基于混沌粒子群与蚁群算法的WSN路由协议

为了降低无线传感器网络（WSN）能量消耗,延长网络生存周期,提出了一种基于混沌粒子群（CPSO）和蚁群算法相结合的路由协议。该协议针对典型的分簇协议LEACH（Low-Energy Adaptive Clustering Hierarchy）协议的簇头选择进行了优化,考虑了节点剩余能量和簇内密集性等因素,采用新的混沌粒子群算法对簇头选择进行优化。然后,针对LEACH协议簇头到基站采用单跳通信,容易使簇头早亡的问题,采用蚁群算法优化簇头到基站的路由路径,减少通信消耗的能量。仿真结果表明,与传统的LEACH协议相比,新的协议能有效减少能量消耗,延长网络生命周期。     

一种基于蚁群优化的分簇路由算法

在无线传感器网络路由协议的研究中,能量高效是其首要设计目标.传统LEACH协议产生簇头数目比较随机,并且簇头直接与基站通信导致能量消耗过快.在分析传统和改进LEACH路由协议的基础上,提出了一种簇头数目固定的簇头选择机制,解决了簇头分布不均匀的问题.并且将蚁群优化算法应用到无线传感器网络的路径选择中,利用蚁群的动态适应性和寻优能力,在簇头与基站之间形成一条最优路径进行通信.在Matlab平台下对新提出的算法进行仿真测试实验,实验结果表明,相对于LEACH路由协议,该算法降低了平均能量消耗,延长了网络的生命周期.     

无线传感器网络基于分簇路由的数据融合研究

无线传感器网络节点资源有限,所以需要采用有效的路由算法与数据融合机制来节省资源,延长网络寿命,提升数据采集效率。LEACH是经典分簇路由协议,针对其在簇头选择机制、数据融合以及簇头与基站通信的路由方面的不足,提出了几点改进方法,在簇头选择的算法中加入了能量控制条件,簇头与基站的路由改为更适合数据融合的多跳反向组播树,并基于信息熵提出了有效数据融合机制。仿真实验表明,改进之后的算法比原LEACH算法更有效地利用了节点资源,延长了网络生存时间。     

WSN中一种基于LEACH的协同通信算法的研究

近年来,协同通信在无线传感器网络中取得了很大的应用,重点分析和研究了一种基于低功耗自适应集簇分层型协议（LEACH）的协同通信算法;在该算法中,通过选择合适的协同节点来发送数据可以有效的减少簇头节点的能量消耗,并且与多跳传输相比,又节省了路由更新耗费的能量,实验仿真证明基于LEACH的协同算法（LEACH-COOP）在能量消耗上与LEACH和基于LEACH的簇头多跳算法（LEACH-MH）相比表现出了更优的性能。     

物联网无线传感器网络中基于能量变化的簇头选择算法

无线传感器网络（WSN）作为物联网中非常重要的一个环节,其网络层协议负责路由发现和维护,网络层路由协议的好坏直接影响到整个网络的性能。本文基于传感器网络的剩余能量以及簇头节点能量的变化,针对经典的LEACH协议进行改进,提出新的簇头选择算法,通过仿真,结果表明本文提出的改进能够达到优化网络性能的目的。     

基于TinyOS的无线传感器网络LEACH算法的改进

LEACH协议是无线传感器网络中最流行的分簇路由协议之一.针对LEACH算法簇分布不均匀以及网络能耗不均衡等问题提出了一种高效节能多跳路由算法.在簇建立阶段,新算法根据网络模型计算出最优簇头间距值,调整节点通信半径以控制簇的大小,形成合理网络拓扑结构;在数据传输阶段,簇头与基站之间采用多跳的通信方式,降低了节点能耗.在TinyOS操作系统下,使用nesC语言设计实现了LEACH-EEMH算法.基于TOSSIM平台的仿真结果表明,新算法较LEACH算法在均衡网络能耗、延长网络寿命方面具有显著优势.     

