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IoT Computing Collaboration and Data-Aware routing algorithm for Edge Computing and DL

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2024年第11期38卷

作者： Li, Bo Tang, JinHong Yang, Zhihe Jiang, Qing Wei, Jingyang ShangHai DianJi Univ Sch Elect Infomat Engn Shanghai 200240 Peoples R China JiangXi Ind Polytech Coll Nanchang 330096 Peoples R China West Anhui Univ Fac Elect & Informat Engn Luan 237012 Peoples R China Jiangxi Siyuan Technol Co Ltd Nanchang 330000 Peoples R China

With the development of mobile edge computing and neural network Deep Learning (DL), more and more scholars are studying the combination of the two. This paper mainly studies the application of mobile edge computing and neural network DL in IoT computing collaboration and data-aware routing algorithms. Therefore, this paper proposes the deployment options of MEC technology and ETSIMEC in mobile edge computing, combining mobile edge computing with DL, designs an optimization algorithm based on Markov decision process and feature expression learning, and then analyzes and optimizes IoT computing and VANET routing algorithm. In order to have a clearer direction for the optimization algorithm, this paper also designs the edge computing model training and experiment comparison, the DL algorithm comparison experiment, and the routing algorithm simulation experiment and performance analysis. Combined with the experimental results, it is optimized and compared with traditional IoT computing and routing algorithms. Finally, it is concluded that the computing efficiency of IoT computing based on edge computing and DL designed in this paper is 21.33% higher than that of traditional IoT computing. The efficiency of the routing algorithm based on edge computing and DL designed in this paper is 9.29% higher than that of the traditional routing algorithm.

关键词： Edge computing deep learning internet of things technology routing algorithm

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A novel look-ahead routing algorithm based on graph theory for triplet-based network-on-chip router

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IEICE ELECTRONICS EXPRESS 2018年第8期15卷 20180300-20180300页

作者： Chen, Xu Shi, Feng Yin, Fei Wang, Xiaojun Beijing Inst Technol Beijing 100081 Peoples R China

The WK-recursive network well conforms to implementation of large distributed systems due to its many favorable properties. In this paper, we employ the concept S-3 group to establish an efficient look-ahead routing algorithm for the triplet-based WK-recursive network. Remarkably, we introduce a data flow model to categorize message traffic as six flow models. For the sake of simplicity, we further leverage the permutation group S(3)to transform different flow models to one model and hence routing computing can be performed in the same model. It is demonstrated that our proposed design can achieve better network performance.

关键词： routing algorithm network-on-chip look-ahead routing graph theory multicore system

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Coordinated planning of multi-area multi-energy systems by a novel routing algorithm based on random scenarios

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 131卷 107028-107028页

作者： Zhou, Nan Xie, Da Gu, Chenghong Li, Guojie Zhang, Luqing Lou, Ziyang Chen, Yang Zhang, Yanchi Chen, Aikang Shanghai Jiao Tong Univ Elect Engn Dept Minist Educ Key Lab Control Power Transmiss & Convers Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Environm Sci & Engn Shanghai 200240 Peoples R China Univ Bath Dept Elect & Elect Engn Bath Avon England Shanghai Dianji Univ Shanghai 201306 Peoples R China

As an important Energy Internet technology, energy router (ER) can implement energy routing and information interconnection for the electrical grid within a certain geography range. However, multi-energy supply allocation between multi-energy routers (MERs) has to be resolved, which can connect isolated area networks and expand the scale of the energy Internet. In this paper, equipment capacity and network routing are planned for multiarea multi-energy system (MAMES), which integrates multiple MERs with a virtual multi-energy router (VMER). Firstly, based on the VMER, the concept of MAMES is proposed. Then, the correlation model of multienergy networks in VMER is constructed, based on MER energy transmission conversion extension model and hybrid power flow model. And the novel routing algorithm is proposed to determine the energy candidate set of the integrated energy networks. During planning, the random scenario generation based on Latin hypercube sampling (LHS) and scenario reduction based on k-means clustering are applied. Finally, the simulation shows that the planning method based on the routing algorithm can effectively obtain the capacity of energy equipment inside MERs and the routing layout between MERs in the MAMES. Proposed routing algorithm and operation scenarios reduction greatly improve the efficiency of planning. Correlated planning helps improve energy efficiency, environment protection, and economic benefits of MAMES.

