IEEE Transactions on Computational Social Systems
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IEEE Transactions on Computational Social Systems Publication Information
Publication Year: 2022,Page(s):C2 - C2
IEEE Transactions on Computational Social Systems Publication Information
Year: 2022 | Volume: 9 | Issue: 1
MetaSocieties in Metaverse: MetaEconomics and MetaManagement for MetaEnterprises and MetaCities
Publication Year: 2022,Page(s):2 - 7
Cited by: Papers (159)
A Grammar-Based Behavioral Distance Measure Between Ransomware Variants
Publication Year: 2022,Page(s):8 - 17
Cited by: Papers (3)
Effective attribution of ransomware attacks requires a way to characterize different variants and estimates their similarity to one another. Unlike other malware, ransomware deliberately discloses itself and interacts explicitly with the victim. This characteristic invites the application of insights from social systems. The resulting behavioral trace offers a richer characterization than the simp...Show More
An Overview of Correlation-Filter-Based Object Tracking
Publication Year: 2022,Page(s):18 - 31
Cited by: Papers (28)
In the last two decades, object tracking has been one of the prevalent fields in social media. Object tracking uses a dynamic model to track the same target, aiming to analyze the same social object and its behavior in a set of consecutive video frames. In this article, we provide a comprehensive survey on some representative and latest correlation-filter-based object tracking methods and compare ...Show More
Social Phenomena and Fog Computing Networks: A Novel Perspective for Future Networks
Shanshan Tu;Muhammad Waqas;Sadaqat Ur Rehman;Talha Mir;Zahid Halim;Iftekhar Ahmad
Publication Year: 2022,Page(s):32 - 44
Cited by: Papers (25)
Fog computing is an emerging technology that aims at reducing the load on cloud data centers by migrating some computation and storage toward end-users. It leverages the intermediate servers for local processing and storage while making it possible to offload part of the computation and storage to the cloud. Inspired by the benefits of fog computing, we present a novel paradigm that considers the ...Show More
Game Starts at GameStop: Characterizing the Collective Behaviors and Social Dynamics in the Short Squeeze Episode
Xiaolong Zheng;Hu Tian;Zhe Wan;Xiao Wang;Daniel Dajun Zeng;Fei-Yue Wang
Publication Year: 2022,Page(s):45 - 58
Cited by: Papers (6)
In January 2021, the users of subreddit r/wallstreetbets (WSB) triggered an unprecedented short squeeze by driving up GameStop’s stock price to an unimaginable high point. During the event, a large number of users participated in the discussion about GameStop and coordinated trading behavior on r/WSB to push the stock price higher. In this article, we investigate the characteristics of the collect...Show More
Guest Editorial Special Issue on Collaborative Edge Computing for Social Internet of Things Systems
Zhaolong Ning;Meng Chu Zhou;Yong Yuan;Edith C. H. Ngai;Ricky Yu-Kwong Kwok
Publication Year: 2022,Page(s):59 - 63
Cited by: Papers (4)
Dynamic Games for Social Model Training Service Market via Federated Learning Approach
Publication Year: 2022,Page(s):64 - 75
Cited by: Papers (13)
In recent years, an increasing amount of new social applications have been emerging and developing with the profound success of deep learning technologies, which have been significantly reshaping our daily life, e.g., interactive games and virtual reality. Deep learning applications are generally driven by a huge amount of training samples collected from the users’ participation, e.g., smartphones...Show More
Secure Edge-Aided Computations for Social Internet-of-Things Systems
Hanlin Zhang;Jia Yu;Mohammad S. Obaidat;Pandi Vijayakumar;Linqiang Ge;Jie Lin;Jianxi Fan;Rong Hao
Publication Year: 2022,Page(s):76 - 87
Cited by: Papers (17)
Devices in the Internet-of-Things (IoT) are networked and perform massive computations to support various social IoT systems. Applications in social IoT systems often involve complicated computations that are out of the computation capacity of some resource-constrained IoT devices. Thus, how to enable resource-constrained IoT devices to accomplish complex computations efficiently and securely is o...Show More
Privacy-Aware Collaborative Task Offloading in Fog Computing
Publication Year: 2022,Page(s):88 - 96
Cited by: Papers (20)
