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Combined optimization strategy for IoT resource allocation with workload prediction

Sustainable Computing: Informatics and Systems 2025年 47卷

作者： B. Sasikala K. Kalaiselvi V. Senthil Murugan Research Scholar Department of Networking and Communication SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu 603203 India Associate Professor Department of Networking and Communication Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu 603203 India Professor Department of Computer Science and Engineering School of Engineering and Technology CMR University Bengaluru Karnataka India

A significant limitation in IoT technology is the challenge of handling the diverse and dynamic nature of IoT workloads, which complicates accurate workload prediction and efficient resource allocation. IoT devices generate vast amounts of heterogeneous data with varying speeds, volumes, and varieties, making traditional methods inadequate for managing this variability and leading to inefficient resource management, suboptimal performance, and increased operational costs. To address these issues, this research proposes a novel hybrid optimization algorithm known as the Lyrebird-Adapted Kookaburra Optimization Algorithm-Improved Analytic Hierarchy Process (LAKO-IAHP) for work load prediction and resource allocation. This approach includes two main phases: the Improved Analytic Hierarchy Process (IAHP) for workload prediction and the LAKO algorithm for resource allocation. The IAHP phase enhances conventional Analytic Hierarchy Process (AHP) techniques by incorporating the Improved k-means clustering (IKMC) process and Euclidean distance calculations to improve the accuracy of workload predictions by considering specific Load Balancing (LB) parameters such as server load and response time. Following this, the LAKO algorithm- an advanced hybrid method combining Kookaburra Optimization Algorithm (KOA) and Lyrebird Optimization Algorithm (LOA)- performs the resource allocation phase, that considers the Quality of Service (QoS) parameters including degree of imbalance, execution time, reliability, and resource utilization. The effectiveness of the LAKO-IAHP approach is demonstrated through various performance metrics and comparisons with existing methods, proving its capability to enhance resource management and maintain high performance and reliability in IoT environments.

关键词： Resource allocation

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Multiple-priority region-of-interest H.264 video compression using constraint variable bitrate control for video surveillance

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Optical engineering 2009年第4期48卷

作者： Huang, Chung-Ming Lin, Chung-Wei National Cheng Kung University Department of Computer Science and Information Engineering Laboratory of Multimedia Mobile Networking Tainan Taiwan

With the growth of digital video surveillance markets and requirements of high-quality surveillance data, an efficient video compression technique that is suitable for surveillance applications and is compatible with emerging coding standards (e.g., H.264) is required urgently. We propose multiple-priority region-of-interest H.264 video compression using constraint variable bitrate control for video surveillance. The proposed Multiple Moving region-of-interest (RoI) macroblock decision and an RoI-based Constraint Variable Bitrate Control, called MM-RoI-CVBC, are able to determine each macroblock (MB) coding priority and increase SNR of automatically or manually detected RoI. In comparison to H.264 JM fixed-quantization parameter coding, H.264 JM constant bitrate control, and other RoI coding algorithms, the proposed MM-RoI-CVBC method can obviously enhance the quality of RoI with less coding complexity in subject to target bits. © 2009 Society of Photo-Optical Instrumentation Engineers.

关键词： Image compression

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Age of Semantics in Cooperative Communications: To Expedite Simulation Towards Real via Offline Reinforcement Learning

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IEEE Transactions on Network Science and engineering 2025年

作者： Chen, Xianfu Zhao, Zhifeng Mao, Shiwen Wu, Celimuge Zhang, Honggang Bennis, Mehdi Shenzhen CyberAray Network Technology Co. Ltd. Shenzhen518100 China Zhejiang University Zhejiang Lab Hangzhou310027 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Auburn University Department of Electrical and Computer Engineering AuburnAL36849 United States The University of Electro-Communications Meta-Networking Research Center Chofu-shi Tokyo182-8585 Japan The University of Electro-Communications Graduate School of Informatics and Engineering Chofu-shi Tokyo182-8585 Japan City University of Macau Faculty of Data Science Taipa999078 China University of Oulu Centre for Wireless Communications Oulu90570 Finland

The age of information metric fails to correctly describe the intrinsic semantics of a status update. In an intelligent reflecting surface-aided cooperative relay communication system, we propose the age of semantics (AoS) for measuring the semantics freshness of status updates. Specifically, we focus on status updates from a source node (SN) to the destination, which is formulated as a Markov decision process. The objective of the SN is to maximize the expected satisfaction of AoS and energy consumption under the maximum transmit power constraint. To seek the optimal control policy, we first derive an online deep actor-critic (DAC) learning scheme under the on-policy temporal difference learning framework. However, implementing the online DAC in practice poses key challenge in infinitely repeated interactions between the SN and the system, which can be dangerous particularly during exploration. We then put forward a novel offline DAC scheme, which estimates the optimal control policy from a previously collected dataset without any further interactions with the system. Numerical experiments verify the theoretical results and show that our offline DAC scheme significantly outperforms the online DAC scheme and the most representative baselines in terms of mean utility, demonstrating strong robustness to dataset quality. © 2013 IEEE.