关键词： Multi-energy router Virtual multi-energy router routing algorithm Multi-area multi-energy system MAMES planning

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Double Stairs: A Fault-Tolerant routing algorithm for Networks-on-Chip

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2016年第6期25卷 1650065-1650065页

作者： Fakhrali, Saleh Zarandi, Hamid R. Amirkabir Univ Technol Tehran Polytech Dept Comp Engn & Informat Technol Tehran Iran Inst Res Fundamental Sci IPM Sch Comp Sci Tehran Iran

Reliability is one of the main concerns in the design of networks-on-chip (NoCs) due to the use of deep submicron technologies in fabrication of such products. This paper presents a new fault-tolerant routing algorithm called double stairs for NoCs. Double stairs routing algorithm is a low overhead routing that has the ability to deal with fault. The proposed routing algorithm makes a redundant copy of each packet at the source node and routes the original and redundant packets in a new partially adaptive routing algorithm. The method is evaluated for various packet injection rates and fault rates. Experimental results show that the proposed routing algorithm offers the best trade-off between performance and fault tolerance compared to other routing algorithms, namely flooding, XYX and probabilistic flooding.

关键词： Networks-on-chip routing algorithm fault-tolerant routing performance analysis

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Energy Efficient Cluster Head Selection and routing algorithm using Hybrid Firefly Glow-Worm Swarm Optimization in WSN

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2023年第8期17卷 2140-2156页

作者： Bharathiraja, S. Selvamuthukumaran, S. Balaji, V AVC Coll Engn Dept Elect & Commun Engn Mannampandal Mayiladuthurai India AVC Coll Engn Dept Comp Applicat Mannampandal Mayiladuthurai India KCG Coll Technol Dept Elect & Commun Engn Chennai India

The Wireless Sensor Network (WSN), is constructed out of teeny-tiny sensor nodes that are very low-cost, have a low impact on the environment in terms of the amount of power they consume, and are able to successfully transmit data to the base station. The primary challenges that are presented by WSN are those that are posed by the distance between nodes, the amount of energy that is consumed, and the delay in time. The sensor node's source of power supply is a battery, and this particular battery is not capable of being recharged. In this scenario, the amount of energy that is consumed rises in direct proportion to the distance that separates the nodes. Here, we present a Hybrid Firefly Glow-Worm Swarm Optimization (HF-GSO) guided routing strategy for preserving WSNs' low power footprint. An efficient fitness function based on firefly optimization is used to select the Cluster Head (CH) in this procedure. It aids in minimising power consumption and the occurrence of dead sensor nodes. After a cluster head (CH) has been chosen, the Glow-Worm Swarm Optimization (GSO) algorithm is used to figure out the best path for sending data to the sink node. Power consumption, throughput, packet delivery ratio, and network lifetime are just some of the metrics measured and compared between the proposed method and methods that are conceptually similar to those already in use. Simulation results showed that the proposed method significantly reduced energy consumption compared to the state-of-the-art methods, while simultaneously increasing the number of functioning sensor nodes by 2.4%. Proposed method produces superior outcomes compared to alternative optimization-based methods.

