Energy efficient and QoS based routing protocol for wireless sensor networks

The increasing demand for real-time applications in Wireless Sensor Networks (WSNs) has made the Quality of Service (QoS) based communication protocols an interesting and hot research topic. Satisfying Quality of Service (QoS) requirements (e.g. bandwidth and delay constraints) for the different QoS based applications of WSNs raises significant challenges. More precisely, the networking protocols need to cope up with energy constraints, while providing precise QoS guarantee. Therefore, enabling QoS applications in sensor networks requires energy and QoS awareness in different layers of the protocol stack. In many of these applications (such as multimedia applications, or real-time and mission critical applications), the network traffic is mixed of delay sensitive and delay tolerant traffic. Hence, QoS routing becomes an important issue. In this paper, we propose an Energy Efficient and QoS aware multipath routing protocol (abbreviated shortly as EQSR) that maximizes the network lifetime through balancing energy consumption across multiple nodes, uses the concept of service differentiation to allow delay sensitive traffic to reach the sink node within an acceptable delay, reduces the end to end delay through spreading out the traffic across multiple paths, and increases the throughput through introducing data redundancy. EQSR uses the residual energy, node available buffer size, and Signal-to-Noise Ratio (SNR) to predict the best next hop through the paths construction phase. Based on the concept of service differentiation, EQSR protocol employs a queuing model to handle both real-time and non-real-time traffic.     

无线传感器网络QoS路由研究进展*

传统网络中的服务质量(quality of service,QoS)路由协议很难直接有效地应用到无线传感器网络中,因此人们针对无线传感器网络提出了一些新的QoS路由协议。首先探讨了无线传感器网络中QoS路由协议的一些特点,分析了设计QoS路由协议所面临的挑战;然后着重分析了当前提出的一些QoS路由协议的QoS机制、特点以及优缺点,并对这些路由协议进行了分类和比较;最后总结了QoS路由协议未来的研究策略和发展趋势。     

IEEMARP- a novel energy efficient multipath routing protocol based on ant Colony optimization (ACO) for dynamic sensor networks

In the past few years, research and development in Wireless Sensor networks (WSNs) have gained momentum due to its numerous applications in agriculture, industrial manufacturing, military surveillance, environmental monitoring, consumer electronics, medical & healthcare, disaster recovery operations etc. Dynamic WSNs offer a robust blend of distributed sensing, computing and communication. Dynamic sensor networks are characterized by large scale deployment, dynamic and unstructured topology, power limitations, less memory and limited computational capabilities. Sensor nodes deployed in real-time environment’s for sensing data have power-limitations which hampers the overall performance of WSNs. So, the only obvious solution is to propose an energy efficient routing protocol to optimize WSN real-time performance. Different specialists have proposed various directing conventions for WSNs dependent on Fuzzy Logic, Genetic Algorithms, Meta-Heuristics, and other improvement strategies. However, every solution suggested till date has its advantages and limitations. In this paper, our primary objective is to utilize Swarm-Intelligence based approach i.e. “Ant Colony Optimization (ACO)”, for routing protocol development. Ant colony optimization (ACO) based approach gives optimal solution in terms of efficient routing path determination, energy efficiency and delivering high performance in terms of packet delivery and throughput. In this paper, we propose a novel energy efficient ACO based multipath routing protocol for WSN i.e. IEEMARP (Improvised Energy Efficient Multipath ACO based Routing Protocol). The proposed protocol works in three phases (Neighbor Discovery via Link Knowledge, Packet Transmission via exponentially weighted moving average method and ACKR packet delivery for assuring end-to-end delivery. To validate the performance of the protocol proposed, extensive simulations were conducted using NS-2.35-allinone simulator on diverse parameters like (PDR), throughput, routing overhead, energy consumption and end-to-end delay. In addition to this, the performance of protocol is compared with traditional routing protocols like Basic ACO, DSDV and DSR and other ACO based WSN protocols like ACEAMR, AntChain, EMCBR, IACR, AntHQSeN, FACOR and ANTALG. Simulation based results, clearly states that as compared to Basic ACO, DSDV and DSR, the performance of WSN network is improvised to around 10% in all performance metrics via IEEMARP routing protocol. And as compared to ACEAMR, AntChain, EMCBR and IACR, IEEMARP performs 20% better in overall functionality and almost 10–12% better as compared to AntHQSeN, FACOR, ANTLAG routing protocols in varied WSN scenarios. It is also observed that IEEMARP protocol is highly efficient in TCP packet transmission from source to destination node.

