无线传感器网络基于梯度的分簇路由算法

无线传感器网络中节点的能量是有限的,而且一般不能补充能量。所以如何最大化节点能量的利用率,延长整个传感器网络的生命周期,一直是无线传感器网络的一个研究热点。本文针对Leach路由算法的不足,提出一种新的基于能量考虑的梯度分簇路由算法。最后通过OMNET＋＋仿真试验,来验证新的路由算法的优越性。     

无线传感器网络基于梯度的分簇路由算法

无线传感器网络中节点的能量是有限的,而且一般不能补充能量.所以如何最大化节点能量的利用率,延长整个传感器网络的生命周期,一直是无线传感器网络的一个研究热点.本文针对Leach路由算法的不足,提出一种新的基于能量考虑的梯度分簇路由算法.最后通过OMNET++仿真试验,来验证新的路由算法的优越性.     

无线传感器网络中分簇算法能量有效性分析

该文针对无线传感器网络是一种能量受限的网络,首先说明根据节点数目以及分布区域特征,确定合理的成簇数目是分簇算法设计的核心;然后给出节点在通信中使用的能量模型,按照分簇的不同层数,分别对其成簇的数目进行理论上的优化分析,最后通过实验的方法验证优化的分簇算法能够满足能量有效性,对均匀节点能耗分布,提高网络生存时间有着重要作用。     

无线传感网络移动分簇路由策略

无线传感网络(WSN)路由协议中,分簇路由具有拓扑管理方便、能量高效和数据融合简单等优点,成为当前重点研究的路由技术。通过研究各种环境下的移动传感器网络,有效地降低能耗则是研究移动无线传感器网络的重要目的之一。针对无线传感网络中移动性问题,基于LEACH协议,利用移动传感器网络中节点距离、速度和剩余能量等因素提出了能量高效的移动分簇路由算法。实验结果表明此算法能够较好地支持节点移动,从而降低网络能耗,延长网络生存时间。     

基于能量均衡的LEACH协议的研究

无线传感器网络节点能量有限,因此为了避免由于节点的能量不足而造成网络瘫痪,在组网过程中必须要充分考虑到节点能量的情况,Leach协议是其中一种典型的网络分簇路由协议。针对传统leach协议在分簇过程中未能考虑网络内节点能量以及簇首数量的基础上,提出一种新的簇首选取优化算法,旨在达到均衡网络能量、延长网络生命周期的结果。经OPNET仿真表明,该算法能快速选择簇首、节省节点能量以及均衡网络的能量分布,最后有效地延长网络的生命周期。     

一种WSN中分簇路由算法的改进

在无线传感器网络中,基于分簇的路由协议对提高网络的寿命有着重要作用,LEACH是一种应用比较广泛的层次路由协议。本文提出一种新的基于最优分簇的无线传感器网络分簇路由（LEACH-O）算法,在簇的形成过程考虑到节点的集中程度和节点的剩余能量,从而减少传感器节点的能量消耗,优化资源利用率。仿真实表明,与传统的LEACH算法相比,该算法配传感器节点间数据传输提供了高效路由,从而延长网络的生命周期。     

一种基于贝叶斯博弈的传感器网络分簇算法

提出了一种基于贝叶斯博弈的无线传感器网络分簇算法.算法将无线传感器网络节点的簇头选择抽象为一个多人的博弈过程,节点之间通过不完全信息的静态博弈实现簇头的合理分布.算法在支付函数的设计时充分考虑了节点能耗和路径损耗等因素,因此通过博弈该算法能实现簇头的合理分布.仿真结果表明,算法在保证数据传输实时性的前提下可使网络能耗更加稳定、能量分布更加均匀,有效地延长网络生命周期.     

