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IEEE/ACM Transactions on Networking Publication Information
Year: 2023 | Volume: 31 | Issue: 6
Achieving High Availability in Inter-DC WAN Traffic Engineering
Han Zhang;Xia Yin;Xingang Shi;Jilong Wang;Zhiliang Wang;Yingya Guo;Tian Lan;Yahui Li;Yongqing Zhu;Ke Ruan;Haijun Geng
Publication Year: 2023,Page(s):2406 - 2421
Cited by: Papers (3)
Inter-DataCenter Wide Area Network (Inter-DC WAN) that connects geographically distributed data centers is becoming one of the most critical network infrastructures. Due to limited bandwidth and inevitable link failures, it is highly challenging to guarantee network availability for services, especially those with stringent bandwidth demands, over inter-DC WAN. We present $\mathsf {TEDAT}$ , a no...Show More
A Secure and Intelligent Data Sharing Scheme for UAV-Assisted Disaster Rescue
Yuntao Wang;Zhou Su;Qichao Xu;Ruidong Li;Tom H. Luan;Pinghui Wang
Publication Year: 2023,Page(s):2422 - 2438
Cited by: Papers (45)
Unmanned aerial vehicles (UAVs) have the potential to establish flexible and reliable emergency networks in disaster sites when terrestrial communication infrastructures go down. Nevertheless, potential security threats may occur on UAVs during data transmissions due to the untrusted environment and open-access UAV networks. Moreover, UAVs typically have limited battery and computation capacity, m...Show More
Cooperation Preference Aware Shapley Value: Modeling, Algorithms and Applications
Publication Year: 2023,Page(s):2439 - 2453
Cited by: Papers (1)
The Shapley value is a cornerstone in cooperative game theory and has been widely applied in networking, data science, etc. The classical Shapley value assumes that each player has an equal preference to cooperate with each other. Since the cooperation preference is an important factor of a variety of networking applications, we first generalize the classical Shapley value to allow general degree ...Show More
Cooperation Preference Aware Shapley Value: Modeling, Algorithms and Applications
Year: 2023 | Volume: 31 | Issue: 6
Octopus: Exploiting the Edge Intelligence for Accessible 5G Mobile Performance Enhancement
Congkai An;Anfu Zhou;Jialiang Pei;Xi Liu;Dongzhu Xu;Liang Liu;Huadong Ma
Publication Year: 2023,Page(s):2454 - 2469
Cited by: Papers (3)
While 5G has rolled out since 2019 and exhibited versatile advantages, its performance under high/extreme mobility scenes (e.g., driving, high-speed railway or HSR) remains mysterious. In this work, we carry out a large-scale field-trial campaign, taking >13,000 Km round-trips on HSR moving at 250–350 Km/h, with operational 5G cellular coverage along the railway. Our empirical study reveals that c...Show More
AirNN: Over-the-Air Computation for Neural Networks via Reconfigurable Intelligent Surfaces
Sara Garcia Sanchez;Guillem Reus-Muns;Carlos Bocanegra;Yanyu Li;Ufuk Muncuk;Yousof Naderi;Yanzhi Wang;Stratis Ioannidis;Kaushik Roy Chowdhury
Publication Year: 2023,Page(s):2470 - 2482
Cited by: Papers (6)
Over-the-air analog computation allows offloading computation to the wireless environment through carefully constructed transmitted signals. In this paper, we design and implement the first-of-its-kind convolution that uses over-the-air computation and demonstrate it for inference tasks in a convolutional neural network (CNN). We engineer the ambient wireless propagation environment through reconf...Show More
Covering Users With QoS by a Connected Swarm of Drones: Graph Theoretical Approach and Experiments
Publication Year: 2023,Page(s):2483 - 2498
Cited by: Papers (6)
In this work, we study the connected version of the covering problem motivated by the coverage of ad-hoc drones’ swarm. We focus on the situation where the number of drones is given, and this number is not necessarily enough to cover all users. That is, we deal with a budget optimization problem, where the budget is the number of given drones. We assume that each ground user has different QoS requ...Show More
SlimFL: Federated Learning With Superposition Coding Over Slimmable Neural Networks
Won Joon Yun;Yunseok Kwak;Hankyul Baek;Soyi Jung;Mingyue Ji;Mehdi Bennis;Jihong Park;Joongheon Kim
Publication Year: 2023,Page(s):2499 - 2514
Cited by: Papers (10)
Federated learning (FL) is a key enabler for efficient communication and computing, leveraging devices’ distributed computing capabilities. However, applying FL in practice is challenging due to the local devices’ heterogeneous energy, wireless channel conditions, and non-independently and identically distributed (non-IID) data distributions. To cope with these issues, this paper proposes a novel ...Show More
Privacy Protection Under Incomplete Social and Data Correlation Information
Publication Year: 2023,Page(s):2515 - 2528