     

基于熵权系数法的无线传感器网络自适应QoS路由算法

针对无线传感器网络中不同业务对服务质量（QoS）指标的不同要求,以及QoS指标在网络运行过程中实时变化的特点,提出一种基于熵权系数法的自适应QoS路由（EAQR）算法。算法将路由建立过程抽象成多指标加权评分的问题,选取节点负载、平均能量势、通信时延作为QoS评价指标,采用熵权系数法自适应地确定指标的权重,选择最优节点转发数据。仿真实验显示,与有序分配路由(SAR)、能量感知QoS路由(EQR)算法相比,EAQR算法可以有效降低网络平均端到端延迟,减少丢包率,延长网络寿命。     

FAMACROW: Fuzzy and ant colony optimization based combined mac,routing, and unequal clustering cross-layer protocol for wireless sensor networks

This paper presents Fuzzy and Ant Colony Optimization Based Combined MAC, Routing, and Unequal Clustering Cross-Layer Protocol for Wireless Sensor Networks (FAMACROW) consisting of several nodes that send sensed data to a Master Station. FAMACROW incorporates cluster head selection, clustering, and inter-cluster routing protocols. FAMACROW uses fuzzy logic with residual energy, number of neighboring nodes, and quality of communication link as input variables for cluster head selection. To avoid hot spots problem, FAMACROW uses an unequal clustering mechanism with clusters closer to MS having smaller sizes than those far from it. FAMACROW uses Ant Colony Optimization based technique for reliable and energy-efficient inter-cluster multi-hop routing from cluster heads to MS. The inter-cluster routing protocol decides relay node considering its: (i) distance from current cluster head and that from MS (for energy-efficient inter-cluster communication), (ii) residual energy (for energy distribution across the network), (iii) queue length (for congestion control), (iv) delivery likelihood (for reliable communication). A comparative analysis of FAMACROW with Unequal Cluster Based Routing [33], Unequal Layered Clustering Approach [43], Energy Aware Unequal Clustering using Fuzzy logic [37] and Improved Fuzzy Unequal Clustering [35] shows that FAMACROW is 41% more energy-efficient, has 75–88% more network lifetime and sends 82% more packets compared to Improved Fuzzy Unequal Clustering protocol.     

基于蚁群优化的无线传感器网络最适路由算法

如何在资源有限的条件下进行实时、高效的数据路由是无线传感器网络的研究热点之一。针对不同应用设计目标的差异性问题,提出一种基于改进蚁群算法的最适路由选择算法。因设计目标的不同,引入一个新的路由选择度量,兼顾实时性、能源效率和负载均衡等方面,并结合蚁群算法的寻优特点,对无线传感器网络最适路由选择问题进行优化。仿真结果表明,最适路由选择算法能够在满足不同设计目标的前提下,延长网络寿命,实现无线传感器网络实时、高效的路由。     

基于遗传算法的WSNs多路径路由优化

对WSNs的拓扑结构进行分析,建立其路由网络模型,结合遗传算法基本原理,提出了一种求解WSNs最优多路径路由算法。该算法采用可变长度染色体编码,采取选择、交叉和变异操作,充分利用基站的信息资源和强大功能,全局优化了WSNs多路径路由。仿真结果表明,该优化机制有效延长了WSNs的生命周期,改善了网络性能。     

Energy efficient teaching-learning-based optimization for the discrete routing problem in wireless sensor networks

Wireless sensor networks (WSNs) are composed of sensor nodes, having limited energy resources and low processing capability. Accordingly, major challenges are involved in WSNs Routing. Thus, in many use cases, routing is considered as an NP-hard optimization problem. Many routing protocols are based on metaheuristics, such as Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). Despite the fact that metaheuristics have provided elegant solutions, they still suffer from complexity concerns and difficulty of parameter tuning. In this paper, we propose a new routing approach based on Teaching Learning Based Optimization (TLBO) which is a recent and robust method, consisting on two essential phases: Teacher and Learner. As TLBO was proposed for continuous optimization problems, this work presents the first use of TLBO for the discrete problem of WSN routing. The approach is well founded theoretically as well as detailed algorithmically. Experimental results show that our approach allows obtaining lower energy consumption which leads to a better WSN lifetime. Our method is also compared to some typical routing methods; PSO approach, advanced ACO approach, Improved Harmony based approach (IHSBEER) and Ad-hoc On-demand Distance Vector (AODV) routing protocol, to illustrate TLBO’s routing efficiency.     

