drones, increasingly rely on sharing time-sensitive information for monitoring and control. In such application domains, it is essential to keep information fresh, as outdated information loses its value and can lead to system failures and safety risks. The Age-of-Information is a performance metric that captures how fresh the information is from the perspective of the destination. In this paper, we show that as the congestion in the wireless network increases, the Age-of-Information degrades sharply, leading to outdated information at the destination. Leveraging years of theoretical research, we propose WiFresh: an unconventional architecture that achieves near optimal information freshness in wireless networks of any size, even when the network is overloaded. Our experimental results show that WiFresh can improve information freshness by two orders of magnitude when compared to an equivalent standard WiFi network. We propose and realize two strategies for implementing WiFresh: one at the MAC layer using hardware-level programming and another at the Application layer using Python.

关键词： Age of Information Implementation Software Defined Radio Wireless networks Optimization

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A Framework for Edge Intelligent Smart Distribution Grids via Federated Learning 30

A Framework for Edge Intelligent Smart Distribution Grids vi...

引用

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

作者： Hudson, Nathaniel Hossain, Md Jakir Hosseinzadeh, Minoo Khamfroush, Hana Rahnamay-Naeini, Mahshid Ghani, Nasir Univ Kentucky Dept Comp Sci Lexington KY 40506 USA Univ S Florida Dept Elect Engn Tampa FL 33620 USA

ISBN: (纸本)9780738113302

Recent advances in distributed data processing and machine learning provide new opportunities to enable critical, time-sensitive functionalities of smart distribution grids in a secure and reliable fashion. Combining the recent advents of edge computing (EC) and edge intelligence (EI) with existing advanced metering infrastructure (AMI) has the potential to reduce overall communication cost, preserve user privacy, and provide improved situational awareness. In this paper, we provide an overview for how EC and EI can supplement applications relevant to AMI systems. Additionally, using such systems in tandem can enable distributed deep learning frameworks (e.g., federated learning) to empower distributed data processing and intelligent decision making for AMI. Finally, to demonstrate the efficacy of this considered architecture, we approach the non-intrusive load monitoring (NILM) problem using federated learning to train a deep recurrent neural network architecture in a 2-tier and 3-tier manner. In this approach, smart homes locally train a neural network using their metering data and only share the learned model parameters with AMI components for aggregation. Our results show this can reduce communication cost associated with distributed learning, as well as provide an immediate layer of privacy, due to no raw data being communicated to AMI components. Further, we show that FL is able to closely match the model loss provided by standard centralized deep learning where raw data is communicated for centralized training.

关键词： Smart grid Federated learning Edge Computing Advanced metering infrastructure Distribution network Cyber-physical systems Non-intrusive Load Monitoring (NILM)

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Tagged Cuckoo Filters 30

Tagged Cuckoo Filters

引用

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

作者： Huang, Kun Yang, Tong Southern Univ Sci & Technol Shenzhen Peoples R China Peng Cheng Lab Shenzhen Peoples R China Peking Univ Beijing Peoples R China

ISBN: (纸本)9780738113302

Bloom filters (BFs) are space-efficient randomized data structures used for fast set membership queries in many applications. The standard BF allows a small fraction of false positives for high space efficiency, but does not support deletions of items. The state-of-the-art cuckoo filter (CF) extends the standard BF to support deletions while achieving higher performance and lower space cost. However, the CF suffers a critical issue of varying space cost per item. This is because the exclusive-OR (XOR) operation used by the CF requires the total number of buckets to be a power of two, leading to the inflation of space. To address the issue, in this paper we propose a scalable variant of the CF called tagged cuckoo filter (TCF). The TCF uses a tagged fingerprint of an item, instead of an untagged fingerprint used by the CF, to compute its two candidate bucket indexes. With a tag of a fingerprint, the TCF does not require the number of buckets to be a power of two, which results in low space cost per item. Experimental results show that the TCF improves the space efficiency while sustaining high performance. Compared to the CF, the TCF reduces up to 2x space cost per item as well as achieves comparable lookup and update performance. In addition, the TCF outperforms other filters in both space cost and performance for same false positive rates.

关键词： Bloom filters cuckoo filters cuckoo hashing

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Smart replication for seamless and efficient real time communication in underground railway train 30

Smart replication for seamless and efficient real time commu...

引用

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

作者： Fahmi, Kariem Leith, Douglas Trinity Coll Dublin Dublin Ireland

ISBN: (纸本)9780738113302

In this paper, we consider the task of transporting mission-critical traffic, with strict QoS requirements for high availability and low packet loss, in underground trains that are equipped with multiple WiFi backhauls. We observe that the commonly used simple replication approach for mitigating frequent handovers comes at the cost of many duplicate packet transmissions and so wasted network capacity. Instead we take the approach of predicting when a handover is about to occur and only replicating packets shortly before it happens, significantly reducing the amount of redundancy needed and freeing up network resources. We propose a novel neural network predictor, based only on features extracted from the WiFi client log, that predicts when a handover will occur. We train and evaluate our predictor on a large data set collected in a production environment, and show it predicts handover with high accuracy. We use this predictor as a basis for an adaptive replication scheme and compare it against simple replication and no replication. Results show that when application throughput is low compared to link capacity, our scheme achieves 91 % of the loss reduction provided by simple replication on average while using only 13% of the redundancy and experiencing 20% less latency. When application throughput is high compared to link capacity, simple replication causes more losses compared to no replication, while our scheme maintains a lower loss rate compared to no replication.

