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Low power energy balanced clustering routing scheme based on improved SSA and Multi-Hop transmission in IoT

SCIENTIFIC REPORTS 2025年第1期15卷 1-20页

作者： Wang, Rui Guo, Xiaoling Sun, Xinghua Yang, Jie Hebei North Univ Sch Informat Sci & Engn Zhangjiakou 075000 Peoples R China Hebei North Univ Fac Sci Zhangjiakou 075000 Peoples R China

In the large scale monitoring application of the IoT, the power carried by a single sensor node is limited, and it may not be replenished in the later stage. Therefore, it is required that the sensor nodes should save power when working, and the power consumption among the sensor nodes should be balanced to avoid the early death of some nodes and the occurrence of monitoring blind spots in the monitor area. Communication is the main part of power loss for sensor nodes. For this reason, this paper introduces a new low power energy balanced clustering routing scheme. Firstly, the sparrow search algorithm is improved by adding adaptive sine function and Cauchy random number to raise the search capability of the discoverer;The standard normal distribution random number is used to enhance the vigilant escape from the limit of local optimal value. Then the enhanced SSA algorithm can be used for cluster head selection. A fitness function with five key parameters is constructed by using the residual energy, the member number within a cluster, the intra-cluster distance in a cluster, the distance among clusters, and the distance from cluster head to base station, which effectively realizes the energy consumption balance among sensors in each round. At the same time, in the data forwarding stage, the multi-hop forwarding rules are designed to further reduce energy loss, greatly delay the arrival of the first dead node, and keep the sensor node working in the low power mode for a long time. Experimental results show that this scheme not only significantly prolongs the sensor lifetime, but also balances the power consumption among sensor nodes. This scheme provides a new idea for IoT sensor nodes to work in low power and ultra long standby mode, especially suitable for large scale and long term deployment scenarios such as ecological monitoring and industrial equipment state perception.

关键词： Low power Energy balanced clustering routing Sparrow search algorithm Multi-hop Network lifetime

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Energy-Efficient clustering routing for WSNs Based on Multiobjective Quantum Adaptive Gray Wolf Optimization

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IEEE SENSORS JOURNAL 2025年第8期25卷 14080-14098页

作者： Xu, Mengying Zu, Yunxiao Zhou, Jie Beijing Univ Posts & Telecommun Sch Elect Engn Beijing 100876 Peoples R China Network Informat Secur Xinjiang Prod & Construct Corps Key Lab Comp Intelligence Shihezi 832000 Peoples R China Shihezi Univ Dept Informat Sci & Technol Shihezi 832000 Peoples R China

Maximizing longevity and improving the communication quality of wireless sensor networks (WSNs) are two pivotal objectives in addressing clustering routing issues. However, existing methods suffer from low quality of service (QoS), and accumulating unnecessary monitoring data results in a reduced network lifetime. In this regard, a new multiobjective quantum adaptive gray wolf optimization-based energy-efficient clustering routing (MQAGWO-EECR) algorithm is proposed, which vigorously prolongs the network lifetime and considerably reduces delay and packet loss rate. Two novel operators named quantum calculation and adaptive adjustment are devised in conjunction with gray wolf optimization (GWO), which significantly enhances solution quality and obviously improves convergence rate. Additionally, a new energy-efficient clustering routing (EECR) model involves sleep scheduling, cluster head (CH) selection, and multihop routing, which accurately captures the data transmission process. To be specific, sleep scheduling alternates nodes between active and sleep modes to reduce unnecessary energy usage. Moreover, clustering routing is designed by concurrently considering energy cost, node density, the distance between CH nodes and the base station (BS), delay, and packet loss rate, ensuring CH selection is rational and significantly guaranteeing QoS performance. The experimental results demonstrate that the proposed MQAGWO-EECR effectively optimizes energy efficiency and further extends network longevity by at least 11.09% compared to energy-efficient multihop LEACH-based clustering (EM-LEACH), KSA-DEEC, and GAPSO-H. Additionally, it decreases transmission delay by at least 5.27% and reduces packet loss rate by at least 4.84% compared to the other three algorithms.

关键词： routing Wireless sensor networks clustering algorithms Energy efficiency Optimization Energy consumption Delays Costs Monitoring Quality of service clustering routing gray wolf optimization (GWO) sleep scheduling wireless sensor networks (WSNs)

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clustering routing Algorithms In Wireless Sensor Networks: An Overview

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2012年第7期6卷 1735-1755页

作者： Liu, Xuxun Shi, Jinglun S China Univ Technol Sch Elect & Informat Engn Guangzhou Guangdong Peoples R China

Wireless sensor networks (WSNs) are becoming increasingly attractive for a variety of applications and have become a hot research area. routing is a key technology in WSNs and can be coarsely divided into two categories: flat routing and hierarchical routing. In a flat topology, all nodes perform the same task and have the same functionality in the network. In contrast, nodes in a hierarchical topology perform different tasks in WSNs and are typically organized into lots of clusters according to specific requirements or metrics. Owing to a variety of advantages, clustering routing protocols are becoming an active branch of routing technology in WSNs. In this paper, we present an overview on clustering routing algorithms for WSNs with focus on differentiating them according to diverse cluster shapes. We outline the main advantages of clustering and discuss the classification of clustering routing protocols in WSNs. In particular, we systematically analyze the typical clustering routing protocols in WSNs and compare the different approaches based on various metrics. Finally, we conclude the paper with some open questions.