用PSO优化基于QoS的WSN路由协议

在过去的10年中,提供服务质量(QoS)保证的路由协议很好的用在了有线网络中,随着无线传感网络(WSN)的广泛使用,就需要考虑如何在无线传感网络中实现QoS的效率.很多QoS度量值都需要被考虑,如数据包时延、带宽效率、能量消耗等.同时QoS也受路由的影响,由于路由解空间随着网络的规模变大而呈指数级的增长,研究路由协议算法的效率就成为一个必然.在研究了智能粒子群最优算法(PSO)后,提出了一个基于PSO的路由算法,不仅考虑了QoS的需求同时也有一个不错的搜索能力.仿真结果表明,与一些典型QoS常规机制比较基于粒子群最优路由算法是有效的.     

Opportunistic routing in wireless sensor networks powered by ambient energy harvesting

Energy consumption is an important issue in the design of wireless sensor networks (WSNs) which typically rely on portable energy sources like batteries for power. Recent advances in ambient energy harvesting technologies have made it possible for sensor nodes to be powered by ambient energy entirely without the use of batteries. However, since the energy harvesting process is stochastic, exact sleep-and-wakeup schedules cannot be determined in WSNs Powered solely using Ambient Energy Harvesters (WSN–HEAP). Therefore, many existing WSN routing protocols cannot be used in WSN–HEAP. In this paper, we design an opportunistic routing protocol (EHOR) for multi-hop WSN–HEAP. Unlike traditional opportunistic routing protocols like ExOR or MORE, EHOR takes into account energy constraints because nodes have to shut down to recharge once their energy are depleted. Furthermore, since the rate of charging is dependent on environmental factors, the exact identities of nodes that are awake cannot be determined in advance. Therefore, choosing an optimal forwarder is another challenge in EHOR. We use a regioning approach to achieve this goal. Using extensive simulations incorporating experimental results from the characterization of different types of energy harvesters, we evaluate EHOR and the results show that EHOR increases goodput and efficiency compared to traditional opportunistic routing protocols and other non-opportunistic routing protocols suited for WSN–HEAP.     

面向环境监测的WSN中基于定向传输的高能效路由算法

能耗问题是WSN在环境监测中发展与应用中的主要限制因素,而路由协议成为解决Qos(即能耗、网络生命周期、网络可扩展性和包开销等)相关问题的研究热点.动态路由协议适用于能量密度较小的场景,但当节点模式从活跃转睡眠时,数据包需要等到下一个发送时间点才能发送,从而降低网络能效、增加数据包的端到端时延,进而增加了网络能耗.为了解决该问题,本文提出了一种基于PEGASIS与DSR联合优化的路由协议JPDORP(Joint PEGASIS-DSR Optimized Routing Protocol),JPDORP有PEGASIS和DSR协议的共同特征,同时也融合运用了遗传算法和细菌觅食优化方法以确定能效最优的传输路径.仿真结果表明,算法在误比特率、时延、能耗、吞吐量方面均有增益,能够提供更好的Qos保障和延长网络生命周期.     

移动传感网中基于本地信息的机会路由策略

在考虑节点信道质量、移动方向和速率、剩余能耗等本地信息的基础上,在移动传感网中提出了基于本地信息的机会路由策略(OR LI)。该策略采用能在一定程度上反映信道质量的接收信号强度指示值对数 常态分布模型建立节点机会概率值;引入移动速率和方向反映节点的移动性;使用节点的剩余能耗反映节点的剩余使用寿命,实现机会路由,并通过候选节点的优选序号来确定候选点的侦听转发时间以避免报文重发。与机会路由策略ExOR和OB比,新策略更适合移动传感网,具有传输有效性高、能耗低等优点。     

基于反馈可信度的可信机会路由转发模型

传统Ad Hoc等先决路由机制不再适合无线Mesh网络。相反,基于后择路由机制的机会路由已经获得越来越多的应用。机会路由中的转发候选集可有效增加无线Mesh网络吞吐量和降低重传数;但是,机会路由也正遭受安全问题困扰。针对节点间的共谋攻击行为,提出一种基于反馈可信度的信任模型,并结合到机会路由中,防止共谋节点加入机会路由转发候选集。建立一种基于反馈可信度的可信机会路由转发模型（简称FCTOR）。仿真实验表明,该模型较经典的ExOR协议可以有效抑制典型恶意节点,尤其面对共谋攻击行为时表现出良好的性能。     

FSE2R: An Improved Collision-Avoidance-based Energy Efficient Route Selection Protocol in USN

The 3D Underwater Sensor Network (USNs) has become the most optimistic medium for tracking and monitoring underwater environment. Energy and collision are two most critical factors in USNs for both sparse and dense regions. Due to harsh ocean environment, it is a challenge to design a reliable energy efficient with collision free protocol. Diversity in link qualities may cause collision and frequent communication lead to energy loss; that effects the network performance. To overcome these challenges a novel protocol Forwarder Selection Energy Efficient Routing (FSE2R) is proposed. Our proposal’s key idea is based on computation of node distance from the sink, Residual Energy (RE) of each node and Signal to Interference Noise Ratio (SINR). The node distance from sink and RE is computed for reliable forwarder node selection and SINR is used for analysis of collision. The novel proposal compares with existing protocols like H2AB, DEEP, and E2LR to achieve Quality of Service (QoS) in terms of throughput, packet delivery ratio and energy consumption. The comparative analysis shows that FSE2R gives on an average 30% less energy consumption, 24.62% better PDR and 48.31% less end-to-end delay compared to other protocols.     