Numerous new applications have been proliferated with the mature of 5G, which generates a large number of latency-sensitive and computationally intensive mobile data requests. The real-time requirement of these mobile data has been accommodated well by fog computing in the past few years, mainly through offloading tasks to fog nodes in the vicinity. On the other hand, the user-privacy hidden in th...Show More
A Security- and Privacy-Preserving Approach Based on Data Disturbance for Collaborative Edge Computing in Social IoT Systems
Peiying Zhang;Yaqi Wang;Neeraj Kumar;Chunxiao Jiang;Guowei Shi
Publication Year: 2022,Page(s):97 - 108
Cited by: Papers (34)
The Internet of things (IoT) has certainly become one of the hottest technology frameworks of the year. It is deep in many industries, affecting people’s lives in all directions. The rapid development of the IoT technology accelerates the process of the era of “Internet of everything” but also changes the role of terminal equipment at the edge of the network. It has changed from a single data user...Show More
Joint Optimization of Task Offloading and Resource Allocation Based on Differential Privacy in Vehicular Edge Computing
Publication Year: 2022,Page(s):109 - 119
Cited by: Papers (39)
In the Internet of Vehicles (IoVs), task offloading is necessary to ensure the low-response delay due to the limitation of vehicular computational capacity. Task offloading involving social behavior can improve the utilization of computational resources in IoVs. To offload tasks effectively, the connected vehicles (CVs) need to upload context information, such as speed and location to road side un...Show More
Accurate and Privacy-Preserving Task Allocation for Edge Computing Assisted Mobile Crowdsensing
Zhihua Wang;Chaoqi Guo;Jiahao Liu;Jiamin Zhang;Yongjian Wang;Jingtang Luo;Xiaolong Yang
Publication Year: 2022,Page(s):120 - 133
Cited by: Papers (20)
Mobile crowdsensing (MCS) has heated up and has become a new paradigm of data collection. In the process of the task allocation of MCS, users are often required to provide their own location information with the server to conveniently dispatch some suitable tasks to them. However, it is possible for malicious servers to infer some sensitive information based on the user’s location such as the user...Show More
Intrusion Detection for Secure Social Internet of Things Based on Collaborative Edge Computing: A Generative Adversarial Network-Based Approach
Laisen Nie;Yixuan Wu;Xiaojie Wang;Lei Guo;Guoyin Wang;Xinbo Gao;Shengtao Li
Publication Year: 2022,Page(s):134 - 145
Cited by: Papers (89)
The Social Internet of Things (SIoT) now penetrates our daily lives. As a strategy to alleviate the escalation of resource congestion, collaborative edge computing (CEC) has become a new paradigm for solving the needs of the Internet of Things (IoT). CEC can provide computing, storage, and network connection resources for remote devices. Because the edge network is closer to the connected devices,...Show More
A Blockchain-Based Mutual Authentication Scheme for Collaborative Edge Computing
Guanjie Cheng;Yan Chen;Shuiguang Deng;Honghao Gao;Jianwei Yin
Publication Year: 2022,Page(s):146 - 158
Cited by: Papers (43)
With the ever-increasing requirements of delay-sensitive and mission-critical applications, it becomes a popular research trend to incorporate edge computing in the Internet of Things (IoT) to mitigate the pressure of traditional cloud-based IoT architecture. Edge computing delivers real-time computations and communications for IoT devices by leveraging edge servers deployed close to users, which ...Show More
Privacy-Preserving Blockchain-Based Federated Learning for Marine Internet of Things
Publication Year: 2022,Page(s):159 - 173
Cited by: Papers (28)
The marine Internet of things (MIoT) is the application of the Internet of things technology in the marine field. Nowadays, with the arrival of the era of big data, the MIoT architecture has been transformed from cloud computing architecture to edge computing architecture. However, due to the lack of trust among edge computing participants, new solutions with higher security need to be proposed. I...Show More
Conditional Support-Vector-Machine-Based Shared Adaptive Computing Model for Smart City Traffic Management
Gunasekaran Manogaran;Joel J. P. C. Rodrigues;Sergei A. Kozlov;Karthikbala Manokaran
Publication Year: 2022,Page(s):174 - 183
Cited by: Papers (15)