Data reporters have privacy concerns when they are requested to contribute personal data to a data collector. Such privacy concerns are strengthened by data correlation and social relationship, as the data correlation could inevitably cause privacy issues to their socially-connected individuals who even do not report the data. However, both factors are hard to quantify precisely in practice due to...Show More
Privacy Protection Under Incomplete Social and Data Correlation Information
Year: 2023 | Volume: 31 | Issue: 6
On the Multilayer Planning of Filterless Optical Networks With OTN Encryption
Publication Year: 2023,Page(s):2529 - 2544
Cited by: Papers (4)
With enhanced cost-effectiveness, filterless optical networks (FONs) have been considered as a promising candidate for future optical infrastructure. However, as the transmission in FON relies on the “select-and-broadcast” scenario, it is more vulnerable to eavesdropping. Therefore, encrypting the communications in FONs will be indispensable, and this can be realized by introducing the optical tra...Show More
On the Multilayer Planning of Filterless Optical Networks With OTN Encryption
Year: 2023 | Volume: 31 | Issue: 6
Simultaneous Data Dissemination Among WiFi and ZigBee Devices
Wei Wang;Xin Liu;Yao Yao;Zicheng Chi;Stuart Ray;Ting Zhu;Yanchao Zhang
Publication Year: 2023,Page(s):2545 - 2558
Cited by: Papers (2)
Recent advances in Cross-Technology Communication (CTC) have opened a new door for cooperation among heterogeneous IoT devices to support ubiquitous applications, such as smart homes and smart offices. However, existing work mainly focuses on physical layer performance improvements. In this paper, we explore how to leverage the latest CTC techniques for network layer performance improvements. Spec...Show More
Simultaneous Data Dissemination Among WiFi and ZigBee Devices
Wei Wang;Xin Liu;Yao Yao;Zicheng Chi;Stuart Ray;Ting Zhu;Yanchao Zhang
Year: 2023 | Volume: 31 | Issue: 6
StarFront: Cooperatively Constructing Pervasive and Low-Latency CDNs Upon Emerging LEO Satellites and Clouds
Publication Year: 2023,Page(s):2559 - 2574
Cited by: Papers (5)
Internet content providers (ICPs) typically exploit content distribution networks (CDNs) to provide wide-area data access with high availability and low latency. However, our analysis on a large-scale trace collected from seven major CDN operators has revealed that: from a global perspective, there are still a large portion of users suffering from high user-perceived latency due to the insufficien...Show More
Exploring the Impact of Critical Programmability on Controller Placement for Software-Defined Wide Area Networks
Publication Year: 2023,Page(s):2575 - 2588
Cited by: Papers (9)
Control latency is a critical concern for deploying Software-Defined Networking (SDN) into Wide Area Networks (WANs). A Software-Defined WAN (SD-WAN) can be divided into multiple domains controlled by multiple controllers with a logically centralized view. The control latency is related to the placement of controllers and mappings between switches and controllers. Existing solutions usually consid...Show More
The Closed Resolver Project: Measuring the Deployment of Inbound Source Address Validation
Yevheniya Nosyk;Maciej Korczyński;Qasim Lone;Marcin Skwarek;Baptiste Jonglez;Andrzej Duda
Publication Year: 2023,Page(s):2589 - 2603
Cited by: Papers (5)
Ingress filtering, commonly referred to as Source Address Validation (SAV), is a practice aimed at discarding packets with spoofed source IP addresses at the network periphery. Outbound SAV, i.e., dropping traffic with spoofed source IP addresses as it leaves its source network, has received widespread attention in operational and research communities. It is one of the most effective ways to preve...Show More
A One-Pass Clustering Based Sketch Method for Network Monitoring
Publication Year: 2023,Page(s):2604 - 2613
Network monitoring solutions need to cope with increasing network traffic volumes, as a result, sketch-based monitoring methods have been extensively studied to trade accuracy for memory scalability and storage reduction. However, sketches are sensitive to skewness in network flow distributions due to hash collisions, and need complicated performance optimization to adapt to line-rate packet strea...Show More
Enhancing TCP via Hysteresis Switching: Theoretical Analysis and Empirical Evaluation
Publication Year: 2023,Page(s):2614 - 2623
Cited by: Papers (3)
In this paper we study the relationship between the TCP packet loss cycle and the performance of time-sensitive traffic in data centers. Using real traffic measurements and analysis, we find that such loss cycles are not long enough to enable most partition-aggregate time-sensitive TCP applications to recover their packet losses via the TCP 3-dup ACKs mechanism. As a result, the Timeout (RTO) mech...Show More
Fast, Scalable and Robust Centralized Routing for Data Center Networks
