Implementation of energy efficient circuit design using A* algorithm in embedded network

In wireless sensor network, the routing path plays a prominent role in network resource utilization. Since, the nodes in network are open to physical abuse an effective routing protocol is necessary to improve data reliability in network and to overcome node data link disconnection. In this paper, we propose to implement A*EEDDP (Energy Efficient Distributed Diffusion protocol) to improve data reliability and increase network lifetime. The A* algorithm determines the shortest routing path between source node and destination node. In addition, the routing path determine with respect to parameters such as energy consumed for communication, residual energy of nodes and the time over which the nodes can support the routing path. The combined A*EEDDP implement in testbed and performance evaluate interms of network lifetime, throughput, packet delivery ratio, energy efficiency and end to end delay. The A*EEDDP performs better compared to other algorithm and achieves higher packet delivery ratio of 97%.     

Fuzzy Based Reliable Load Balanced Routing Approach for Ad hoc Sensor Networks

Energy management and packet delivery rate are the important factors in ad hoc networks. It is the major network where nodes share the information without administration. Due to the mobility of nodes, maximum energy is spent on transmission of packets. Mostly energy is wasted on packet dropping and false route discovery. In this research work, Fuzzy Based Reliable Load Balanced Routing Approach (RLRA) is proposed to provide high energy efficiency and more network lifetime using optimal multicast route discovery mechanism. It contains three phases. In first phase, optimal multicast route discovery is initiated to resolve the link failures. In second phase, the link quality is estimated and set to threshold value to meet the requirements of high energy efficiency. In third phase, energy model is shown to obtain total energy of network after transmission of packets. A multicast routing is established Based on path reliability and fault tolerant calculation is done and integrated with multicast routing. The routes can withstand the malicious issues. Fuzzy decision model is integrated with propose protocol to decide the performance of network lifetime. The network simulation tool is used for evaluating the RLRA with existing schemes and performance of RLRA is good compared to others.     

基于博弈论能耗均衡的WSN非均匀分簇路由协议

在无线传感器网络(WSN)的分簇路由算法中,节点间能耗不均容易引发 “能量空洞”现象,影响整个网络的性能。针对这个问题,提出了一种基于博弈论能耗均衡的非均匀分簇路由(GBUC)算法。该算法在分簇阶段,采用非均匀分簇结构,簇的半径由簇头到汇聚节点的距离和剩余能量共同决定,通过调节簇头在簇内通信的能耗和转发数据的能耗来达到能耗的均衡;在簇间通信阶段,通过建立一个以节点剩余能量和链路可靠度为效益函数的博弈模型,利用其纳什均衡的解来寻找联合能耗均衡、链路可靠性的最优传输路径,从而提高网络性能。仿真结果表明:与能量高效的非均匀分簇(EEUC)算法和非均匀分簇节能路由(UCEER)算法相比,GBUC算法在均衡节点能耗、延长网络生命周期等性能方面有显著的提高。     

基于链路可靠性的两跳QoS路由

针对工业无线传感器网络对路由协议的QoS要求，研究了一种基于链路可靠性的两跳QoS路由（Link-Reliability Based Two-Hop Routing for QoS Guarantee in Industrial Wireless Sensor Networks， LRTHQR）.采用两跳速度策略和数据优先级调度策略提高实时性，采用改进的信任评估模型以选择可信路径进行路由，采用基于接收功率的链接概率和数据包重传次数作为衡量链路可靠性的指标，同时采用能够综合考虑节点剩余能量和转发能耗的转发策略，以改善网络寿命.仿真结果显示：与未考虑链路可靠性的NCSRT （NodeCredible Security Routing for IWSN Based on THTR）算法相比， LRTHQR算法在丢包率、时延以及包平均能耗方面有着明显优势；与同样侧重QoS要求的LRTHR （Link-Reliability based Two-Hop Routing）算法相比， LRTHQR算法在截止期错失率、路由开销以及包平均能耗方面有着显著提升.     

Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

Link asymmetry in wireless mesh access networks (WMAN) of Mobile ad-hoc Networks (MANETs) is due mesh routers’ transmission range. It is depicted as significant research challenges that pose during the design of network protocol in wireless networks. Based on the extensive review, it is noted that the substantial link percentage is symmetric, i.e., many links are unidirectional. It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message. Therefore, the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asymmetric links. It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation. Here, a novel Learning-based Dynamic Tree routing (LDTR) model is proposed to improve network performance and delay. For the evaluation of delay measures, asymmetric link, interference, probability of transmission failure is evaluated. The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity. This learning model is a productive way for resolving the routing issues over the network model during uncertainty. The asymmetric path is chosen to achieve exploitation and exploration iteratively. The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem. Here, the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model (DQN), asymmetric MAC model (AMAC), and cooperative asymmetric MAC model (CAMAC) model. The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others. The average energy consumption is 250 J, packet energy consumption is 6.5 J, PRR is 50 bits/sec, 95% PDR, average delay percentage is 20%.     

