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Improvement of Apriori Algorithm Using Parallelization Technique on Multi-CPU and GPU Topology 在多 CPU 和 GPU 拓扑上使用并行化技术改进 Apriori 算法
Pub Date : 2024-05-31 DOI: 10.1155/2024/7716976
Hooman Bavarsad Salehpour, Hamid Haj Seyyed Javadi, Parvaneh Asghari, Mohammad Ebrahim Shiri Ahmad Abadi
In the domain of data mining, the extraction of frequent patterns from expansive datasets remains a daunting task, compounded by the intricacies of temporal and spatial dimensions. While the Apriori algorithm is seminal in this area, its constraints are accentuated when navigating larger datasets. In response, we introduce an avant-garde solution that leverages parallel network topologies and GPUs. At the heart of our method are two salient features: (1) the use of parallel processing to expedite the realization of optimal results and (2) the integration of the cat and mouse-based optimizer (CMBO) algorithm, an astute algorithm mirroring the instinctual dynamics between predatory cats and evasive mice. This optimizer is structured around a biphasic model: an initial aggressive pursuit by the cats and a subsequent calculated evasion by the mice. This structure is enriched by classifying agents using their objective function scores. Complementing this, our architectural blueprint seamlessly amalgamates dual Nvidia graphics cards in a parallel configuration, establishing a marked ascendancy over conventional CPUs. In amalgamation, our approach not only rectifies the inherent shortfalls of the Apriori algorithm but also accentuates the extraction of association rules, pinpointing frequent patterns with enhanced precision. A comprehensive evaluation across a spectrum of network topologies explains their respective merits and demerits. Set against the benchmark of the Apriori algorithm, our method conspicuously outperforms in terms of speed and effectiveness, heralding a significant stride forward in data mining research.
在数据挖掘领域,从庞大的数据集中提取频繁模式仍然是一项艰巨的任务,而错综复杂的时间和空间维度又使这项任务变得更加复杂。虽然 Apriori 算法在这一领域具有开创性意义,但在浏览大型数据集时,该算法的局限性更加突出。为此,我们推出了一种利用并行网络拓扑结构和 GPU 的前卫解决方案。我们方法的核心有两个显著特点:(1)利用并行处理加速实现最优结果;(2)整合基于猫和老鼠的优化器(CMBO)算法,这是一种反映捕食性猫和逃避性老鼠之间本能动态的精明算法。该优化器以双相模型为基础:猫最初的攻击性追逐和老鼠随后的计算躲避。通过使用目标函数得分对代理进行分类,这种结构得到了丰富。作为补充,我们的架构蓝图在并行配置中无缝集成了双 Nvidia 显卡,从而确立了对传统 CPU 的明显优势。在合并过程中,我们的方法不仅纠正了 Apriori 算法的固有缺陷,还突出了关联规则的提取,以更高的精度精确定位频繁出现的模式。对各种网络拓扑结构的综合评估说明了它们各自的优缺点。以 Apriori 算法为基准,我们的方法在速度和有效性方面明显优于 Apriori 算法,预示着数据挖掘研究向前迈出了一大步。
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引用次数: 0
Hybrid Agent-Based Load-Balancing Approach Used in an IaaS Platform IaaS 平台中使用的基于代理的混合负载均衡方法
Pub Date : 2024-04-26 DOI: 10.1155/2024/2357142
Shoney Sebastian, Iyyappan. MIn, Sultan Ahmad, Mohammad Maqbool Waris, Hikmat A. M. Abdeljaber, Jabeen Nazeer
Cloud computing has received a resounding welcome. It was created following methodical and thorough study in web services, distributed computing, utility computing, and virtualization, and it offers several benefits, including lower costs, less space required, and easier management. These advantages bring in a significant number of new users to the cloud platform every day. In addition, because cloud computing is an Internet-based computing paradigm, it must deal with the issue of overwhelming demands through effective load-balancing. A very small number of studies only focus on load-balancing problems in cloud computing platforms, while the majority of load-balancing research is accessible in many domains, including parallel, distributed, and grid computing. Infrastructure as a Service (IaaS), Software as a Service, and Platform as a Service are the three basic categories under which cloud computing falls. For these models, there are notable differences in the load-balancing techniques used. This work compared the outcome with the current method and presented a hybrid agent-based load-balancing approach for the IaaS platform.