Fusheng Lin;Hongyu Wang;Guo Chen;Guihua Zhou;Tingting Xu;Dehui Wei;Li Chen;Yuanwei Lu;Andrew Qu;Hua Shao;Hongbo Jiang
Publication Year: 2023,Page(s):2624 - 2639
Cited by: Papers (2)
This paper presents a fast and robust centralized data center network (DCN) routing solution, called Primus. For fast routing calculation, Primus uses centralized controllers to collect/disseminate the network’s link-states (LS), and offload the actual routing calculation onto each switch. Observing that the routing changes can be classified into a few fixed patterns in DCNs which have regular top...Show More
Optimizing Parameter Mixing Under Constrained Communications in Parallel Federated Learning
Xuezheng Liu;Zirui Yan;Yipeng Zhou;Di Wu;Xu Chen;Jessie Hui Wang
Publication Year: 2023,Page(s):2640 - 2652
Cited by: Papers (2)
In vanilla Federated Learning (FL) systems, a centralized parameter server (PS) is responsible for collecting, aggregating and distributing model parameters with decentralized clients. However, the communication link of a single PS can be easily overloaded by concurrent communications with a massive number of clients. To overcome this drawback, multiple PSes can be deployed to form a parallel FL (...Show More
CocoSketch: High-Performance Sketch-Based Measurement Over Arbitrary Partial Key Query
Ruijie Miao;Yinda Zhang;Zihao Zheng;Ruixin Wang;Ruwen Zhang;Tong Yang;Zaoxing Liu;Junchen Jiang
Publication Year: 2023,Page(s):2653 - 2668
Cited by: Papers (2)
Sketch-based measurement has emerged as a promising solutions due to its high accuracy and resource efficiency. Prior sketches focus on measuring single flow keys and cannot support measurement on multiple keys. This work takes a significant step towards supporting arbitrary partial key queries, which aims to provide information for any key in the predefined range of possible flow keys. The design...Show More
Optimal Oblivious Routing With Concave Objectives for Structured Networks
Kanatip Chitavisutthivong;Sucha Supittayapornpong;Pooria Namyar;Mingyang Zhang;Minlan Yu;Ramesh Govindan
Publication Year: 2023,Page(s):2669 - 2681
Oblivious routing distributes traffic from sources to destinations following predefined routes with rules independent of traffic demands. While finding optimal oblivious routing with a concave objective is intractable for general topologies, we show that it is tractable for structured topologies often used in datacenter networks. To achieve this, we apply graph automorphism and prove the existence...Show More
Multi-Edge Server-Assisted Dynamic Federated Learning With an Optimized Floating Aggregation Point
Bhargav Ganguly;Seyyedali Hosseinalipour;Kwang Taik Kim;Christopher G. Brinton;Vaneet Aggarwal;David J. Love;Mung Chiang
Publication Year: 2023,Page(s):2682 - 2697
Cited by: Papers (10)
We propose cooperative edge-assisted dynamic federated learning (CE-FL). CE-FL introduces a distributed machine learning (ML) architecture, where data collection is carried out at the end devices, while the model training is conducted cooperatively at the end devices and the edge servers, enabled via data offloading from the end devices to the edge servers through base stations. CE-FL also introdu...Show More
Constrained Network Slicing Games: Achieving Service Guarantees and Network Efficiency
Publication Year: 2023,Page(s):2698 - 2713
Cited by: Papers (9)
Network slicing is a key capability for next generation mobile networks. It enables infrastructure providers to cost effectively customize logical networks over a shared infrastructure. A critical component of network slicing is resource allocation, which needs to ensure that slices receive the resources needed to support their services while optimizing network efficiency. In this paper, we propos...Show More
Crowdfunding With Cognitive Limitations
Publication Year: 2023,Page(s):2714 - 2729
Cited by: Papers (1)
To achieve the desirable funding target in a crowdfunding campaign, the project creator needs to accurately anticipate the pledging behaviors of contributors with practical cognitive limitations. In this paper, we present a study on how the contributors’ cognitive bounded rationality affects the creator’s campaign decisions. Specifically, we consider a two-stage crowdfunding model, where a creator...Show More
Online Learning for Failure-Aware Edge Backup of Service Function Chains With the Minimum Latency
Publication Year: 2023,Page(s):2730 - 2744
Cited by: Papers (4)
Virtual network functions (VNFs) have been widely deployed in mobile edge computing (MEC) to flexibly and efficiently serve end users running resource-intensive applications, which can be further serialized to form service function chains (SFCs), providing customized networking services. To ensure the availability of SFCs, it turns out to be effective to place redundant SFC backups at the edge for...Show More
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