Energy efficiency analysis of high speed triple-play services in next-generation PON deployments

In this paper, the energy consumption of high speed access services up to 1 Gb/s per customer is estimated for different passive optical network (PON) technologies. While other studies on PON power consumption typically assume a fixed split ratio, we also consider a greenfield approach, where the split ratio can be optimized for each technology, taking full advantage of its capacity and reach. The split ratio optimization takes into account Quality of Service (QoS) in terms of bandwidth availability and packet loss for triple-play services (voice, television and Internet). This paper includes an in-depth discussion of our split ratio dimensioning approach and our power consumption model for an optical access network in a major city. The obtained results show that statistical gain provided by dynamic bandwidth allocation as well as power splitting ratio optimization in PONs are key factors for achieving energy efficiency. For access rates up to 900 Mb/s, XG-PON1 turns out to be the most energy efficient option. For higher access rates up to 1 Gb/s, the optimal technology depends on split ratio restrictions. If an existing optical distribution network (ODN) with split ratio 1:64 is used, XG-PON1 remains the most energy efficient technology. If higher split ratios up to 1:256 can be achieved, TWDM PON becomes the most energy efficient solution for access rates up to 1 Gb/s.     

采用半贪心优化的节点非均匀分布路由协议

为避免无线传感器网络中因节点能耗不均衡而产生的能量空洞现象,延长网络生命周期,提出采用半贪心优化的节点非均匀分布路由协议。首先在网络监测区域分层的基础上,计算各层感知数据转发能耗,根据各层网络能耗比例和监测区域覆盖要求,设计了密度递减的节点部署模型;然后基于两跳通信的贪心范围,提出两跳能耗代价估计函数,改进半贪心算法;在簇间多跳通信阶段,利用优化的半贪心算法求解簇头到基站的最优转发路径。仿真实验表明,与现有的几种路由协议相比,新协议能够均衡各层网络节点能耗,延长网络生命周期,有效避免能量空洞现象。     

基于非均匀分簇机制的ZigBee混合路由算法

针对现有ZigBee网络路由算法存在节点能量消耗不均衡问题,在树路由算法与无线自组网按需距离矢量路由改进(AODVjr)算法的基础上,提出一种基于非均匀分簇机制的ZigBee混合路由算法。该算法将网络分成若干个非均匀的逻辑簇,使距离协调器越近的簇规模越小,从而减少转发任务,使得能量消耗均衡。在分簇的基础上,将节点之间的传输分为簇内传输与簇间传输。簇内传输采用基于邻居表的树路由算法;簇间传输在基于树路由算法无效的情况下,采用AODVjr算法,找到两个簇首之间的较短路径;同时规定只有簇首节点和网关节点才能广播请求分组(RREQ),可以减少冗余的RREQ分组。仿真结果表明,该算法能有效推迟死亡节点出现的时间,延长网络的生存周期,达到提高网络性能的目的。     

Study on the algorithm for smart community sensor network routing with adaptive optimization via cluster head election

To reduce the uneven energy consumption for the data transmission and extend network life of intelligent community sensor network, an adaptive routing optimized algorithm for intelligent community sensor networks with cluster head election is proposed. In this algorithm, a three-dimensional clustering method adapted to the structure of intelligent community sensor network is proposed. The three-dimensional clustering method uses the cluster head election mechanism based on minimizing the total transmission loss to optimize the energy of the intelligent community sensor network. Second, an adaptive ant colony propagation method is proposed to solve the problem of intercluster data propagation after clustering. With the best path finding algorithm of ant colony algorithm, energy balance routing with lower energy loss and lower packet error rate is proposed. Finally, the simulation results show that the algorithm has better performance in reducing energy consumption and delay, improving transmission efficiency and node survival time.     