基于能量均衡的LEACH改进协议

能量有限性是无线传感器网络（WSN）的最重要的特性,在网络路由算法中也是优先考虑的一个主要因素。LEACH路由协议是无线传感器网络中被广泛应用的分层协议,但其簇头选取的随机性,不可避免的使该协议存在着簇头选择不合理,节点能耗不均衡的缺点。本文对一些LEACH的改进协议进行研究,在此基础上提出了一种新的LEACH改进协议,并通过理论分析证明了该协议的可靠性。     

基于双簇头非均匀分簇的LEACH协议的改进

在无线传感器网络中的LEACH协议是一种自适应聚类路由算法．由于LEACH协议存在着无法控制簇首在网络中的分布位置、簇首选择方式限制条件不够等缺点导致能量消耗太大．基于簇头能量限制和双簇头路由方式,对LEACH协议进行了改进,设计了一种降低能耗的双簇头非均匀分簇路由协议．双簇头非均匀分簇路由协议采用NS2进行网络仿真实验,通过仿真结果的分析以及与LEACH协议的对比,证明双簇头非均匀分簇路由协议有效提高了网络能耗的均衡性．     

无线传感器网络LEACH协议的研究与改进

无线传感器网络(WSN)的数据传输不能与路由协议分离,高效的能量传输是无线传感器网络中最重要的因素之一。针对LEACH簇头分布的不均匀以及与基站距离的不同,提出了一种改进的LEACH算法,该算法考虑剩余能量和最优簇头,与现有的LEACH协议相比,该协议降低了能耗。     

基于剩余能量和节点度的多跳分簇算法的研究

LEACH协议是第一个在无线传感器网络中提出的分簇路由协议,由于其簇头产生的随机性,产生了一些不足,因此为了均衡整个网络的能耗,延长WSN的生命周期,提出了基于节点剩余能量和节点度的多跳分簇路由协议。其基本思想是在LEACH中加入门限,让剩余能量高且节点度高的节点优先成为簇头,簇头之间采用多跳路由传输机制。仿真结果表明,该协议能够有效地延长网络的生命期。     

Energy‐efficient multihop routing in WSN using the hybrid optimization algorithm

The technical growth in the field of the wireless sensor networks (WSNs) has resulted in the process of collecting and forwarding the massive data between the nodes, which was a major challenge to the WSNs as it is associated with greater energy loss and delay. This resulted in the establishment of a routing protocol for the optimal selection of the multipath to progress the routing in WSNs. This paper proposes an energy‐efficient routing in WSNs using the hybrid optimization algorithm, cat–salp swarm algorithm (C‐SSA), which chooses the optimal hops in progressing the routing. Initially, the cluster heads (CHs) are selected using the low‐energy adaptive clustering hierarchy (LEACH) protocol that minimizes the traffic in the network. The CHs are engaged in the multihop routing, and the selection of the optimal paths is based on the proposed hybrid optimization, which chooses the optimal hops based on the energy constraints, such as energy, delay, intercluster distance, intracluster distance, link lifetime, delay, and distance. The simulation results prove that the proposed routing protocol acquired minimal delay of 0.3165 with 50 nodes and two hops, maximal energy of 0.1521 with 50 nodes and three hops, maximal number of the alive nodes as 39 with 100 nodes and two hops, and average throughput of 0.9379 with 100 nodes and three hops.     

Double Cluster Based Energy Efficient Routing Protocol for Wireless Sensor Network

Reducing the energy consumption of sensor nodes and prolonging the life of the network is the central topic in the research of wireless sensor network (WSN) protocol. The low-energy adaptive clustering hierarchy (LEACH) is one of the hierarchical routing protocols designed for communication in WSNs. LEACH is clustering based protocol that utilizes randomized rotation of local cluster-heads to evenly distribute the energy load among the sensors in the network. But LEACH is based on the assumption that each sensor nodes contain equal amount of energy which is not valid in real scenarios. A developed routing protocol named as DL-LEACH is proposed. The DL-LEACH protocol cluster head election considers residual energy of nodes, distance from node to the base station and neighbor nodes, which makes cluster head election reasonable and node energy consumption balance. The simulation results of proposed protocols are compared for its network life time in MATLAB with LEACH protocol. The DL-LEACH is prolong the network life cycle by 75 % than LEACH.     