关键词： Adaptation models Redundancy Packet loss Handover Predictive models Feature extraction Throughput

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An Open, Real-World Dataset of Cellular UAV Communication Properties 30

An Open, Real-World Dataset of Cellular UAV Communication Pr...

引用

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

作者： Martinez, Gonzalo J. Dubrovskiy, Grigoriy Zhu, Shangyue Mohammed, Alamin Lin, Hai Laneman, J. Nicholas Striegel, Aaron D. Pragada, Ravikumar, V Castor, Douglas R. Univ Notre Dame Notre Dame IN 46556 USA InterDigital Commun Wilmington DE USA

ISBN: (纸本)9780738113302

In the past few years, unmanned aerial vehicles (UAVs) have drastically increased in popularity both from consumer and industry perspectives. A key component towards enabling the widespread usage of UAVs is the ability to stay in near-constant communication with the drone for command and control and conveying relevant instrumentation. The usage of cellular technology, namely LTE, seems to be a natural fit for addressing coverage and Line of Sight (LoS) issues. However, there is a relative dearth of data, specifically open source data that explores key performance aspects of cellular at altitudes typically envisioned for commercial UAV operation. The key contribution of this paper is to analyze data taken from numerous drone flights that include varying altitudes, locations, and multiple cellular carriers as recorded in a medium-sized Midwestern city. Further, we offer our data as an open-source repository for the community offering multiple vantage points for the various runs including the operating system, chipset (through MobileInsight), drone instrumentation, and server-side packet captures as part of the recorded data streams.

关键词： UAVs Drones Drone Control LTE Cellular

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Validation and Benchmarking of CNFs in OSM for pure Cloud Native applications in 5G and beyond 30

Validation and Benchmarking of CNFs in OSM for pure Cloud Na...

引用

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

作者： Pino, Adrian Khodashenas, Pouria Hesselbach, Xavier Coronado, Estefania Siddiqui, Shuaib I2CAT Fdn Barcelona Spain Univ Politecn Catalunya UPC Dept Network Engn Barcelona Spain

ISBN: (纸本)9780738113302

Cloud Native (CN) in 5G systems has been identified as a pivotal candidate for operational and capital expenditure savings as well as for improvements in system agility and services role-out. CN telco is a step forward with respect to Network Function Virtualisation (NFV) aiming at embracing a microservice-based architecture. With this in mind, the European Telecommunications Standards Institute (ETSI) has evolved the ETSI NFV reference architecture to adapt to CN and fill the gap with the NFV framework, including containers and Zero-Touch, among other capabilities. Open-source Management & Orchestration (MANO) initiatives, such as Open Source MANO (OSM), are promoting this adoption giving support to CN solutions based on containers. However, at this early stage deployments are currently non-standalone and embedded in VNF-based solutions such as OpenStack. In this context, this paper presents a proof of concept of a full container technology deployment -via Kubernetes- in a NFV architecture. First, a full CN NFV environment is set with the help of OSM MANO, for which we describe the implementation to enable native kubernetes-based Container Network Functions (CNFs) and analyse their performance, limits, advantages and drawbacks. Finally, our solution for CNFs is benchmarked against a typical OSM-OpenStack setup where VNFs are deployed. The results obtained in this work can help to further encourage users and operators to use CNFs and get the most out of containerisation in NFV.

关键词： NFV 5G Cloud Native OSM K8s

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Def-IDS: An Ensemble Defense Mechanism Against Adversarial Attacks for Deep Learning-based Network Intrusion Detection 30

Def-IDS: An Ensemble Defense Mechanism Against Adversarial A...

引用

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

作者： Wang, Jianyu Pan, Jianli AlQerm, Ismail Liu, Yuanni Univ Missouri Dept Comp Sci St Louis MO 63121 USA Chongqing Univ Posts & Telecommun Inst Future Network Technol Chongqing Peoples R China

ISBN: (纸本)9780738113302

Network intrusion detection plays an important role in the Internet of Things systems for protecting devices from security breaches. Facing challenges of the rapidly increasing amount of diverse network traffic, recent research has employed end-to-end deep learning-based intrusion detectors for automatic feature extraction and high detection accuracy. However, deep learning has been proved vulnerable to adversarial attacks that may cause misclassification by imposing imperceptible perturbation on input samples. Though such vulnerability is widely discussed in the image processing domain, very few studies have investigated its perniciousness against network intrusion detection systems (NIDS) and proposed corresponding defense strategies. In this paper, we try to fill this gap by proposing Def-IDS, an ensemble defense mechanism specially designed for NIDS, against both known and unknown adversarial attacks. It is a two-module training framework that integrates multi-class generative adversarial networks and multi-source adversarial retraining to improve model robustness, while the detection accuracy on unperturbed samples is maintained. We evaluate the mechanism over CSE-CIC-IDS2018 dataset and compare its performance with the other three defense methods. The results demonstrate that Def-IDS is able to detect various adversarial attacks with better precision, recall, F1 score, and accuracy.