云计算受到了热烈欢迎。云计算是在对网络服务、分布式计算、公用事业计算和虚拟化进行有条不紊的深入研究后产生的,它具有成本更低、所需空间更小、更易于管理等多种优势。这些优势每天都为云平台带来大量新用户。此外,由于云计算是一种基于互联网的计算模式,它必须通过有效的负载平衡来解决需求过大的问题。只有极少数研究关注云计算平台中的负载平衡问题,而大多数负载平衡研究都可以在并行计算、分布式计算和网格计算等许多领域中获得。基础设施即服务(IaaS)、软件即服务和平台即服务是云计算的三个基本类别。对于这些模式,所使用的负载平衡技术存在明显差异。这项工作将结果与当前方法进行了比较,并为 IaaS 平台提出了一种基于代理的混合负载平衡方法。
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引用次数: 0
Hierarchical Cross Traffic Scheduling Based on Time-Aware Shapers for Mobile Time-Sensitive Fronthaul Network 基于时间感知整形器的分层交叉流量调度,适用于移动时敏前端网络
Pub Date : 2024-04-15 DOI: 10.1155/2024/8882006
Chang Liu, Yue Hong, Jin Wang, Chang Liu Sr., Li Tian, Jiangpei Xu
To solve the problem of jitter and low network throughput caused by the impact of background flows on IQ traffic in mobile fronthaul network, this paper proposed a new scheduling model for background flows, named hierarchical crossover traffic scheduling mechanism based on time-aware shaper (HC-TAS) by improving the traditional counterpart. Then, in this new model, we designed an inbound scheduling algorithm based on frame length matching and an outbound scheduling algorithm based on queue status, making sure that smaller data frames will not be blocked by large data frames. This greatly improves the utilization of timeslots in the scheduling process and reduces the jitter impact of background flows. To verify its performance, we conducted experiments in a simulated fronthaul network conforming to IEEE 802.1CM. The experimental results show that, under the condition that the jitter is guaranteed to be zero, compared with two mainstream scheduling schemes, Comb-FITting and TAS + Preemption, our proposed scheme can achieve lower maximum end-to-end delay and higher link utilization. The proposed HC-TAS meets the requirements of low jitter and high bandwidth utilization in 5G fronthaul network, and the research results provide a technical basis for the application and development of general time-sensitive networks as well.
为了解决移动前传网络中背景流对 IQ 流量的影响所导致的抖动和网络吞吐量低的问题,本文通过改进传统的背景流调度模型,提出了一种新的背景流调度模型,命名为基于时间感知整形器的分层交叉流量调度机制(HC-TAS)。在这个新模型中,我们设计了基于帧长匹配的入站调度算法和基于队列状态的出站调度算法,确保较小的数据帧不会被大数据帧阻塞。这大大提高了调度过程中时隙的利用率,并减少了背景流的抖动影响。为了验证其性能,我们在符合 IEEE 802.1CM 标准的模拟前线网络中进行了实验。实验结果表明,在保证抖动为零的条件下,与 Comb-FITting 和 TAS + Preemption 这两种主流调度方案相比,我们提出的方案能实现更低的最大端到端延迟和更高的链路利用率。所提出的 HC-TAS 方案满足了 5G 前传网络低抖动和高带宽利用率的要求,其研究成果也为一般时敏网络的应用和发展提供了技术基础。
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引用次数: 0
On the Performance of MMSE Channel Estimation in Massive MIMO Systems over Spatially Correlated Rician Fading Channels 论大规模多输入多输出(Massive MIMO)系统在空间相关的里杉衰减信道上的 MMSE 信道估计性能
Pub Date : 2024-04-12 DOI: 10.1155/2024/5445725
Jorge F. Arellano, Carlos Daniel Altamirano, Henry Ramiro Carvajal Mora, Nathaly Verónica Orozco Garzón, Fernando Darío Almeida García
Massive multiple-input-multiple-output (M-MIMO) offers remarkable advantages in terms of spectral, energy, and hardware efficiency for future wireless systems. However, its performance relies on the accuracy of channel state information (CSI) available at the transceivers. This makes channel estimation pivotal in the context of M-MIMO systems. Prior research has focused on evaluating channel estimation methods under the assumption of spatially uncorrelated fading channel models. In this study, we evaluate the performance of the minimum-mean-square-error (MMSE) estimator in terms of the normalized mean square error (NMSE) in the uplink of M-MIMO systems over spatially correlated Rician fading. The NMSE allows for easy comparison of different M-MIMO configurations, serving as a relative performance indicator. Besides, it is an advantageous metric due to its normalization, scale invariance, and consistent performance indication across diverse scenarios. In the system model, we assume imperfections in channel estimation and that the random angles in the correlation model follow a Gaussian distribution. For this scenario, we derive an accurate closed-form expression for calculating the NMSE, which is validated via Monte-Carlo simulations. Our numerical results reveal that as the Rician -factor decreases, approaching Rayleigh fading conditions, the NMSE improves. Additionally, spatial correlation and a reduction in the antenna array interelement spacing lead to a reduction in NMSE, further enhancing the overall system performance.
