Symmetry

Research

21 pages, 905 KiB

Open AccessArticle

Flexible Offloading and Task Scheduling for IoT Applications in Dynamic Multi-Access Edge Computing Environments

by Yang Sun, Yuwei Bian, Huixin Li, Fangqing Tan and Lihan Liu

Symmetry 2023, 15(12), 2196; https://doi.org/10.3390/sym15122196 - 14 Dec 2023

Cited by 1 | Viewed by 1782

Nowadays, multi-access edge computing (MEC) has been widely recognized as a promising technology that can support a wide range of new applications for the Internet of Things (IoT). In dynamic MEC networks, the heterogeneous computation capacities of the edge servers and the diversified [...] Read more.

Nowadays, multi-access edge computing (MEC) has been widely recognized as a promising technology that can support a wide range of new applications for the Internet of Things (IoT). In dynamic MEC networks, the heterogeneous computation capacities of the edge servers and the diversified requirements of the IoT applications are both asymmetric, where and when to offload and schedule the time-dependent tasks of IoT applications remains a challenge. In this paper, we propose a flexible offloading and task scheduling scheme (FLOATS) to adaptively optimize the computation of offloading decisions and scheduling priority sequences for time-dependent tasks in dynamic networks. We model the dynamic optimization problem as a multi-objective combinatorial optimization problem in an infinite time horizon, which is intractable to solve. To address this, a rolling-horizon-based optimization mechanism is designed to decompose the dynamic optimization problem into a series of static sub-problems. A genetic algorithm (GA)-based computation offloading and task scheduling algorithm is proposed for each static sub-problem. This algorithm encodes feasible solutions into two-layer chromosomes, and the optimal solution can be obtained through chromosome selection, crossover and mutation operations. The simulation results demonstrate that the proposed scheme can effectively reduce network costs in comparison to other reference schemes. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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23 pages, 1085 KiB

Open AccessArticle

A Novel Adaptive UE Aggregation-Based Transmission Scheme Design for a Hybrid Network with Multi-Connectivity

by Huamin Chen, Ruijie Fang, Tao Chen, Peng Wang, Zhuwei Wang, Shaofu Lin and Fan Li

Symmetry 2023, 15(9), 1766; https://doi.org/10.3390/sym15091766 - 15 Sep 2023

Cited by 7 | Viewed by 1304

Abstract

With the progress of the eras and the development of science and technology, the requirements of device-to-device (D2D) connectivity increased rapidly. As one important service in future systems, ultra-reliable low-latency communication (URLLC) has attracted attention in many applications, especially in the Internet of [...] Read more.

With the progress of the eras and the development of science and technology, the requirements of device-to-device (D2D) connectivity increased rapidly. As one important service in future systems, ultra-reliable low-latency communication (URLLC) has attracted attention in many applications, especially in the Internet of Things (IoT), smart cities, and other scenarios due to its characteristics of ultra-low latency and ultra-high reliability. However, in order to achieve the requirement of ultra-low latency, energy consumption often increases significantly. The optimization of energy consumption and the latency of the system in the communication field are often in conflict with each other. In this paper, in order to optimize the energy consumption and the latency jointly under different scenarios, and since the detailed requirements for latency and reliability are diverse in different services, we propose an adaptive UE aggregation (AUA)-based transmission scheme that explores the diversity gain of multiple simultaneous paths to reduce the overall latency of data transmission, wherein multiple paths correspond to multiple coordination nodes. Furthermore, it could provide the feasibility of link adaptation by adjusting the path number according to the real transmission environment. Then, unnecessary energy waste could be avoided. To evaluate the performance, the energy-delay product (EDP) is proposed for the latency and energy comparison. The provided simulation results align with the numerical data. Through the analysis, it can be proven that the proposed scheme can achieve a joint optimization of latency and energy consumption to meet different types of URLLC services. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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20 pages, 859 KiB

Open AccessArticle

Edge Intelligence-Assisted Asymmetrical Network Control and Video Decoding in the Industrial IoT with Speculative Parallelization

by Shuangye Yang, Zhiwei Zhang, Hui Xia, Yahui Li and Zheng Liu

Symmetry 2023, 15(8), 1516; https://doi.org/10.3390/sym15081516 - 1 Aug 2023

Viewed by 1502

Abstract

Industrial Internet of Things (IIoTs) has drawn significant attention in the industry. Among its rich applications, the field’s video surveillance deserves particular interest due to its advantage in better understanding network control. However, existing decoding methods are limited by the video coding order, [...] Read more.