关键词： Cluster head selection routing algorithm Wireless Sensor Network Firefly algorithm Glow Worm Swarm Optimization

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A clustering routing algorithm based on wolf pack algorithm for heterogeneous wireless sensor networks

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COMPUTER NETWORKS 2020年第0期167卷 106994-000页

作者： Xiu-wu, Y. U. Hao, Y. U. Yong, Liu Ren-rong, Xiao Univ South China 28 Changsheng West Rd Hengyang 421001 Hunan Peoples R China Hunan Engn Res Ctr Uranium Tailings Decommiss & T 28 Changsheng West Rd Hengyang 421001 Hunan Peoples R China

In order to maximize the network performance of heterogeneous sensor networks and effectively control the network cost, a clustering routing algorithm based on wolf pack algorithm (CLWPA) for heterogeneous wireless sensor networks is proposed. Firstly, the optimal deployment of heterogeneous nodes is transformed into a mixed integer programming problem. The approximate optimal solution of the problem is obtained by through the wolf pack algorithm (WPA) which improved by logistic function and levy flight then a heterogeneous network routing algorithm based on the improved wolf pack algorithm (LWPA) is proposed. Secondly, in order to solve the problem of fixed path in LWPA routing algorithm, the concept of edge degree is introduced to improve DEEC algorithm. The improved DEEC algorithm (IDEEC) is used to dynamically cluster common nodes in heterogeneous networks, and the data transmission mode is carried out after the clustering mode set. Finally, through simulation analysis, compared with other three heterogeneous network routing algorithms, CLWPA algorithm effectively prolongs the network's stable period and lifetime, and the energy consumption is more balanced. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Heterogeneous sensor networks Wolf pack algorithm routing algorithm Dynamic clustering

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Ring-Split: Deadlock-Free routing algorithm for Circulant Networks-on-Chip

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MICROMACHINES 2023年第1期14卷 141-141页

作者： Romanov, Aleksandr Y. Myachin, Nikolay M. Lezhnev, Evgenii, V Ivannikov, Alexander D. El-Mesady, Ahmed HSE Univ Moscow 101000 Russia OOO OZON TEKHNOL Moscow 123112 Russia Russian Acad Sci Inst Design Problems Microelect Moscow 124365 Russia Menoufia Univ Fac Elect Engn Dept Phys & Engn Math Menoufia 32952 Egypt

This article considers the usage of circulant topologies as a promising deadlock-free topology for networks-on-chip (NoCs). A new high-level model, Newxim, for the exploration of NoCs with any topology is presented. Two methods for solving the problem of cyclic dependencies in circulant topologies, which limit their applications for NoCs due to the increased possibility of deadlocks, are proposed. The first method of dealing with deadlocks is universal and applicable to any topology;it is based on the idea of bypassing blocked sections of the network on an acyclic subnetwork. The second method-Ring-Split-takes into account the features of circulant topologies. The results of high-level modeling and comparison of the peak throughput of NoCs for circulant and mesh topologies using deadlock-free routing algorithms are presented. It was shown that a new approach for routing in circulants (compared to mesh topology) shows up to 59% better network throughput with a uniform distribution of network load.

关键词： network-on-chip routing algorithm deadlock circulant topology NoC modeling

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FedRDR: Federated Reinforcement Distillation-Based routing algorithm in UAV-Assisted Networks for Communication Infrastructure Failures

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DRONES 2024年第2期8卷 49-49页

作者： Li, Jie Liu, Anqi Han, Guangjie Cao, Shuang Wang, Feng Wang, Xingwei Northeastern Univ Sch Comp Sci & Engn Shenyang 110167 Peoples R China Hohai Univ Dept Informat & Commun Syst Changzhou 213022 Peoples R China Northeastern Univ Sch Software Coll Shenyang 110167 Peoples R China

Traditional Internet of Things (IoT) networks have limited coverage and may experience failures due to natural disasters affecting critical IoT devices, making it difficult for them to provide communication services. Therefore, how to establish network communication service more efficiently in the presence of fault points is the problem we solve in this paper. To address this issue, this study constructs a hierarchical multi-domain data transmission architecture for an emergency network with unmanned aerial vehicles (UAVs) employed as core communication devices. This architecture expands the functionality of UAVs as key network devices and provides a theoretical basis for their feasibility as intelligent network controllers and switches. Firstly, the UAV controllers perceive the network status and learn the spatio-temporal characteristics of air-to-ground network links. Secondly, a routing algorithm within the domain based on federated reinforcement distillation (FedRDR) is developed, which enhances the generalization capability of the routing decision model by increasing the training data samples. Simulation experiments are conducted, and the results show that the average communication data size between each domain controller and the server is approximately 45.3 KB when using the FedRDR algorithm. Compared to the transmission of parameters through federated reinforcement learning algorithms, FedRDR reduces the transmitted parameter size by approximately 29%. Therefore, the FedRDR routing algorithm helps to facilitate knowledge transfer, accelerate the training process of intelligent agents within the domain, and reduce communication costs in resource-constrained scenarios for UAV networks and has practical value.