大规模多输入多输出(M-MIMO)在频谱、能源和硬件效率方面为未来的无线系统提供了显著优势。然而,其性能取决于收发器上可用信道状态信息(CSI)的准确性。因此,信道估计在 M-MIMO 系统中至关重要。之前的研究主要集中在空间不相关衰落信道模型假设下的信道估计方法评估。在本研究中,我们用归一化均方误差(NMSE)评估了 M-MIMO 系统上行链路在空间相关里氏衰减情况下最小均方误差(MMSE)估计器的性能。归一化均方误差便于比较不同的 M-MIMO 配置,可作为相对性能指标。此外,NMSE 还具有归一化、规模不变性以及在不同场景下性能指示一致等优点。在系统模型中,我们假设信道估计不完善,相关模型中的随机角度遵循高斯分布。在这种情况下,我们得出了计算 NMSE 的精确闭式表达式,并通过蒙特卡罗模拟进行了验证。我们的数值结果表明,随着里氏因子的减小,接近瑞利衰落条件时,NMSE 将得到改善。此外,空间相关性和天线阵列单元间距的减小也会导致 NMSE 的减小,从而进一步提高系统的整体性能。
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引用次数: 0
Analysis of Filtered Multicarrier Modulation Techniques Using Different Windows for 5G and Beyond Wireless Systems 使用不同窗口的滤波多载波调制技术在 5G 及以后无线系统中的应用分析
Pub Date : 2024-03-26 DOI: 10.1155/2024/9428292
Sourav Debnath, Samin Ahmed, S. M. Shamsul Alam
In contemporary wireless communication systems, multicarrier modulation schemes have become widely adopted over single-carrier techniques due to their improved capacity to address challenges posed by multipath fading channels, leading to enhanced spectral efficiency. Orthogonal frequency division multiplexing (OFDM), a prevalent multicarrier scheme in 4G, is favored for its ease of implementation, interference resilience, and high data rate provision. But it falls short of meeting the requirements for 5G and beyond due to limitations such as out-of-band (OOB) emissions and cyclic prefixes. This paper introduces the filter bank multicarrier (FBMC) and universal filtered multicarrier (UFMC) with quadrature amplitude modulation (QAM) and phase shift keying (PSK) waveforms through Additive White Gaussian Noise channel (AWGN), Rayleigh fading channel and Rician channel. The objective of this paper is to enhance the performance of UFMC with reduced complexity through the new filtering approach for achieving optimal outcomes. The proposed scheme, incorporating Tukey filtering technique, demonstrates superior performance in reducing peak-to-average power ratio (PAPR) and improving bit error ratio (BER) compared to the original UFMC signal without necessitating additional power increments. Specifically, the UFMC system with Tukey filtering achieves a notable net gain of 5 dB. Simulation results demonstrate that utilizing various filter types in FBMC and UFMC systems, combined with QAM modulation, significantly reduces OOB emissions compared to conventional systems. In aspect to BER, Tukey window showed almost 10−6 at 15 dB SNR in UFMC which is better than FBMC.
