Article
Computer Science, Information Systems
Gang Li, Jun Cai, Xianfu Chen, Zhou Su
Summary: This paper studies task offloading in edge computing systems and proposes an incentive mechanism design problem considering the unique characteristics of these systems. It introduces a novel online incentive mechanism called Integrate Rounding Scheme based Maxima-in-distributional Range (IRSM) and verifies its effectiveness through theoretical analysis and comprehensive simulations.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Engineering, Multidisciplinary
Shiyuan Zheng, Hong Xie, John C. S. Lui
Summary: Online social networks (OSNs) provide important platforms for users to share information and enhance their social visibility. In this study, we propose a mechanism where the OSN operator offers a social visibility boosting service, incentivizing transactions between requesters and suppliers. We design a pricing scheme to charge requesters and reward suppliers, while the OSN operator keeps a fraction of the payment and distributes the rest to participating suppliers fairly. We consider two objectives of the OSN provider and develop an efficient approximation algorithm to solve the problems with provable theoretical guarantee.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Yifan Wang, Shuai Liu, Bo Sun, Xiuxian Li
Summary: This article addresses the issue of distributed energy management in smart grids by proposing a distributed algorithm for solving composite problems with smooth and nonsmooth terms. The algorithm achieves global optimality through local computation and communication, demonstrating its effectiveness through multiple simulations.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Environmental
Zhisong Chen, Keith C. K. Cheung
Summary: The study shows that supply chains only have internal incentives for water-saving management under low or medium cost scenarios, and the government only has external incentives for subsidizing water-saving behaviors and effects under medium-cost scenarios. The coordination strategy outperforms the equilibrium strategy in all situations, while a niche targeting subsidy policy based on actual water-saving effects can achieve social welfare maximization.
WATER ENVIRONMENT RESEARCH
(2021)
Article
Computer Science, Information Systems
Tong Liu, Yameng Zhang, Yanmin Zhu, Weiqin Tong, Yuanyuan Yang
Summary: This article introduces an optimized task offloading strategy based on mobile-edge computing in an ultradense network. A double deep Q network (DDQN) approach is proposed using reinforcement learning, along with a context-aware attention mechanism. Extensive simulations demonstrate the effectiveness of the proposed method.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Economics
Jiantao Guo, Juliang Zhang, T. C. E. Cheng, Shouting Zhao
Summary: In recent years, many online freight platforms have emerged to improve transport market efficiency and address the issue of supply-demand matching. Various mechanisms have been proposed to consider different transaction costs and information asymmetry. Numerical studies indicate that these mechanisms are more effective than traditional ones.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Computer Science, Theory & Methods
Xingqiu He, Yuhang Shen, Jing Ren, Sheng Wang, Xiong Wang, Shizhong Xu
Summary: This paper proposes an online auction-based incentive mechanism for task allocation and resource utilization in collaborative edge computing systems. The mechanism is proven to have desirable properties through theoretical analysis, and its effectiveness is validated through simulation experiments.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Suzhen Wang, Zhongbo Hu, Yongchen Deng, Lisha Hu
Summary: Task offloading and resource allocation are crucial in edge computing, as they can reduce processing time and energy consumption. Current studies mainly focus on resource allocation between terminals and edge servers, disregarding the computing resources in the cloud center. To address this, we propose a coarse-grained task offloading strategy and intelligent resource matching scheme that leverages both cloud and edge server resources. Our approach considers mobile device heterogeneity and inter-channel interference, and maximizes system utility through a game-theory-based task migration model. Experimental results demonstrate the superiority of our scheme in terms of latency, energy consumption, and scalability.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Software Engineering
Ioannis Caragiannis, Aris Filos-Ratsikas, Swaprava Nath, Alexandros A. Voudouris
Summary: This study considers a social welfare maximizing approach to design and analyze truthful mechanisms in hybrid social choice settings. The results show that the cardinal setting is quite rich and allows for several non-trivial randomized truthful mechanisms.
MATHEMATICAL PROGRAMMING
(2022)
Article
Telecommunications
Tao Li, Yanqing Wang, Yongjun Ren, Yongzhen Ren, Qi Qian, Xi Gong
Summary: This article introduces a privacy protection algorithm for recommendation systems in cloud computing, which uses nonnegative matrix factorization and random perturbation technology to generate accurate recommendation results while protecting user privacy.
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
(2022)
Article
Telecommunications
Cuili Jiang, Tengfei Cao, Jianfeng Guan
Summary: This paper studies the problem of computation offloading in a mobile edge computation-enabled cell networks and proposes an intelligent task offloading and collaborative computation scheme based on collaborator screening and Lyapunov stochastic optimization theory to achieve optimal computation offloading.
CHINA COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Wenqi Zhou, Junjuan Xia, Fasheng Zhou, Lisheng Fan, Xianfu Lei, Arumugam Nallanathan, George K. Karagiannidis
Summary: This paper investigates a multiuser cache-enabled vehicular mobile edge computing (MEC) network, and proposes a solution to the critical challenge of optimizing the system design and performance by maximizing the profit of the edge server (ES) and jointly exploiting caching and computing resources.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Guoyao Rao, Deying Li, Yongcai Wang, Wenping Chen, Chunlai Zhou, Yuqing Zhu
Summary: This paper discusses the impact of widespread dissemination of information on social media platforms on people's behavior, particularly online conflicts in social networks. It proposes an optimization algorithm to strategically select influencers who can mitigate conflicts. Experimental results show the algorithm outperforms other methods.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Information Systems
Fangming Liu, Jian Chen, Qixia Zhang, Bo Li
Summary: As a technology for vehicle-to-vehicle networks, multi-access edge computing provides a platform for sharing power and resources and offloading computation-intensive tasks between vehicles. However, in MEC-enabled V2V networks, the unpredictable variations in road traffic conditions and vehicle mobility make computation task offloading challenging and disruptive, affecting the Quality of Service. This paper proposes a distributed Online Instability-aware Computation Offloading algorithm to improve service efficiency and quality.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Xi Liu, Jun Liu
Summary: This study addresses the problem of online virtual machine provisioning and allocation, proposing a mathematical model and designing offline and online mechanisms. Experimental results demonstrate that our proposed online greedy mechanism achieves near-optimal solutions in a reasonable time.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Di Zhang, Yujian Fang, Yuezhi Zhou, Junyi He, Yaoxue Zhang
Summary: This paper proposes a game theoretic approach to enable D2D content sharing with multihop communication capabilities. It models a Nash bargaining game and introduces a novel incentive mechanism to stimulate cooperation. Experimental results demonstrate the effectiveness of the approach in dealing with participant selection, routing, and pricing problems.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