Industrial Internet of Things (IIoTs) has drawn significant attention in the industry. Among its rich applications, the field’s video surveillance deserves particular interest due to its advantage in better understanding network control. However, existing decoding methods are limited by the video coding order, which cannot be decoded in parallel, resulting in low decoding efficiency and the inability to process the massive amount of video data in real time. In this work, a parallel decoding framework based on the speculative technique is proposed. In particular, the video is first speculatively decomposed into data blocks, and then a verification method is designed to ensure the correctness of the decomposition. After verification, the data blocks having passed the validation can be decoded concurrently in the parallel computing platform. Finally, the concurrent decoding results are concatenated in line with the original encoding order to form the output. Experiments show that compared with traditional serial decoding ones, the proposed method can improve the performance by 9 times on average in the parallel computing environment with NVIDIA Tegra 4 chips, thus significantly enhancing the real-time video data’s decoding efficiency with guaranteed accuracy. Furthermore, proposed and traditional serial methods obtain almost the same peak signal-to-noise ratio (PSNR) and mean square error (MSE) metrics at different bit rates and resolutions, showing that the introduction of the speculative technique does not degrade the decoding accuracy. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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20 pages, 374 KiB

Open AccessArticle

Outage Performance of Asymmetrical Cognitive Simultaneous Wireless Information and Power Transfer Networks Based on Non-Orthogonal Multiple Access with an Incremental Cooperation Relay and Hardware Impairments

by Shuai Liu, Man Cui, Anxin Zhao, Chen Zhang and Yuanlong Zhang

Symmetry 2023, 15(7), 1465; https://doi.org/10.3390/sym15071465 - 24 Jul 2023

Viewed by 1094

Abstract

This work aims to investigate an asymmetrical NOMA transmission network based on cognitive radio, where both the source and relay nodes of the secondary user are energy limited, and the energy could be harvested from the transmission signal of the power beacon. Considering [...] Read more.

This work aims to investigate an asymmetrical NOMA transmission network based on cognitive radio, where both the source and relay nodes of the secondary user are energy limited, and the energy could be harvested from the transmission signal of the power beacon. Considering some particular hardware impairments and asymmetry in the NOMA transmission, the closed-form expressions of outage probability for relay and destination nodes were derived using incremental relay methods. Furthermore, built on the expressions of the outage probability, the throughput performance was analyzed. Finally, the correctness of our theoretical analysis was verified using simulations. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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23 pages, 10877 KiB

Open AccessArticle

Generalization Investigation for Artificial Intelligence-Based Positioning in IIoT

by Qin Mu, Muqing Wu and Huixuan Zhou

Symmetry 2023, 15(5), 992; https://doi.org/10.3390/sym15050992 - 27 Apr 2023

Viewed by 1519

Abstract

In recent years, IIoT scenarios show increasing demand for high-precision positioning. Cellular-based positioning plays a very important role in this application area. The cellular-based positioning system can be categorized as an asymmetric processing system. In this system, multiple base stations transmit positioning reference [...] Read more.

In recent years, IIoT scenarios show increasing demand for high-precision positioning. Cellular-based positioning plays a very important role in this application area. The cellular-based positioning system can be categorized as an asymmetric processing system. In this system, multiple base stations transmit positioning reference signaling to one device and the device derives its coordinates based on the measurement of the positioning reference signal by using certain positioning algorithms. The classical positioning algorithms encounter great challenges in satisfying the stringent precision requirement. Meanwhile, artificial intelligence (AI)-based positioning solutions draw great attention due to their strong ability in improving positioning accuracy in IIoT scenarios. For AI-based algorithms, generalization capability is one important metric. It demonstrates the ability to adapt to different environments. However, there is little literature touching on the investigation of generalization capability. In this article, we will tackle this issue by considering typical features in IIoT scenarios including the clutter distribution, network synchronization error, and receiving timing error. The impact of these typical features on the generalization capability is firstly evaluated and then the feasibility of existing popular generalization improvement solutions, i.e., optimized training data set and fine-tuning are tested under different cases. At last, directions to further guarantee the generalization capability are presented. The results of this article provide useful experience for developing AI models for positioning in realistic IIoT scenarios. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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21 pages, 697 KiB

Open AccessArticle

Water Pumping and Refilling (WPR): A Resource Allocation Algorithm for Maximizing Acceptance Ratio in Asymmetrical Edge Computing Networks

by Li Dong, Wenji He and Yunjie Liu

Symmetry 2023, 15(5), 985; https://doi.org/10.3390/sym15050985 - 26 Apr 2023

Viewed by 1741

Abstract

Computation offloading has received a significant amount of attention in recent years, with many researchers proposing joint offloading decision and resource allocation schemes. However, although existing delay minimization schemes achieve minimum delay costs, they do so at the cost of losing possible further [...] Read more.

