无线传感器网络中的路由能耗优化策略的研究

无线传感器网络由于受到实际通信环境的限制,传感节点在进行路由计算与数据转发时所需的电力能源主要由一次性电池供给。为了能够有效的节约节点上的路由能耗,提出了基于网络编码及动态功率控制优化策略,通过优化节点路由的数据转发次数和发射功率,减少了传感节点的路由能耗,延长了网络的生命周期。     

基于交叉流网络编码的节能路由

节能路由是无线自组织网络的一个重要研究课题,对延长网络生存时间极为重要。在传统路由下,多对节点之间通信使用的多条数据传递路径会出现交叉存在公共节点,这些公共节点因需要转发来自多条交叉路径的数据包而比其它节点消耗更多的能量,从而过早因能量耗竭而失效。为了克服这一能耗不均衡问题,该文提出基于网络编码的节能路由NCBEER (Network Coding Based Energy Efficient Routing),它可捕捉多条路径交叉的机会,让公共节点对所转发的数据包进行编码,然后把编码数据包多播(Multicast)邻居节点,以减少公共节点转发数据包次数从而降低能耗;推导了编码节点使全部接收节点接收到编码数据包所需要的平均多播次数,定义了无线链路的传输代价,并将之作为信源将流量分配给不同路径的依据。仿真试验表明,NCBEER可降低和均衡节点的能耗,且能够延长网络生存时间。     

面向智慧园区的WSN路由优化算法

为解决智慧园区中无线传感器网络(WSN)的能耗不均衡问题,构建了路由代价函数,并提出了一种新的能耗均衡路由算法.该算法结合智慧园区中无线传感器网络的特点,综合考虑节点地理位置和剩余能量来构建路由代价函数.传感器节点通过选择其邻居节点中路由代价最小的节点进行数据转发.仿真结果表明,该算法可以有效节约网络能耗,同时延长了网络的生命周期.     

链路可靠的无线传感器网络组播路由协议

在无线传感器网络实际应用中,组播正在发挥着越来越重要的作用.但由于能量等多方面的因素,使得为无线传感器网络设计一个有效的组播路由是非常困难的.针对无线传感器网络中节点的能量限制,通过寻求节点间最短路径,提出一种能量有效的链路可靠组播路由协议(RLMR).该协议充分考虑到网络中节点的能耗因素和两节点间的链路可靠性等,通过对这两个因素的综合考虑,让能量较多并且以发送节点更靠近的节点承担更多传输任务的方式,为数据流优化路由选择,均衡无线传感器网络节点的能量消耗,以延长网络的生存时间.仿真结果证明了RLMR的有效性和可靠性.     

无线传感器网络中基于最优转发集的协作式编码传输协议

针对当前大多数据传输协议没有充分利用无线信道的广播特性这一问题,本文提出了基于网络编码的机会路由协议NCOR（Network Coding based Opportunistic Routing protocol）.首先,通过分析网络端到端传输代价,本文提出了最优转发集构造机制以最小化传输代价.此后,NCOR在转发集内执行节点协作式编码传输以保证传输可靠性.最后,理论分析了NCOR的传输可靠性结论.仿真实验表明NCOR可适用于不同的链路环境,且在保证可靠传输的同时,大幅降低了网络能耗.     

无线传感器网络簇间节能路由算法

针对基于分簇网络的无线传感器网络簇间路由协议,让簇首和Sink节点直接通信或通过簇首节点转发数据造成能耗不均,节点过早死亡的缺陷。文中提出一种基于网关节点模型的无线传感器网络簇间路由算法,通过簇头与网关节点、网关节点自身建立虚电路,制定存储转发路由,将数据转发给Sink节点。并引入延时等待机制,增强了簇间信息的融合度,此算法适用于大规模无线传感器网络,有良好的可扩展性。仿真表明在能量节省等性能上与传统簇间路由算法相较有较大提高。     

无线传感器网络中基于协同的机会路由

提出了一种适用于无线传感器网络的基于协同的机会路由协议,协议在结合区域路由、会聚机制和睡眠机制的基础上,使用跨层的方法对无线传感器网络的路由协议进行改进,以增强网络连接随机变化条件下路由协议的顽健性,并以能量有效的方式提高了数据的转发速度.仿真结果表明,在不同节点密度条件下,基于协同的机会路由在数据转发能效方面比非协同的机会路由有很大的提高.     