基于蚁群算法的能量均衡多路径路由算法的研究

本文对现有的基于蚁群算法的路由协议进行了深入的研究,并提出了一种基于蚁群算法的能量均衡多路径路由算法（ABMR）,该算法在蚂蚁数据包结构、信息素更新公式、信息素更新方式和多路径建立机制等方面作了改进。在信息素更新公式中综合考虑了路径的能量消耗速度、路径上剩余的最小能量、距离目的节点Sink的跳数和路径的拥塞程度。在信息素更新方式上,改变传统的信息素的累加更新方式,采用彻底的链路信息素更新方式,使网络负载更加均衡。ABMR的多路径生成机制可以在源节点和目的节点间更加合理的建立起多条路径。数据发送阶段,概率路由选择策略使数据流量均衡的注入无线传感器网络。本文在NS-2仿真环境下对ABMR协议进行仿真实验,仿真结果表明,和传统协议比较, ABMR协议在能量有效性、数据分组投递率以及分组端到端时延等方面都有一定的提高。     

Energy Efficient Gravitational Search Algorithm and Fuzzy Based Clustering With Hop Count Based Routing For Wireless Sensor Network

In Wireless sensor networks, energy efficiency is the significant attribute to be improved. Clustering is the major technique to enhance energy efficiency. Using this technique, sensor nodes in the network region are grouped as several clusters and cluster head (CH) is chosen for each and every cluster. This CH gathers data packet from the non-CH members inside the cluster and forwards the collected data packet to the base station. However, the CH may drain its energy after a number of transmissions. So, we present the Energy efficient Gravitational search algorithm (GSA) and Fuzzy based clustering with Hop count based routing for WSN in this paper. Initially, CH is selected using Gravitational Search Algorithm (GSA), based on its weight sensor nodes are joined to the CH and thus cluster is formed. Among the selected CHs in the network, supercluster head (SCH) is selected using a fuzzy inference system (FIS). This selected SCH gathers the data packet from all CHs and forwards it to the sink or base station. For transmission, the efficient route is established based on the hop count of the sensor nodes. Simulation results show that the performance of our proposed approach is superior to the existing work in terms of delivery ratio and energy efficiency.

     

负载均衡的水声传感器网络多跳非均匀分簇路由协议

针对现有水声传感器网络分簇路由协议在簇头选举阶段和数据传输阶段中的不足,设计一种负载均衡的多跳非均匀分簇路由协议(load-balanced multi-hop unequal clustering routing protocol,LBMUC)。该协议基于节点的剩余能量及相对距离,计算节点竞争半径和节点综合属性值,改进优化簇头选举,使得簇头节点分布更加合理,并得以随着剩余能量的变化自适应的调整簇的规模,有效均衡节点的能量消耗;在建立簇间多跳路由阶段,综合考虑节点剩余能量、位置及相邻簇的规模对路由选择的影响,引入中继节点代价函数选择最优中继节点,均衡节点能耗,延长网络生命周期,降低网络丢包率,提高网络性能。仿真实验结果表明,LBMUC协议均衡了节点能耗,有效延长了网络生命周期,降低了数据丢包率。     

基于网络效用最大化与冲突避免的无线传感器网络MAC协议

针对周期汇报型无线传感器网络(WSN)中的无线信号冲突和能量利用效率问题,提出了一种基于网络效用最大化与冲突避免的媒体访问控制(UM-MAC)协议。该协议基于时分多路复用(TDMA)调度机制,将效用模型引入无冲突的节点工作时隙分配过程中,把链路可靠性、网络能耗归纳到一个统一的效用优化框架中;进而提出了一个启发式算法,使网络能够快速找到一个基于网络效用最大化与冲突避免的节点工作时隙调度方案。将UM-MAC协议与S-MAC协议和冲突避免MAC(CA-MAC)协议进行比较,在不同节点数量的网络环境中,UM-MAC获得的网络效用较大,平均数据包成功发送率较高,生命周期介于S-MAC与CA-MAC之间,在不同的网络负载下所有节点发数据包到汇聚节点的平均时延有所增加。仿真实验结果表明:UM-MAC协议较好地解决了冲突干扰问题,提高了网络的数据包成功发送率和能量利用效率等性能;在低网络负载时,TDMA类协议的性能并不比竞争类协议好。     

基于滑动缓存的WSN可靠协议及其能耗分析

数据如何以较低的能耗进行可靠传输是无线传感器网络中数据采集亟需解决的问题。基于此,提出一种缓存位置滑动调整的可靠传输协议,该协议基于通信的中间节点缓存数据包,按照通信距离将链路上的节点划分为近源节点和近汇聚节点,根据链路质量动态调整缓存数据包的节点区域,数据包在相应节点区域的缓存呈正态分布。NS2仿真结果与基于马尔科夫链能耗分析结果表明,该协议中数据包的传输时延小于HHRA协议,吞吐量有较大程度的提高。     