基于LEACH协议的WSNs楼宇环境监控系统的设计

针对楼宇环境监控的布线复杂与高功耗,设计了一种基于WSNs的大楼监控系统,使用了LEACH路由协议,构造了一个基于簇的网络。由于系统中的节点受到无线传输范围的限制,距离较远的簇首不能直接传递信息包给汇聚节点,所以簇首信息的交换被一个以汇聚节点为根的多跳生成树代替,汇聚节点将信息汇总然后发送至服务器内,这种簇的构造方法消耗节点能量少。子节点周期性地记录各种环境数据,实现数据传输。现场测试结果表明:此系统数据采集准确,操作方便,结构简单,实时性好。     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

一种基于K-means的WSN移动汇聚路由算法

无线传感网络(Wireless Sensor Network,WSN)作为一种资源受限的网络,网络中节点的能耗直接影响了网络的性能。因此,均衡网络中的能耗,延长网络的生命周期,成为设计WSN路由算法的重要目标。于是,在LEACH-C协议的基础上提出了一种移动汇聚路由算法。分簇阶段由Sink节点计算最优簇首个数,通过K-means聚类将网络中的节点划分至不同的集群,选择通信成本最低的节点作为各集群的簇首。稳定传输阶段通过移动Sink进行数据采集,针对不同的延迟分别规划Sink节点的移动轨迹。MATLAB仿真结果表明,与LEACH和LEAHC-C算法相比簇首的分布更合理,结合Sink节点的移动策略能有效均衡网络能耗,延长网络的寿命。     

An Improved LEACH Routing Algorithm for Wireless Sensor Network

Optimization of energy consumption is major concern for the design and planning of wireless sensor networks (WSNs). Recent research has demonstrated that organizing nodes in clusters has higher energy efficiency. LEACH is the most popular routing protocol for cluster-based in WSNs, and FCM algorithm is used for the optimum number of the clusters and their location. Aiming at the shortcomings of LEACH and FCM-LEACH, which including inaccurate cluster centers, unreasonable clustering and sole data transmission mode. This paper proposes a new energy efficient routing algorithm (NF-LEACH). In the new algorithm, There are many factors have considered to prolong the network life cycle that they are the degree of membership, residual energy, base station distance and data transmission mode. Finally, the comparison among LEACH, FCM-LEACH, and NF-LEACH has been done. The results show that the NF-LEACH has the longest lifetime and the most evenly distributed amongst three algorithms.     

An Improved Fuzzy Unequal Clustering Algorithm for Wireless Sensor Network

This paper introduces IFUC, which is an Improved Fuzzy Unequal Clustering scheme for large scale wireless sensor networks (WSNs).It aims to balance the energy consumption and prolong the network lifetime. Our approach focuses on energy efficient clustering scheme and inter-cluster routing protocol. On the one hand, considering each node’s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine each node’s chance of becoming cluster head and estimate the cluster head competence radius. On the other hand, we use Ant Colony Optimization (ACO) method to construct the energy-aware routing between cluster heads and base station. It reduces and balances the energy consumption of cluster heads and solves the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The validation experiment results have indicated that the proposed clustering scheme performs much better than many other methods such as LEACH, CHEF and EEUC.     

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

In wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering‐based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked–LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols.     

Modulated relay based stable election protocol for large-scale wireless sensor networks

Internet of things (IoT) applications based on wireless sensor networks (WSNs) have recently gained vast momentum. These applications vary from health care, smart cities, and military applications to environmental monitoring and disaster prevention. As a result, energy consumption and network lifetime have become the most critical research area of WSNs. Through energy-efficient routing protocols, it is possible to reduce energy consumption and extend the network lifetime for WSNs. Using hybrid routing protocols that incorporate multiple transmission methods is an effective way to improve network performance. This paper proposes modulated R-SEP (MR-SEP) for large-scale WSN-based IoT applications. MR-SEP is based on the well-known stable election protocol (SEP). MR-SEP defines three initial energy levels for the nodes to improve the network energy distribution and establishes multi-hop communication between the cluster heads (CHs) and the base station (BS) through relay nodes (RNs) to reduce the energy consumption of the nodes to reach the BS. In addition, MR-SEP reduces the replacement frequency of CHs, which helps increase network lifetime and decrease power consumption. Simulation results show that MR-SEP outperforms SEP, LEACH, and DEEC protocols by 70.2%, 71.58%, and 74.3%, respectively, in terms of lifetime and by 86.53%, 86.68%, and 86.93% in terms of throughput.