一种基于UAV的无人海岛监控网络数据收集策略

针对传统的最小跳路由无线传感器网络（WSN）在数据汇聚上较高的能量开销问题,提出了一种基于无人机(UAV)数据收集的动态分簇算法,其主要思想是利用节点剩余能量来确定那些节点可以当选簇首,同时利用节点坐标位置和设定地分簇半径来划分簇的大小。该算法的优势是能最大程度地均衡每个传感器节点的能量,使整体的节点剩余的能量维持在同一水平。为了提高数据收集的效率,采用蚁群算法规划了无人机数据收集的最短路径。仿真结果表明,与相同的分簇算法下传统的最小跳路由无线传感器网络相比,所提出的基于无人机的无线传感器网络（UAV-WSN）在能量利用率和生命周期方面分别提升了15%和25%,并且以上两种网络的能量利用率高达70%。     

基于LEACH的WSN路由算法研究

为了提高无线传感器网络的可扩展性在其路由协议中通常会采用分簇技术。由于无线传感器网络由能量有限的节点组成,网络中节点的能量多为电池供电,因此高效节能以延长网络生命周期是无线传感器网络必须要充分考虑的问题。针对LEACH(低功耗自适应分簇)路由算法在簇首选择时存在的问题,提出一种改进建议。对改进算法利用仿真工具NS2进行仿真,并对节点存活率和网络能耗两个方面进行比较与分析,仿真结果表明,改进算法很好地延长了网络的寿命。     

LEACH协议中的最佳建簇概率

无线传感器网络中,传感器节点是通过携带能量有限的电池供电,因此如何有效利用能量,延长节点的生命周期是无线传感器网络首要研究的问题。为了达到降低网络能源消耗的目的,本文在第一顺序无线电模型的基础上利用能量消耗的关系得到了典型分簇路由协议LEACH的最佳建簇概率。研究结果表明,当分簇数目小于最佳建簇数目时,传感器网络每轮消耗的总能量就会以指数方式增加,说明确立最佳建簇数目可以降低网络能耗,从而提高无线传感器网络的整体生存时间。 更多还原     

无线传感器网络分簇算法分析与性能比较

文中在介绍无线传感器网络路由协议的基础上,重点分析了几种有代表性的分簇路由协议算法。然后对各种分簇算法从10个评价参数上进行了一个综合对比,总结了无线传感器网络现有分簇路由协议的优点和存在的问题。最后从网络安全性和协议的实用性等方面,并对无线传感器网络分簇路由协议算法进行了展望。     

Multi-factor and Distributed Clustering Routing Protocol in Wireless Sensor Networks

One of important issues in wireless sensor networks is how to effectively use the limited node energy to prolong the lifetime of the networks. Clustering is a promising approach in wireless sensor networks, which can increase the network lifetime and scalability. However, in existing clustering algorithms, too heavy burden of cluster heads may lead to rapid death of the sensor nodes. The location of function nodes and the number of the neighbor nodes are also not carefully considered during clustering. In this paper, a multi-factor and distributed clustering routing protocol MFDCRP based on communication nodes is proposed by combining cluster-based routing protocol and multi-hop transmission. Communication nodes are introduced to relay the multi-hop transmission and elect cluster heads in order to ease the overload of cluster heads. The protocol optimizes the election of cluster nodes by combining various factors such as the residual energy of nodes, the distance between cluster heads and the base station, and the number of the neighbor nodes. The local optimal path construction algorithm for multi-hop transmission is also improved. Simulation results show that MFDCRP can effectively save the energy of sensor nodes, balance the network energy distribution, and greatly prolong the network lifetime, compared with the existing protocols.     

Adaptive Online Sensor Clustering and Routing Algorithms for QoS Provisioning and Energy Efficiency

Due to the limited energy supply, energy efficiency is the most important issue for wireless sensor networks. In addition, next generation networks are also expected to support QoS sensitive data services. In this paper, a new online sensor network management scheme is developed for energy efficiency and QoS provisioning. To satisfy these conflicting requirements, the proposed scheme consists of clustering and routing algorithms. Without global network information, the online control paradigm is realized in a distributed way. Therefore, the principle contributions of these algorithms are its scalability and responsiveness to current network situations. Simulation results indicate the superior performance of the proposed schemes, while other schemes cannot offer such an attractive performance balance.     