Computation offloading has received a significant amount of attention in recent years, with many researchers proposing joint offloading decision and resource allocation schemes. However, although existing delay minimization schemes achieve minimum delay costs, they do so at the cost of losing possible further maximization of the number of serviced requests. Furthermore, the asymmetry between uplink and downlink poses challenges to resource allocation in edge computing. This paper addresses this issue by formulating the joint computation offloading and edge resource allocation problem as a mixed-integer nonlinear programming (MINLP) problem in an edge-enabled asymmetrical network. Leveraging the margin between a delay-minimum scheme and a near-deadline scheme, a water pumping and refilling (WPR) algorithm is proposed to maximize the number of accepted requests. The WPR algorithm can function both as a supplementary algorithm to a given offloading scheme and as a standalone algorithm to obtain a resource allocation scheme following a customizable refilling policy. The simulation results demonstrated that the proposed algorithm outperforms delay-minimum schemes in achieving a high acceptance ratio. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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11 pages, 1391 KiB

Open AccessArticle

Asymmetry Opinion Evolution Model Based on Dynamic Network Structure

by An Lu and Yaguang Guo

Symmetry 2022, 14(12), 2499; https://doi.org/10.3390/sym14122499 - 25 Nov 2022

Cited by 1 | Viewed by 1507

Abstract

On social media platforms, users can not only unfollow others whose opinion excessively opposes their own, but they can also add new connections. To better reflect the evolution of opinions on social media, this paper proposes an opinion asymmetry evolution model based on [...] Read more.

On social media platforms, users can not only unfollow others whose opinion excessively opposes their own, but they can also add new connections. To better reflect the evolution of opinions on social media, this paper proposes an opinion asymmetry evolution model based on a dynamic network structure, where the trusts between two individuals are not mutual and dynamic. First, the paper analyzes the general properties of the model. We prove that group opinion can converge to a steady state even if the connection is unidirectional. Second, we compare the evolution process of static and dynamic network structures. Computer simulation results show that a higher probability of new connections leads to less aggregation of group opinion, higher information entropy, lower HHI, and lower degrees of polarization. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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15 pages, 1092 KiB

Open AccessArticle

A DRL-Driven Intelligent Optimization Strategy for Resource Allocation in Cloud-Edge-End Cooperation Environments

by Chao Fang, Tianyi Zhang, Jingjing Huang, Hang Xu, Zhaoming Hu, Yihui Yang, Zhuwei Wang, Zequan Zhou and Xiling Luo

Symmetry 2022, 14(10), 2120; https://doi.org/10.3390/sym14102120 - 12 Oct 2022

Cited by 16 | Viewed by 2734

Abstract

Complex dynamic services and heterogeneous network environments make the asymmetrical control a curial issue to handle on the Internet. With the advent of the Internet of Things (IoT) and the fifth generation (5G), the emerging network applications lead to the explosive growth of [...] Read more.

Complex dynamic services and heterogeneous network environments make the asymmetrical control a curial issue to handle on the Internet. With the advent of the Internet of Things (IoT) and the fifth generation (5G), the emerging network applications lead to the explosive growth of mobile traffic while bringing forward more challenging service requirements to future radio access networks. Therefore, how to effectively allocate limited heterogeneous network resources to improve content delivery for massive application services to ensure network quality of service (QoS) becomes particularly urgent in heterogeneous network environments. To cope with the explosive mobile traffic caused by emerging Internet services, this paper designs an intelligent optimization strategy based on deep reinforcement learning (DRL) for resource allocation in heterogeneous cloud-edge-end collaboration environments. Meanwhile, the asymmetrical control problem caused by complex dynamic services and heterogeneous network environments is discussed and overcome by distributed cooperation among cloud-edge-end nodes in the system. Specifically, the multi-layer heterogeneous resource allocation problem is formulated as a maximal traffic offloading model, where content caching and request aggregation mechanisms are utilized. A novel DRL policy is proposed to improve content distribution by making cache replacement and task scheduling for arriving content requests in accordance with the information about users’ history requests, in-network cache capacity, available link bandwidth and topology structure. The performance of our proposed solution and its similar counterparts are analyzed in different network conditions. Full article

(This article belongs to the Special Issue Asymmetrical Network Control for Complex Dynamic Services)

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