关键词： Deep reinforcement learning

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Semantic-aided Parallel Image Transmission Compatible with Practical System

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IEEE Transactions on Wireless Communications 2025年

作者： Xu, Mingkai Wu, Yongpeng Shi, Yuxuan Xia, Xiang-Gen Debbah, Mérouane Zhang, Wenjun Zhang, Ping Shanghai Jiao Tong University Department of Electronic Engineering Shanghai 200240 China Shanghai Jiao Tong University School of Cyber and Engineering Shanghai 200240 China University of Delaware Department of Electrical and Computer Engineering Newark 19716 DE United States Khalifa University of Science and Technology KU6G Research Center PO Box Abu Dhabi 127788 United Arab Emirates University Paris-Saclay CentraleSupelec Gif-sur-Yvette 91192 France Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing 100876 China

In this paper, we propose a novel semantic-aided image communication framework for supporting the compatibility with practical separation-based coding architectures. Particularly, the deep learning (DL)-based joint source-channel coding (JSCC) is integrated into the classical separate source-channel coding (SSCC) to transmit the images via the combination of semantic stream and image stream from DL networks and SSCC respectively, which we name as parallel-stream transmission. The positive coding gain stems from the sophisticated design of the JSCC encoder, which leverages the residual information neglected by the SSCC to enhance the learnable image features. Furthermore, a conditional rate adaptation mechanism is introduced to adjust the transmission rate of semantic stream according to residual, rendering the framework more flexible and efficient to bandwidth allocation. We also design a dynamic stream aggregation strategy at the receiver, which provides the composite framework with more robustness to signal-to-noise ratio (SNR) fluctuations in wireless systems compared to a single conventional codec. Finally, the proposed framework is verified to surpass the performance of both traditional and DL-based competitors in a large range of scenarios and meanwhile, maintains lightweight in terms of the transmission and computational complexity of semantic stream, which exhibits the potential to be applied in real systems. © 2002-2012 IEEE.

关键词： Joint source-channel coding Rate adaptation Semantic communication Wireless transmission

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3-Approximation algorithm for joint routing and link scheduling in wireless relay networks

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IEEE Transactions on Wireless Communications 2009年第2期8卷 856-861页

作者： Hong, Chi-Yao Pang, Ai-Chun Department of Computer Science and Information Engineering National Taiwan University Taipei 10617 Taiwan Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering National Taiwan University Taipei 10617 Taiwan

In emerging wireless relay networks (WRNs) such as IEEE 802.16j, efficient resource allocation is becoming a substantial issue for throughput optimization. In this paper, we propose an algorithm for joint routing and link scheduling in WRNs. The developed theoretical analysis indicates that the performance of the proposed algorithm is within a factor of three of that of any optimal algorithm in the worst case. Through simulation experiments, the numerical results show that our algorithm outperforms the previously proposed routing and link-scheduling algorithms. Furthermore, the proposed algorithm can effectively achieve near-optimal performance, and provide much better throughput than the theoretical worst-case bound in the average case. © 2006 IEEE.

关键词： Approximation algorithms

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Cooperative Vehicular Content Distribution in Edge Computing Assisted 5G-VANET

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China Communications 2018年第7期15卷 1-17页

作者： Guiyang Luo Quan Yuan Haibo Zhou Nan Cheng Zhihan Liu Fangchun Yang Xuemin (Sherman) Shen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications School of Electronic Science and Engineering Nanjing University Department of Electrical and Computer Engineering University of Waterloo

By leveraging the 5G enabled vehicular ad hoc network(5G-VANET), it is widely recognized that connected vehicles have the potentials to improve road safety, transportation intelligence and provide in-vehicle entertainment experience. However, many enabling applications in 5G-VANET rely on the efficient content sharing among mobile vehicles, which is a very challenging issue due to the extremely large data volume, rapid topology change, and unbalanced traffic. In this paper, we investigate content prefetching and distribution in 5G-VANET. We first introduce an edge computing based hierarchical architecture for efficient distribution of large-volume vehicular data. We then propose a multi-place multi-factor prefetching scheme to meet the rapid topology change and unbalanced traffic. The content requests of vehicles can be served by neighbors, which can improve the sharing efficiency and alleviate the burden of networks. Furthermore, we use a graph theory based approach to solve the content distribution by transforming it into a maximum weighted independent set problem. Finally, the proposed scheme is evaluated with a greedy transmission strategy to demonstrate its efficiency.