关键词： Network intrusion detection adversarial attacks deep learning

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Engineering an IoT-Edge-Cloud Computing System Architecture: Lessons Learnt from An Undergraduate Lab Course 30

Engineering an IoT-Edge-Cloud Computing System Architecture:...

引用

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

作者： Dizdarevic, Jasenka Jukan, Admela Tech Univ Carolo Wilhelmina Braunschweig Braunschweig Germany

ISBN: (纸本)9780738113302

With the rapid advances in IoT, edge and cloud computing solutions, it is critical to educate and train students in computer science and engineering in various aspects of IoT-edge-cloud (IoT-E-C) system architecture implementations. We outline the design and development of an undergraduate laboratory course that sets the goal of implementing various interfaces and communication protocols to connect IoT, edge and cloud computing systems and evaluating their performance. The lab setup is modular and based on open source tools. In the IoT context, it consists of low-cost processing platforms with various sensors and actuators. In the edge and cloud computing context, we implement and deploy single board computers and Firebase cloud solutions, respectively. The modular lab setup allows students to engineer and integrate various communication protocol solutions, including MQTT, COAP and HTTP. In addition to the system implementation, students can evaluate and benchmark the performance of the entire system.

关键词： Edge and cloud computing communication protocols IoT

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A P4-Based Packet Scheduling Approach for Clustered Deep Packet Inspection Appliances 30

A P4-Based Packet Scheduling Approach for Clustered Deep Pac...

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

作者： Jiang, Ping Zhang, Shuo Liu, Qingyun Zheng, Chao Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China Natl Engn Lab Informat Secur Technol Beijing Peoples R China Geedge Networks Beijing Peoples R China

ISBN: (纸本)9780738113302

Packet scheduling approach enables clustered deep packet inspection (DPI) appliances to achieve stateful packet processing through efficient cooperation. In this paper, we propose a novel methodology of packet scheduling, called P4CLUS, for clustering DPI appliances efficiently. P4CLUS eliminates unnecessary packet transmission between peer nodes via the idea of packet path prediction. It performs sketch-based measurement on traffic handling nodes to record their flow distributions and then compresses the results to a compact packet forwarding table. Our approach guarantees per-flow consistency with lower bandwidth overhead and is effective in the practice of eliminating asymmetric traffic in stateful DPI. We construct the P4CLUS prototype with P4 on Protocol-Independent Switch Architecture (PISA). Our evaluation shows that P4CLUS can reduce the bandwidth overhead by up to 73.75% than the hash-based method, and only requires 2MB SRAM and 80KB TCAM resources at most.

关键词： packet scheduling asymmetric traffic prediction P4CLUS

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mck8s: An orchestration platform for geo-distributed multi-cluster environments 30

mck8s: An orchestration platform for geo-distributed multi-c...

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

作者： Tamiru, Mulugeta Ayalew Pierre, Guillaume Tordsson, Johan Elmroth, Erik Elastisys AB Umea Sweden Univ Rennes IRISA CNRS INRIA Rennes France

ISBN: (纸本)9780738113302

Following the adoption of cloud computing, the proliferation of cloud data centers in multiple regions, and the emergence of computing paradigms such as fog computing, there is a need for integrated and efficient management of geo-distributed clusters. Geo-distributed deployments suffer from resource fragmentation, as the resources in certain locations are over-allocated while others are under-utilized. Orchestration platforms such as Kubernetes and Kubernetes Federation offer the conceptual models and building blocks that can be used to build integrated solutions that address the resource fragmentation challenge. In this work, we propose mck8s - an orchestration platform for multi-cluster applications on multiple geo-distributed Kubernetes clusters. It offers controllers that automatically place, scale, and burst multi-cluster applications across multiple geo-distributed Kubernetes clusters. mck8s allocates the requested resources to all incoming applications while making efficient use of resources. We designed mck8s to be easy to use by development and operation teams by adopting Kubernetes' design principles and manifest files. We evaluated mck8s in a geo-distributed experimental testbed in Grid'5000. Our results show that mck8s balances the resource allocation across multiple clusters and reduces the fraction of pending pods to 6% as opposed to 65% in the case of Kubernetes Federation for the same workload.

关键词： Resource provisioning placement scheduling autoscaling Kubernetes multi-cluster

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