关键词： WSN clustering routing block-based clustering grid-based clustering chain-based clustering

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clustering routing Algorithm for Underwater Sensor Networks Based on Improved Northern Pale Eagle Optimisation Algorithm 5

Clustering Routing Algorithm for Underwater Sensor Networks ...

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5th International Conference on Computer Engineering and Application (ICCEA)

作者： Tong, Xiwei Liu, Bingqi Xu, Yihu YanBian Univ Coll Engn Div Elect & Commun Engn Yanji Peoples R China

ISBN: (纸本)9798350386783;9798350386776

Aiming at the energy loss in underwater sensor networks, a routing algorithm based on improved Northern Goshawk Optimisation (NGO) algorithm is proposed. With the determination of the optimal number of cluster heads, the individual fitness function of the northern goshawk is constructed by considering the energy and distance factors. Cluster head selection is optimized using the NGO *** position update rate of candidate cluster head nodes is adjusted using convex lens and positive cosine strategies to broaden local search and expedite global search *** MATLAB simulation, the improved algorithm improves the uptime by 23.4% and 85% compared to the LEACH-improved algorithm and the classical LEACH algorithm, which effectively cuts down the network energy consumption and increases the network working time.

关键词： underwater sensor networks clustering routing NGO algorithm

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A new clustering routing method based on PECE for WSN

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2015年第1期2015卷 1页

作者： Zhang, De-gan Wang, Xiang Song, Xiao-dong Zhang, Ting Zhu, Ya-nan Tianjin Univ Technol Minist Educ Key Lab Comp Vis & Syst Tianjin 300384 Peoples R China Tianjin Univ Technol Tianjin Key Lab Intelligent Comp & Novel Software Tianjin 300384 Peoples R China Tangshan Coll Dept Comp Sci & Technol Tangshan 063200 Peoples R China

A new clustering routing method based on predictive energy consumption efficiency (PECE) for a wireless sensor network (WSN) is presented in this paper. It consists of two stages: cluster formation and stable data transfer. In the cluster formation stage, we design an energy-saving clustering routing algorithm based on the node degree, the relative distance between nodes, and the rest energy of nodes. When this algorithm selects the cluster head, the node degree and the relative distance between the nodes are fully considered, so the selected cluster not only has better coverage performance but also short average distance from other member nodes in the formative cluster;therefore, the cost of communications within the clusters is small. In the stable data transfer stage, by using bee colony optimization (BCO), we design a PECE strategy for data transmission. On the basis of considering the predictive values of energy consumption, the hops, and the propagation delay on this route, this strategy gives a precise definition of the route yield by using two types of bee agent to predict the route yield of each routing path from the source node to the sink node. Through the optimization design of the algorithm, it can improve the quality of clusters, thereby increasing the overall network performance, and reduces and balances the energy consumption of whole network and prolongs the survival time of the network.

关键词： WSN BCO PECE clustering routing

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GAPSO-SVM: An IDSS-based Energy-Aware clustering routing Algorithm for IoT Perception Layer

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WIRELESS PERSONAL COMMUNICATIONS 2022年第3期126卷 2249-2268页

作者： Shad, Mozhdeh Norouzi Maadani, Mohsen Moghadam, Meisam Nesari Islamic Azad Univ Dept Elect Engn Sci & Res Branch Tehran Iran Islamic Azad Univ Dept Elect Engn Shahr E Qods Branch Tehran Iran

With the emergence of Internet of Things (IoT) having large scale and generating huge amount of data, Intelligent Decision Support Systems (IDSSs) have attracted a lot of attention for provisioning the required Quality of Service. IoT perception layer is responsible for data dissemination of the "Things", and energy efficient clustering protocols play an important role in providing them with long-time battery operation. clustering routing protocols are among the most efficient methods in large scale IoT networks and using location-based decision support can highly simplify the routing problem. Existing literature either assume that the nodes' location is known, or rely on the expensive and energy consuming GPS modules which are not practical in most IoT use cases. Developing a low-cost and low-energy localization solution is an ongoing challenge. In this paper, an IDSS based clustering routing protocol, named GAPSO-SVM, is proposed for the IoT perception layer utilizing a Support Vector Machine (SVM) based algorithm to estimate the nodes' locations, and a hybrid Genetic Algorithm-Particle Swarm Optimization (GAPSO) based mechanism for clustering optimization. Simulation results show that, although the exact location of the nodes is not available, compared with recent similar works the convergence rate and network lifetime is enhanced by up to 80% and 11%, respectively.