Smart connected vehicles are becoming standardized with the incorporation of information and communication technology. Connected vehicles are employed for surveillance and management of road traffic, navigation assistance, etc., by inheriting different analytical and communication techniques. With the Social Internet of Things (SIoT), interogrowthperable and shared computing models are adopted by ...Show More
Collaborative Edge Computing for Social Internet of Vehicles to Alleviate Traffic Congestion
Publication Year: 2022,Page(s):184 - 196
Cited by: Papers (24)
Edge computing in vehicles is emerging as an essential candidate for the Internet of Vehicles (IoV) to improve traffic efficiency. The proliferation of IoV pushes the horizon of edge computing. The social features and connections among vehicles are significant for traffic efficiency solutions. However, it is quite challenging to perform collaborative edge computing (CEC) for social IoV systems bec...Show More
FedVCP: A Federated-Learning-Based Cooperative Positioning Scheme for Social Internet of Vehicles
Xiangjie Kong;Haoran Gao;Guojiang Shen;Gaohui Duan;Sajal K. Das
Publication Year: 2022,Page(s):197 - 206
Cited by: Papers (68)
Intelligent vehicle applications, such as autonomous driving and collision avoidance, put forward a higher demand for precise positioning of vehicles. The current widely used global navigation satellite systems (GNSS) cannot meet the precision requirements of the submeter level. Due to the development of sensing techniques and vehicle-to-infrastructure (V2I) communications, some vehicles can inter...Show More
Social Prediction-Based Handover in Collaborative-Edge-Computing-Enabled Vehicular Networks
Publication Year: 2022,Page(s):207 - 217
Cited by: Papers (13)
Collaborative edge computing (CEC) can realize the cooperation and integration of heterogeneous resources distributed in adjacent areas, increasing the overall resource utilization efficiency. In a CEC-supported heterogeneous vehicular network composed of different access solutions, including cellular vehicle-to-everything (C-V2X) and dedicated short-range communications (DSRC), good network conne...Show More
Energy–Delay Tradeoff in Adaptive Cooperative Caching for Energy-Harvesting Ultradense Networks
Publication Year: 2022,Page(s):218 - 229
Cited by: Papers (8)
Edge caching in collaborative edge computing (CEC) is a resource-friendly technique to improve energy efficiency and alleviate backhaul link congestion. Caching diverse contents based on the social features among users at energy-harvesting-powered (EH-powered) small base stations can further save on-grid energy, but it may lead to a longer delay to mobile users (MUs). In this article, we focus on ...Show More
Collaborative Caching for Energy Optimization in Content-Centric Internet of Things
Publication Year: 2022,Page(s):230 - 238
Cited by: Papers (16)
The development of the content-centric Internet of Things (C2IoT) enriches the services provided by the IoT devices, which diversifies the provided contents. However, system resources are terribly wasted by repeated delivering the same content. Efficiently utilizing caching resources can reduce the link load caused by delivering and forwarding contents, further improving the users’ quality of expe...Show More
Digital Twin Empowered Content Caching in Social-Aware Vehicular Edge Networks
Publication Year: 2022,Page(s):239 - 251
Cited by: Papers (86)
The rapid proliferation of smart vehicles along with the advent of powerful applications bring stringent requirements on massive content delivery. Although vehicular edge caching can facilitate delay-bounded content transmission, constrained storage capacity and limited serving range of an individual cache server as well as highly dynamic topology of vehicular networks may degrade the efficiency o...Show More
Collaborative Edge Computing With FPGA-Based CNN Accelerators for Energy-Efficient and Time-Aware Face Tracking System
Xing Liu;Jianfeng Yang;Chengming Zou;Qimei Chen;Xin Yan;Yuao Chen;Chenran Cai
Publication Year: 2022,Page(s):252 - 266
Cited by: Papers (43)
Convolutional neural networks (CNNs) have become the critical technology to realize face detection and face recognition in the face tracking (FT) system. However, traditional CNNs usually have nontrivial computational time and high energy consumption, making them inappropriate to be deployed in the large-scale time-sensitive FT system. To address this challenge, we design an artificial intelligenc...Show More
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