一种面向无线传感网络的AODV改进路由协议

为了提高无线传感网络的数据传输的稳定性和网络能量利用率,提出基于路径稳定和路径能量的改进AODV路由(An Improved AODV Routing based on Stability and Energy of Path, I-AODV-SE)。I-AODV-SE协议以按需距离矢量(Ad Hoc On-demand Distance Vector,AODV)为基础,对其路由决策机制进行改进。首先,I-AODV-SE协议先计算邻居变化率,再估计路径稳定性,然后,再计算路径能量,最后,基于路径稳定和路径能量计算路径权重,并择优选择权重小的路径传输数据。实验数据表明,提出的I-AODV-SE协议提升了网络生存时间和数据包传递率     

无线传感器网络中确保端到端传输质量的自适应调制缩放技术

在满足数据收集任务的时延要求及可靠性要求的前提下最小化能量消耗是传感嚣网络设计中的一个关键问题。选取不同的调制级数(即调制时的星座图大小,每符号位数)可以获得不同程度的能量节省,但引入不同程度的时延的同时也会造成不同程度的丢包。本文提出了一种优化模型在满足数据收集任务的时延要求及可靠性要求的前提下,最优选取各节点的调制级数以最小化网络能耗延长网络生命期。并在此基础之上提出了一个集中式控制算法以根据网络状况自适应地调节各节点的调制级数。实验表明本算法在所考查的各种网络环境下都能明显减少能耗,可以用该模型来确定时延及丢包率对能耗影响的敏感区。另外我们发现,如果将节点的服务率设置为与节点的包到达率近似成比例,在大多数情况下都能够获得好的节能效果。     

结合相对熵和多跳转发路由的改进WSN节能策略

目前,基于低功耗自适应集簇分层型协议(LEACH)的改进协议大多是从簇头选举、簇的分布、路径选择等方面入手,数据之间的冗余性考虑不够。提出了一种结合相对信息熵的改进LEACH协议(LEACH-CIE),结合相对熵模型,计算节点相邻两个周期数据概率分布的相对熵值,再与阈值进行比较,以此判断数据的冗余度,通过拒绝冗余数据的传输,达到降低网络能耗的目的。在数据发送阶段,考虑通信距离、能耗比等因素,提出一种兼顾自身剩余能量的多跳转发路由(MFRCRE),优化节点转发条件,均衡网络各节点的能量消耗速率。实验结果表明,该方法可以有效地降低并均衡网络节点的能耗以延长网络生存周期。     

基于能量最小路径的WSN分簇算法

为延长无线传感器网络(WSN)的生存时间,提出一种基于能量最小路径的WSN分簇算法。参照节点的剩余能量与全网动态平均能量的比例关系,决定节点是否成为簇头,并结合簇头间的能量最小路径,实现全网的能耗均衡。仿真结果显示,该算法在网络生存时间、数据吞吐量和网络能耗等指标上性能较优。     

基于多目标优化的WSN簇首选择算法

分簇思想可以很好的用于优化路由算法,现有的分簇算法簇首轮换选举大多数只是从簇首和基站之间距离、节点密集度、剩余能量、节点位置等指标来进行改进,没有考虑候选簇头距离各个簇首的平均距离。簇间转发数据包会消耗大量能量,是影响网络性能的一个重要因素。针对目前簇首轮换选举算法存在的不足,提出了一种综合考虑簇内和簇间两个优化目标的算法,此种算法本文简称为DEDS。建立了候选节点剩余能量、候选簇头节点距各个簇首节点平均距离等多目标概率模型作为簇首轮换选择依据。通过在NS2仿真平台上验证了该算法在时延、分组递交率、能耗、稳定性等网络性能优于其它分簇算法。     

Performance evaluation of tree based data aggregation for real time indoor environment monitoring using wireless sensor network

A fundamental challenge in the implementation of Wireless Sensor Network is to reduce packet loss when channel bandwidth is limited and the energy of sensor is finite. In this paper, a suitable solution is provided for controlling packet loss through tree-based data aggregation and routing. From this perspective, a binary tree-based data aggregation and routing has been proposed which can reduce packet loss and energy dissipation which occurs due to unsuccessful packet delivery. Simulation result using NS-2 shows that binary tree-based data aggregation reduces packet loss up to 63.1% compared to cluster based protocol LEACH, up to 26.5% compared to chain based protocol PEGASIS. Moreover binary tree based data aggregation out performs both LEACH and PEGASIS with respect to the parameters end to end delay, packet delivery ratio and total energy consumption. Our proposed architecture integrates sensor network, mobile device, Access point and Cloud services as a single unit for real time monitoring. An experimental analysis of the proposed approach for indoor environment monitoring is carried out in the university laboratory to evaluate the performance in terms of time and energy consumption.