关键词： clustering routing Internet of Things (IoT) Intelligent Decision Support System (IDSS) Support Vector Machine (SVM) Genetic Algorithm-Particle Swarm Optimization (GAPSO) Convergence rate

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Game-Based Dynamic clustering routing Strategy for Mobile Wireless Sensor Networks

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IEEE INTERNET OF THINGS JOURNAL 2024年第15期11卷 26481-26491页

作者： Cai, Lingru Luo, Lun Li, Zhangjie Xiong, Zhi Shantou Univ Dept Comp Sci Shantou 515063 Peoples R China

In mobile wireless sensor networks (MWSNs), the mobility of nodes imposes heightened energy management demands on the network. This study proposes a game-based dynamic clustering routing (GDCR) protocol for MWSNs. The GDCR protocol employs multidimensional clustering and constructs a mixed strategy game model among heterogeneous nodes. This model considers various factors for cluster head selection, including residual energy, movement, distance to the sink, and node spacing, ensuring comprehensive decision making. In addition, the protocol incorporates detached node management to ensure network security and stability. Simulation experiments demonstrate that the proposed protocol reduces the average network energy consumption when nodes have unrestricted movements. Furthermore, it effectively curtails fluctuations in energy consumption as the network scales up, thereby prolonging network lifetime and enhancing stability.

关键词： clustering routing detached node management energy consumption management mixed strategy games mobile wireless sensor networks (MWSNs) clustering routing detached node management energy consumption management mixed strategy games mobile wireless sensor networks (MWSNs)

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Research on clustering routing Protocol Based on Improved PSO in FANET

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IEEE SENSORS JOURNAL 2021年第23期21卷 27168-27185页

作者： Sun, Guanyu Qin, Danyang Lan, Tingting Ma, Lin Heilongjiang Univ Sch Elect Engn Harbin 150080 Peoples R China Harbin Inst Technol Sch Elect & Informat Engn Harbin 150001 Peoples R China

In disaster response, 2D wireless sensor networks fail to be deployed since a large number of sensors cannot be placed in harsh ground environments. In this case, as the best air carrier for sensors, unmanned aerial vehicles (UAVs) are always used to construct a 3D flying ad hoc network (FANET) to realize emergency communication. In FANET, however, node localization and data transmission are great challenges due to the increase in network dimensions and the high mobility of UAVs. In this paper, a novel FANET clustering routing protocol based on nodes location is proposed. Firstly, an improved particle swarm optimization (IPSO) algorithm is designed by fusing variable neighborhood search, and IPSO is used to improve the locating precision of UAVs. Furthermore, the base station (BS) clusters UAVs evenly according to nodes location, and the cluster head is determined by weighting the intra-cluster distance and residual energy of nodes. Finally, the optimal next-hop routing is selected by IPSO according to the link reliability and the distance between nodes and the BS to ensure data are transmitted to the BS timely and reliable. The simulation results show that routing protocol based on IPSO realize more efficient performance compared with the existing schemes in terms of positioning indicators, energy consumption, delay, and clustering lifetime.

关键词： routing protocols clustering algorithms Three-dimensional displays Sensors routing Wireless sensor networks Location awareness clustering routing improved particle swarm optimization UAVs positioning flying ad hoc network disaster response

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A Survey on clustering routing Protocols in Wireless Sensor Networks

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SENSORS 2012年第8期12卷 11113-11153页

作者： Liu, Xuxun S China Univ Technol Sch Elect & Informat Engn Guangzhou 510641 Guangdong Peoples R China

The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) in a wide range of applications and it has become a hot research area. Based on network structure, routing protocols in WSNs can be divided into two categories: flat routing and hierarchical or clustering routing. Owing to a variety of advantages, clustering is becoming an active branch of routing technology in WSNs. In this paper, we present a comprehensive and fine grained survey on clustering routing protocols proposed in the literature for WSNs. We outline the advantages and objectives of clustering for WSNs, and develop a novel taxonomy of WSN clustering routing methods based on complete and detailed clustering attributes. In particular, we systematically analyze a few prominent WSN clustering routing protocols and compare these different approaches according to our taxonomy and several significant metrics. Finally, we summarize and conclude the paper with some future directions.

关键词： wireless sensor networks clustering routing cluster construction data transmission taxonomy

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A Novel clustering routing Protocol with Community Structure Detection for Wireless Sensor Networks

A Novel Clustering Routing Protocol with Community Structure...

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4th International Conference on Mechanical Science and Technology (ICMSE 2014)

作者： Wu, Jie Yu Shao, Xin Yu Zhu, Hai Ping Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

ISBN: (纸本)9783037859650

A wireless sensor network (WSN) is a large collection of sensor nodes with limited power supply and constrained computational capability. clustering routing method in wireless sensor networks has been considered as an important field of research recently to prolong the network lifetime of WSNs. We present a novel clustering method that can balance the energy consumption and extend the lifetime of WSN. Network nodes can be divided into densely connected subgroups through the algorithm of detecting community structure in complex networks. Moreover, the role of cluster-head is scheduled among the cluster members according to the residual energy of nodes, and then the cluster heads send the data to the sink directly. Based on the community clustering strategy, a novel routing protocol, called community structure clustering routing protocol (CSCR), has been raised for WSN. Performance evaluation has shown that the proposed method can achieve improvement compared with LEACH and SEP.

关键词： clustering routing community structure WSN

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