移动WSNs的能耗区路由

节点的移动对移动无线传感网络(MWSNs)路由设计提出了挑战。为此,提出基于接触时间的能耗区路由(CECA)。CECA路由采用休眠-唤醒机制,降低了节点能耗。CECA路由利用源节点与信宿的位置信息构成圆角矩形区域,且只允许区域内的节点才能参与路由。通过节点移动信息,计算接触时间,并利用接触时间设置定时器,进而通过定时器竞争产生下一跳转发节点。仿真数据表明,CECA路由的通信连通时间及数据包传递率得到有效的增加和提高。     

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。     

基于跨层网络编码感知的无线传感器网络节能路由算法研究

编码感知路由可以发现路由中的网络编码机会,减少数据传输次数,提高网络吞吐量,是近年来路由算法研究的一个热点.当前编码感知路由存在编码条件失效、未考虑节点能量的问题,不适合直接应用于无线传感器网络.本文提出基于跨层网络编码感知的无线传感器网络节能路由算法CAER (Cross layer coding Aware Energy efficient Routing).提出并证明了修正后的网络编码条件,以解决编码条件失效问题.基于跨层思想,将网络编码感知机制与拓扑控制、覆盖控制结合,挖掘潜在编码机会.提出综合考虑节点编码机会、节点能量的跨层综合路由度量CCRM (Cross layer Coding aware Routing Metric).仿真结果表明,相比现有编码感知路由,CAER能够提高网络编码感知准确性,增加网络编码机会数量5%~15%,延长网络生存时间8%~12%.     

一种新的基于部分网络编码的机会路由机制

网络编码能够提升无线网络传输性能,网络中的节点若采用传统的全网络编码,必须等待所有的数据包到达后才能进行解码,而这将造成网络的延迟。通过将部分网络编码和机会路由相结合,提出了一种新的路由协议(ORoPNC),该协议可以降低网络编码延迟,提高网络的稳定性。同时,设计了一种新的转发策略——ETXoEC。在这一策略下,转发节点的选取决定于当前链路状态和节点的剩余能量。仿真结果表明,网络的延迟降低了25%左右,能量消耗也得到了较好的平衡,整个网络的稳定性得到进一步提高。     

WSNs中基于转发区域调整的能效地理路由

针对无线传感网络(WSNs)的数据传输问题,提出基于转发区域调整的能效地理位置路由(FAEG)。FAEG限定了数据包的转发区域,构建候选转发节点集,并从节点集中选择权重大的节点传递数据包;通过节点剩余能量和离目的节点距离信息计算节点权重,使剩余能量大和离目的节点近的节点具有优先传递数据包的资格,提高了路由稳定性。节点遭遇路由空洞时,则调整转发区域,在更广范围内选择传输数据包的节点。仿真结果表明,提出的FAEG降低了能耗,并提高了数据包传递率。     

Balance energy-efficient and real-time with reliable communication protocol for wireless sensor network

In many wireless sensor network applications, it should be considered that how to trade off the inherent conflict between energy efficient communication and desired quality of service such as real-time and reliability of transportation. In this paper, a novel routing protocols named balance energy-efficient and real-time with reliable communication (BERR) for wireless sensor networks (WSNs) are proposed, which considers the joint performances of real-time, energy efficiency and reliability. In BERR, a node, which is preparing to transmit data packets to sink node, estimates the energy cost, hop count value to sink node and reliability using local information gained from neighbor nodes. BERR considers not only each sender’ energy level but also that of its neighbor nodes, so that the better energy conditions a node has, the more probability it will be to be chosen as the next relay node. To enhance real-time delivery, it will choose the node with smaller hop count value to sink node as the possible relay candidate. To improve reliability, it adopts retransmission mechanism. Simulation results show that BERR has better performances in term of energy consumption, network lifetime, reliability and small transmitting delay.     