在当代无线通信系统中,多载波调制方案由于能更好地应对多径衰落信道带来的挑战,从而提高频谱效率,已被广泛采用,而不是单载波技术。正交频分复用(OFDM)是 4G 领域中一种流行的多载波方案,因其易于实施、抗干扰能力强和数据传输速率高而备受青睐。但由于带外(OOB)发射和循环前缀等限制,它无法满足 5G 及更高的要求。本文介绍了滤波器组多载波(FBMC)和通用滤波多载波(UFMC),它们采用正交振幅调制(QAM)和相移键控(PSK)波形,通过加性白高斯噪声信道(AWGN)、瑞利衰落信道和里阡信道。本文的目的是通过新的滤波方法提高 UFMC 的性能,同时降低其复杂性,以获得最佳结果。与原始 UFMC 信号相比,包含 Tukey 滤波技术的拟议方案在降低峰均功率比 (PAPR) 和改善误码率 (BER) 方面表现出卓越的性能,而无需增加额外的功率增量。具体而言,采用 Tukey 滤波技术的 UFMC 系统实现了 5 dB 的显著净增益。仿真结果表明,与传统系统相比,在 FBMC 和 UFMC 系统中使用各种类型的滤波器并结合 QAM 调制,可显著减少 OOB 发射。在误码率方面,UFMC 在 15 dB SNR 时,Tukey 窗口的误码率接近 10-6,优于 FBMC。
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引用次数: 0
An Elliptic Curve Menezes–Qu–Vanston-Based Authentication and Encryption Protocol for IoT 基于椭圆曲线梅内塞斯-库-万斯顿的物联网身份验证和加密协议
Pub Date : 2024-03-22 DOI: 10.1155/2024/5998163
Susovan Chanda, Ashish Kr. Luhach, J. Sharmila Anand Francis, Indranil Sengupta, Diptendu Sinha Roy
The exponential growth of the Internet of Things (IoT) has led to a surge in data generation, critical for business decisions. Ensuring data authenticity and integrity over unsecured channels is vital, especially due to potential catastrophic consequences of tampered data. However, IoT’s resource constraints and heterogeneous ecosystem present unique security challenges. Traditional public key infrastructure offers strong security but is resource intensive, while existing cloud-based solutions lack comprehensive security and rise to latency and unwanted wastage of energy. In this paper, we propose a universal authentication scheme using edge computing, incorporating fully hashed Elliptic Curve Menezes–Qu–Vanstone (ECMQV) and PUF. This approach provides a scalable and reliable solution. It also provides security against active attacks, addressing man-in-the-middle and impersonation threats. Experimental validation on a Zybo board confirms its effectiveness, offering a robust security solution for the IoT landscape.
物联网(IoT)的指数级增长导致数据生成量激增,这对业务决策至关重要。在不安全的渠道上确保数据的真实性和完整性至关重要,特别是由于篡改数据可能带来灾难性后果。然而,物联网的资源限制和异构生态系统带来了独特的安全挑战。传统的公钥基础设施提供了强大的安全性,但需要耗费大量资源,而现有的基于云的解决方案则缺乏全面的安全性,并会导致延迟和不必要的能源浪费。在本文中,我们提出了一种使用边缘计算的通用身份验证方案,将完全散列的椭圆曲线梅内塞斯-奎-范斯通(ECMQV)和 PUF 结合在一起。这种方法提供了一种可扩展的可靠解决方案。它还提供了针对主动攻击的安全性,解决了中间人和冒名顶替的威胁。在 Zybo 电路板上进行的实验验证证实了它的有效性,为物联网领域提供了强大的安全解决方案。
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引用次数: 0
An Intelligent Energy-Efficient Data Routing Scheme for Wireless Sensor Networks Utilizing Mobile Sink 利用移动 Sink 的无线传感器网络智能节能数据路由方案
Pub Date : 2024-03-18 DOI: 10.1155/2024/7384537
Hassan Al-Mahdi, Mohamed Elshrkawey, Shymaa Saad, Safa Abdelaziz
Data collection and energy consumption are critical concerns in Wireless sensor networks (WSNs). To address these issues, both clustering and routing algorithms are utilized. Therefore, this paper proposes an intelligent energy-efficient data routing scheme for WSNs utilizing a mobile sink (MS) to save energy and prolong network lifetime. The proposed scheme operates in two major modes: configure and operational modes. During the configure mode, a novel clustering mechanism is applied once, and a prescheduling cluster head (CH) selection is introduced to ensure uniform energy expenditure among sensor nodes (SNs). The scheduling technique selects successive CHs for each cluster throughout the WSNs’ lifetime rounds, managed at the base station (BS) to minimize SN energy consumption. In the operational mode, two main objectives are achieved: sensing and gathering data by each CH with minimal message overhead, and establishing an optimal path for the MS using the genetic algorithm. Finally, the MS uploads the gathered data to the BS. Extensive simulations are conducted to verify the efficiency of the proposed scheme in terms of stability period, network lifetime, average energy consumption, data transmission latency, message overhead, and throughput. The results demonstrate that the proposed scheme outperforms the most recent state-of-the-art methods significantly. The results are substantiated through statistical validation via hypothesis testing utilizing ANOVA, as well as post hoc analysis.