关键词： routing algorithm UAV-assisted networks reinforcement learning federated learning

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GIR: An Opportunistic Network routing algorithm Based on Game Theory

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IEEE ACCESS 2020年 8卷 201158-201172页

作者： Li, Limiao Wang, Haotian Liu, Zhixiong Ye, Hui Changsha Univ Sch Comp Engn & Appl Math Changsha 410003 Peoples R China Cent South Univ Sch Comp Sci & Engn Changsha 410075 Peoples R China

A large number of routing algorithms in Opportunistic Networks are based on the assumption that nodes are free to help other nodes forward messages. However, when the Opportunistic Network is applied to an urban environment, the nodes will have certain social attributes. In many cases, a node can decide whether to execute the routing policy or not. Due to the limited resources and poor social relationships, nodes may be unwilling to forward messages from other nodes and have strong motivation to implement selfish policies. As a result, increased network latency reduces message delivery rates and affects the overall network performance. In order to solve this problem, we propose a perceptual routing protocol to promote node cooperation from the perspective of game theory. Specifically, We introduce the concept of virtual currency and construct a price function, and nodes can obtain a certain virtual currency through cooperation. In the process of message forwarding, we consider the change of link degree and energy of node (the energy exists in the form of electricity in this article), and use them as factors of the trading node quotation. The trading node finally makes it through the multiple rounds of bargaining games, so that the proposed game between both sides reaches the Nash equilibrium. Experiments show that the algorithm outperforms Epidemic, EPSR, MINEIRO and ICRP algorithms in terms of delivery rate, average latency and energy consumption. According to the simulation experiments, the average delivery ratio of GIR algorithm is 0.68, which is 13% higher than that of the epidemic algorithm. In terms of average delay, 7% is better than ICRP algorithm.

关键词： Cooperation routing algorithm Nash equilibrium selfish

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An energy recovery routing algorithm for opportunistic networks based on connection stability and node encounter type

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AD HOC NETWORKS 2024年 157卷

作者： Fu, Yanhe Zhou, Bo Xu, Gang Wang, Yuqi Huang, Baoqi Zhang, Feng Inner Mongolia Univ Coll Comp Sci Hohhot 010021 Peoples R China Inner Mongolia Univ Engn Res Ctr Ecol Big Data Minist Educ Hohhot 010021 Peoples R China Shanxi Univ Sch Comp & Informat Technol Taiyuan Peoples R China

routing algorithms have been the focus of research on opportunistic networks to effectively deal with the connectivity problem of intermittent communication in opportunistic networks. Due to the frequent forwarding of messages by active nodes in the opportunistic networks leading to excessive energy consumption, opportunistic networks suffer from communication susceptibility to interruption and unstable network connectivity. In order to solve this problem, this paper proposes an opportunistic network routing algorithm (ST-ProPhet) based on connection stability and energy recovery, which takes into account the node's historical average connection duration, encounter probability, and the node's energy consumption. Firstly, a node encounter probability prediction model fusing the average connection duration is developed. Secondly, the base station is introduced and the node wireless energy recovery strategy is designed. Finally, the ST-ProPhet algorithm proposes a message forwarding strategy based on node encounter types on the basis of the encounter probability prediction model and energy recovery model. Simulation experiments show that the ST-ProPhet algorithm has an overall reduction of 5066.27mAh over the ProPhet algorithm in terms of average message energy consumption.

关键词： Opportunistic networks routing algorithm Connection duration Energy recovery

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