Energy Efficiency Routing with Node Compromised Resistance in Wireless Sensor Networks

For the energy limited wireless sensor networks, the critical problem is how to achieve the energy efficiency. Many attackers can consume the limited network energy, by the method of capturing some legal nodes then control them to start DoS and flooding attack, which is difficult to be detected by only the classic cryptography based techniques with common routing protocols in wireless sensor networks (WSNs). We argue that under the condition of attacking, existing routing schemes are low energy-efficient and vulnerable to inside attack due to their deterministic nature. To avoid the energy consumption caused by the inside attack initiated by the malicious nodes, this paper proposes a novel energy efficiency routing with node compromised resistance (EENC) based on Ant Colony Optimization. Under our design, each node computes the trust value of its 1-hop neighbors based on their multiple behavior attributes evaluation and builds a trust management by the trust value. By this way, sensor nodes act as router to achieve dynamic and adaptive routing, where the node can select much energy efficiency and faithful forwarding node from its neighbors according to their remaining energy and trust values in the next process of data collection. Simulation results indicate that the established routing can bypass most compromised nodes in the transmission path and EENC has high performance in energy efficiency, which can prolong the network lifetime.     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.     

Secure coverage-preserving node scheduling scheme using energy prediction for wireless sensor networks

With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.     

A novel slot scheduling technique for duty-cycle based data transmission for wireless sensor network

The duty cycling process involves turning a radio into an active and dormant state for conserving energy. It is a promising approach for designing routing protocols for a resource-constrained Wireless Sensor Networks (WSNs). In the duty cycle-based WSNs, the network lifetime is improved and the network transmission is increased as compared to conventional routing protocols. In this study, the active period of the duty cycle is divided into slots that can minimize the idle listening problem. The slot scheduling technique helps determine the most efficient node that uses the active period. The proposed routing protocol uses the opportunistic concept to minimize the sender waiting problem. Therefore, the forwarder set will be selected according to the node's residual active time and energy. Further, the optimum routing path is selected to achieve the minimum forwarding delay from the source to the destination. Simulation analysis reveals that the proposed routing scheme outperforms existing schemes in terms of the average transmission delay, energy consumption, and network throughput.     

无线传感器网络能量高效混合MAC算法

针对无线传感器网络MAC协议中存在的能耗问题,提出了能量高效的无线传感器网络混合MAC(EEH-MAC)算法,采用基于TDMA机制的时槽系数动态调整簇内节点的时槽大小来降低数据的传输时延;同时,对部分不需要数据传输的节点不分配时槽来减少能耗;按簇内节点剩余能量系数形成时槽分配顺序来减少状态转换的能耗;在簇头之间采用CSMA/CA机制的随机分配策略进行通信.仿真结果表明,EEH-MAC协议能有效减少能耗并延长网络生命周期.     

Clustering routing protocol based on improved PSO algorithm in WSN

Aiming at the problem that the location distribution of cluster head nodes filtered by wireless sensor network clustering routing protocol was unbalanced and the data transmission path of forwarding nodes was unreasonable,which would increase the energy consumption of nodes and shorten the network life cycle,a clustering routing protocol based on improved particle swarm optimization algorithm was proposed.In the process of cluster head election,a new fitness function was established by defining the energy factor and position equalization factor of the node,the better candidate cluster head node was evaluated and selected,the position update speed of the candidate cluster head nodes was adjusted by the optimized update learning factor,the local search and speeded up the convergence of the global search was expanded.According to the distance between the forwarding node and the base station,the single-hop or multi-hop transmission mode was adopted,and a multi-hop method was designed based on the minimum spanning tree to select an optimal multi-hop path for the data transmission of the forwarding node.Simulation results show that the clustering routing protocol based on improved particle swarm optimization algorithm can elect cluster head nodes and forwarding nodes with more balanced energy and location,which shortened the communication distance of the network.The energy consumption of nodes is lower and more balanced,effectively extending the network life cycle.     

DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks

Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population.