数据收集和能源消耗是无线传感器网络(WSN)的关键问题。为了解决这些问题,需要使用聚类和路由算法。因此,本文提出了一种利用移动汇(MS)的 WSN 智能节能数据路由方案,以节约能源并延长网络寿命。所提方案有两种主要运行模式:配置模式和运行模式。在配置模式下,一次应用新颖的聚类机制,并引入预调度簇头(CH)选择,以确保传感器节点(SN)之间能量消耗均匀。调度技术在 WSN 的整个生命周期中为每个簇选择连续的 CH,由基站(BS)管理,以最大限度地减少 SN 的能量消耗。在运行模式下,要实现两个主要目标:每个 CH 以最小的信息开销感知和收集数据,并使用遗传算法为 MS 建立最佳路径。最后,MS 将收集到的数据上传到 BS。我们进行了大量仿真,从稳定期、网络寿命、平均能耗、数据传输延迟、信息开销和吞吐量等方面验证了所提方案的效率。结果表明,所提出的方案明显优于最新的先进方法。利用方差分析进行假设检验和事后分析,通过统计验证证实了上述结果。
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引用次数: 0
A Novel Hybrid Feature Selection with Cascaded LSTM: Enhancing Security in IoT Networks 使用级联 LSTM 的新型混合特征选择:增强物联网网络的安全性
Pub Date : 2024-03-13 DOI: 10.1155/2024/5522431
Karthic Sundaram, Yuvaraj Natarajan, Anitha Perumalsamy, Ahmed Abdi Yusuf Ali
The rapid growth of the Internet of Things (IoT) has created a situation where a huge amount of sensitive data is constantly being created and sent through many devices, making data security a top priority. In the complex network of IoT, detecting intrusions becomes a key part of strengthening security. Since IoT environments can be easily affected by a wide range of cyber threats, intrusion detection systems (IDS) are crucial for quickly finding and dealing with potential intrusions as they happen. IDS datasets can have a wide range of features, from just a few to several hundreds or even thousands. Managing such large datasets is a big challenge, requiring a lot of computer power and leading to long processing times. To build an efficient IDS, this article introduces a combined feature selection strategy using recursive feature elimination and information gain. Then, a cascaded long–short-term memory is used to improve attack classifications. This method achieved an accuracy of 98.96% and 99.30% on the NSL-KDD and UNSW-NB15 datasets, respectively, for performing binary classification. This research provides a practical strategy for improving the effectiveness and accuracy of intrusion detection in IoT networks.
随着物联网(IoT)的快速发展,大量敏感数据不断产生并通过许多设备发送,数据安全成为重中之重。在复杂的物联网网络中,检测入侵成为加强安全的关键部分。由于物联网环境很容易受到各种网络威胁的影响,入侵检测系统(IDS)对于快速发现和处理潜在入侵至关重要。IDS 数据集的特征范围很广,从几个到几百个甚至上千个不等。管理如此庞大的数据集是一项巨大的挑战,需要大量的计算机能力,并导致处理时间过长。为了建立高效的 IDS,本文介绍了一种使用递归特征消除和信息增益的组合特征选择策略。然后,使用级联长短期存储器来改进攻击分类。该方法在 NSL-KDD 和 UNSW-NB15 数据集上进行二元分类的准确率分别达到了 98.96% 和 99.30%。这项研究为提高物联网网络入侵检测的有效性和准确性提供了一种实用策略。
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引用次数: 0
Resource Scheduling in URLLC and eMBB Coexistence Based on Dynamic Selection Numerology 基于动态选择数值法的 URLLC 和 eMBB 共存中的资源调度
Pub Date : 2024-02-28 DOI: 10.1155/2024/9480388
Lei Wang, Sijie Tao, Lindong Zhao, Dengyou Zhou, Zhe Liu, Yanbing Sun
This paper focuses on the resource allocation problem of multiplexing two different service scenarios, enhanced mobile broadband (eMBB) and ultrareliable low latency (URLLC) in 5G New Radio, based on dynamic numerology structure, mini-time slot scheduling, and puncturing to achieve optimal resource allocation. To obtain the optimal channel resource allocation under URLLC user constraints, this paper establishes a relevant channel model divided into two convex optimization problems: (a) eMBB resource allocation and (b) URLLC scheduling. We also determine the numerology values at the beginning of each time slot with the help of deep reinforcement learning to achieve flexible resource scheduling. The proposed algorithm is verified in simulation software, and the simulation results show that the dynamic selection of numerologies proposed in this paper can better improve the data transmission rate of eMBB users and reduce the latency of URLLC services compared with the fixed numerology scheme for the same URLLC packet arrival, while the reasonable resource allocation ensures the reliability of URLLC and eMBB communication.