关键词： content distribution 5G-VANET edge computing graph theory

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A simulation-based model for a multi-domain distributed GMPLS-based IP-over-optical network work in progress paper

A simulation-based model for a multi-domain distributed GMPL...

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2014 Symposium on Theory of Modeling and Simulation - DEVS Integrative M and S Symposium, DEVS 2014;2014 Spring Simulation Multi-Conference, SpringSim 2014

作者： Albarrak, Suad Department of Computer Engineering and Networking Al-Jouf University Saudi Arabia

ISBN: (纸本)9781632662156

This paper is concerned with the development of a comprehensive simulation-based model for a multi-domain Distributed GMPLS-based IP-over-optical network using the OMNeT++ platform. The work ensured that such an implementation mirrored as far as possible the operation and performance of real multi-domain/multi-layer structure. Therefore, this model can be considered as a basis for research to investigate key issues that affect the operation of multi-domain GMPLS-based IP-over-optical networks.

关键词： Internet protocols

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Intelligent Satin Bowerbird Optimizer Based Compression Technique for Remote Sensing Images

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computers, Materials & Continua 2022年第8期72卷 2683-2696页

作者： M.Saravanan J.Jayanthi U.Sakthi R.Rajkumar Gyanendra Prasad Joshi L.Minh Dang Hyeonjoon Moon Department of Networking and Communications School of ComputingSRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Sona College of TechnologySalem636005India Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennai602105India Department of Electronics and Instrumentation Engineering Kongu Engineering CollegePerundurai638060India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

Due to latest advancements in the field of remote sensing,it becomes easier to acquire high quality images by the use of various satellites along with the sensing *** the massive quantity of data poses a challenging issue to store and effectively transmit the remote sensing ***,image compression techniques can be utilized to process remote sensing *** this aspect,vector quantization(VQ)can be employed for image compression and the widely applied VQ approach is Linde–Buzo–Gray(LBG)which creates a local optimum codebook for image *** process of constructing the codebook can be treated as the optimization issue and the metaheuristic algorithms can be utilized for resolving *** this motivation,this article presents an intelligent satin bowerbird optimizer based compression technique(ISBO-CT)for remote sensing *** goal of the ISBO-CT technique is to proficiently compress the remote sensing images by the effective design of ***,the ISBO-CT technique makes use of satin bowerbird optimizer(SBO)with LBG approach is *** design of SBO algorithm for remote sensing image compression depicts the novelty of the *** showcase the enhanced efficiency of ISBO-CT approach,an extensive range of simulations were applied and the outcomes reported the optimum performance of ISBO-CT technique related to the recent state of art image compression approaches.

关键词： Remote sensing images image compression vector quantization sand bowerbird optimizer metaheuristics space savings

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A multi-core based parallel streaming mechanism for concurrent video-on-demand applications

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IEEE Communications Letters 2009年第4期13卷 286-288页

作者： Huang, Chung-Ming Lin, Chung-Wei Tsai, Wan-Ping Laboratory of Multimedia Mobile Networking Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

In this paper, we design a novel Multi-Core based Parallel Streaming Mechanism for concurrently streaming the scalable extension of H.264/AVC videos, which is called MCPSM. MC-PSM is able to serve lots of heterogeneous users who may utilize distinct terminals through distinct network interfaces to get on-demand videos from an ISP streaming server at meanwhile. With the concept of CPU scheduling- SJF (Shortest- Job-First) and multi-core based parallel programming, multiple streaming tasks can be executed in parallel using a proposed task dispatcher based on network connection speeds, video bit-rate and users' waiting time. Comparing with a normal-threading streaming approach, the average execution time can decrease effectively and CPU resources can be utilized more fully. © 2009 IEEE.

关键词： Parallel programming

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Toward optimal embedding capacity for permutation steganography

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IEEE Signal Processing Letters 2009年第9期16卷 802-805页

作者： Huang, Nien-Ching Li, Meng-Tsan Wang, Chung-Ming Department of Computer Science and Engineering National Chung Hsing University Taichung 402 Taiwan Institute of Networking and Multimedia Department of Computer Science and Engineering National Chung Hsing University Taichung 402 Taiwan

Bogomjakov et al. proposed a universal algorithm for permutation steganography. In this paper, we introduce a more effective algorithm. A theoretical analysis indicates that our algorithm achieves 99% of optimal when using 128 elements, while Bogomjakov et al.'s method attains only 98.34% of optimal even when employing as many as 1,048,576 *** conducted an experiment using a 3-D polygon dataset for comparison. The analysis and practical experiments demonstrate that our algorithm attains a capacity closer to the optimal but has the same runtime complexity as Bogomjakov et al.'s algorithm. © 2009 IEEE.

关键词： Steganography

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