Dual head static clustering algorithm for wireless sensor networks

Clustering of nodes is often used in wireless sensor networks to achieve data aggregation and reduce the number of nodes transmitting the data to the sink. This paper proposes a novel dual head static clustering algorithm (DHSCA) to equalise energy consumption by the sensor nodes and increase the wireless sensor network lifetime. Nodes are divided into static clusters based on their location to avoid the overhead of cluster re-formation in dynamic clustering. Two nodes in each cluster, selected on the basis of the their residual energy and their distance from the sink and other nodes in the cluster, are designated as cluster heads, one for data aggregation and the other for data transmission. This reduces energy consumption during intra-cluster and inter-cluster communication. A multi-hop technique avoiding the hot-spot problem is used to transmit the data to the sink. Experiments to observe the energy consumption patterns of the nodes and the fraction of packets successfully delivered using the DHSCA suggest improvements in energy consumption equalisation, which, in turn, enhances the lifetime of the network. The algorithm is shown to outperform all the other static clustering algorithms, while being comparable with the performance of the best dynamic algorithm.     

A comparative study of distributed frequency assignment algorithms for wireless sensor networks

Wireless sensor networks are composed of energy constrained nodes embedding limited transmission, processing and sensing capabilities. The main research efforts in this area sought to prolong the network lifetime by reducing energy consumption of network operations. Data gathering mechanisms such as clustering have been shown to achieve significant energy savings. However, such benefits can be obtained only if neighboring clusters operate on different frequencies (channels). As the salient characteristics of wireless sensor networks favor a distributed approach, we analyze the performance of several distributed frequency assignment algorithms with a focus on energy consumption. In this context, we find that a heuristic may achieve better results than backtracking-based algorithms.     

LUCA: An Energy-efficient Unequal Clustering Algorithm Using Location Information for Wireless Sensor Networks

Over the last several years, various clustering algorithms for wireless sensor networks have been proposed to prolong network lifetime. Most clustering algorithms provide an equal cluster size using node??s ID, degree and etc. However, many of these algorithms heuristically determine the cluster size, even though the cluster size significantly affects the energy consumption of the entire network. In this paper, we present a theoretical model and propose a simple clustering algorithm called Location-based Unequal Clustering Algorithm (LUCA), where each cluster has a different cluster size based on its location information which is the distance between a cluster head and a sink. In LUCA, in order to minimize the energy consumption of entire network, a cluster has a larger cluster size as increasing distance from the sink. Simulation results show that LUCA achieves better performance than conventional equal clustering algorithm for energy efficiency.     

A grid based clustering and routing algorithm for solving hot spot problem in wireless sensor networks

Energy conservation of the sensor nodes is the most important issue that has been studied extensively in the design of wireless sensor networks (WSNs). In many applications, the nodes closer to the sink are overburdened with huge traffic load as the data from the entire region are forwarded through them to reach the sink. As a result, their energy gets exhausted quickly and the network is partitioned. This is commonly known as hot spot problem. Moreover, sensor nodes are prone to failure due to several factors such as environmental hazards, battery exhaustion, hardware damage and so on. However, failure of cluster heads (CHs) in a two tire WSN is more perilous. Therefore, apart from energy efficiency, any clustering or routing algorithm has to cope with fault tolerance of CHs. In this paper, we address the hot spot problem and propose grid based clustering and routing algorithms, combinedly called GFTCRA (grid based fault tolerant clustering and routing algorithms) which takes care the failure of the CHs. The algorithms follow distributed approach. We also present a distributed run time management for all member sensor nodes of any cluster in case of failure of their CHs. The routing algorithm is also shown to tolerate the sudden failure of the CHs. The algorithms are tested through simulation with various scenarios of WSN and the simulation results show that the proposed method performs better than two other grid based algorithms in terms of network lifetime, energy consumption and number of dead sensor nodes.     

A Centralized Balance Clustering Routing Protocol for Wireless Sensor Network

Routing protocol plays a role of great importance in the performance of wireless sensor networks (WSNs). A centralized balance clustering routing protocol based on location is proposed for WSN with random distribution in this paper. In order to keep clustering balanced through the whole lifetime of the network and adapt to the non-uniform distribution of sensor nodes, we design a systemic algorithm for clustering. First, the algorithm determines the cluster number according to condition of the network, and adjusts the hexagonal clustering results to balance the number of nodes of each cluster. Second, it selects cluster heads in each cluster base on the energy and distribution of nodes, and optimizes the clustering results to minimize energy consumption. Finally, it allocates suitable time slots for transmission to avoid collision. Simulation results demonstrate that the proposed protocol can balance the energy consumption and improve the network throughput and lifetime significantly.     

A stable energy efficient clustering protocol for wireless sensor networks

Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.