本文基于动态数字结构、小时隙调度和穿刺技术,重点研究了5G新无线电中增强型移动宽带(eMBB)和超可靠低时延(URLLC)两种不同业务场景复用的资源分配问题,以实现最优资源分配。为了获得 URLLC 用户约束条件下的最优信道资源分配,本文建立了一个相关的信道模型,将其分为两个凸优化问题:(a)eMBB 资源分配和(b)URLLC 调度。我们还借助深度强化学习来确定每个时隙开始时的数值,从而实现灵活的资源调度。本文提出的算法在仿真软件中进行了验证,仿真结果表明,在相同的 URLLC 数据包到达率下,本文提出的动态数值选择方案与固定数值方案相比,能更好地提高 eMBB 用户的数据传输速率,降低 URLLC 服务的延迟,同时合理的资源分配保证了 URLLC 和 eMBB 通信的可靠性。
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引用次数: 0
Reliability-Constrained Task Scheduling for DAG Applications in Mobile Edge Computing 移动边缘计算中 DAG 应用的可靠性受限任务调度
Pub Date : 2024-01-29 DOI: 10.1155/2024/6980514
Liangbin Zhu, Ying Shang, Jinglei Li, Yiming Jia, Qinghai Yang
The development of the internet of things (IoT) and 6G has given rise to numerous computation-intensive and latency-sensitive applications, which can be represented as directed acyclic graphs (DAGs). However, achieving these applications poses a huge challenge for user equipment (UE) that are constrained in computational power and battery capacity. In this paper, considering different requirements in various task scenarios, we aim to optimize the execution latency and energy consumption of the entire mobile edge computing (MEC) system. The system consists of single UE and multiple heterogeneous MEC servers to improve the execution efficiency of a DAG application. In addition, the execution reliability of a DAG application is viewed as a constraint. Based on the strong search capability and Pareto optimality theory of the cuckoo search (CS) algorithm and our previously proposed improved multiobjective cuckoo search (IMOCS) algorithm, we improve the initialization process and the update strategy of the external archive, and propose a reliability-constrained multiobjective cuckoo search (RCMOCS) algorithm. According to the simulation results, our proposed RCMOCS algorithm is able to obtain better Pareto frontiers and achieve satisfactory performance while ensuring execution reliability.
物联网(IoT)和 6G 的发展催生了大量计算密集型和对延迟敏感的应用,这些应用可表示为有向无环图(DAG)。然而,对于计算能力和电池容量有限的用户设备(UE)来说,实现这些应用是一个巨大的挑战。在本文中,考虑到各种任务场景中的不同要求,我们旨在优化整个移动边缘计算(MEC)系统的执行延迟和能耗。该系统由单个 UE 和多个异构 MEC 服务器组成,旨在提高 DAG 应用程序的执行效率。此外,DAG 应用程序的执行可靠性也是一个约束条件。基于布谷鸟搜索(CS)算法的强搜索能力和帕累托最优理论以及我们之前提出的改进型多目标布谷鸟搜索(IMOCS)算法,我们改进了外部存档的初始化过程和更新策略,并提出了一种可靠性约束多目标布谷鸟搜索(RCMOCS)算法。根据仿真结果,我们提出的 RCMOCS 算法能够获得更好的帕累托前沿,并在确保执行可靠性的同时获得令人满意的性能。
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引用次数: 0
期刊
Wireless Communications and Mobile Computing
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