无线传感器网络路由协议安全研究

路由算法是无线传感器网络（WirdessSensorNetworks,WSNs）感知信息传输和汇聚的基础,作为多跳网络,WSNs有其自身的特点,特别是在路由的安全性方面,需要进行深入的研究。文章对近年来的WSNs路由协议安全进行了分析和总结,首先介绍WSNs安全路由的基本概念,接着对路由协议易受到的安全威胁和攻击进行了分类对比,最后对WSNs中几种典型路由协议的安全陛进行了描述和分析。     

Coordinated opportunistic routing protocol for wireless mesh networks

Opportunistic routing is an emerging research area in Wireless Mesh Networks (WMNs), that exploits the broadcast nature of wireless networks to find the optimal routing solution that maximizes throughput and minimizes packet loss. Opportunistic routing protocols mainly suffer from computational overheads, as most of the protocols try to find the best next forwarding node. In this paper we address the key issue of computational overhead by designing new routing technique without using pre-selected list of potential forwarders. We propose a novel opportunistic routing technique named, Coordinated Opportunistic Routing Protocol for WMNs (CORP-M). We compare CORP-M with well-known protocols, such as AODV, OLSR, and ROMER based on throughput, delivery ratio, and average end-to-end delay. Simulation results show that CORP-M, gives average throughput increase upto 32%, and increase in delivery ratio (from 10% to 20%). We also analyze the performance of CORP-M and ROMER based on various parameters, such as duplicate transmissions and network collisions, by analysis depicts that CORP-M reduces duplicate transmissions upto 70% and network collisions upto 30%.     

无线传感器网络能量最优的QoS路由发现方法

针对无线传感器网络的动态网络环境和节点能源受限,且通常无法补充的能源特性等不利因素,提出了一种可以实现能量最优的QoS路由发现方法。该方法利用节点选择机制和节点邻居表来建立满足QoS带宽需求的可供选择的节点集合,从而减少路由发现过程中的所要监测的节点数量。所提方法还构建了无线传感器网络的能量评价模型和节点能耗权重模型,使用遗传算法从可供选择的节点集合中构建可实现能量最优的QoS路由,自适应的实现对节点调度,从而延长无线传感器网络的寿命。通过实验仿真与分析,给出了实现无线传感器网络能量最优的遗传算法控制参数的选择区间。实验结果显示:该方法对无线传感器网络具有更好的适应性,且能保证其有更长的寿命。     

一种多径QoS的MANET路由协议

近年来,QoS(Quality of Service)路由问题已成为Ad hoc网络的一个研究热点.本文提出一种按需的多径QoS路由协议-MTBP(Multipath Ticket Based Probing Routing Protocol).该协议能够在源节点和目的节点间找到多条满足QoS要求的路由.与传统路由协议相比,本协议通过"票"限制洪泛,在链路断裂时采用备份路由及时恢复数据分组的传递,具有多路径传输、负载平衡、控制开销小等特点,能很好的适应无线移动自组织网中网络拓扑结构变化迅速,节点间移动速率快的特性.     

基于群智能算法无线传感网络分簇路由协议

无线传感网络路由协议——LEACH协议(Low Energy Adaptive Clustering Hierarchy)是一种经典的分簇路由协议,LEACH协议相比其他平面路由协议生命周期提高15%以上。然而LEACH协议还是存在不少使能耗过大的缺陷,为改进LEACH协议这些缺陷本文提出了一种节能高效的基于群智能算法的智能分簇路由协议SI-CRP协议(Swarm Intelligence-Clustering Routing Protocol)。     

Ant based Pareto optimal solution for QoS aware energy efficient multicast in wireless networks

Most of the group communication technologies support real-time multimedia applications such as video conferencing and distributed gaming. These applications require quality-of-service (QoS) aware multicast routing protocol to deliver the same data stream to a predefined group of receivers. Since nodes in wireless networks are severely energy constrained due to finite battery source, hence it is of paramount importance that QoS aware multicast routing protocol be energy efficient. Transmission power control is one of the methods used to save energy. In this method, the nodes dynamically adjust the transmission power so that energy consumption in the tree is minimized. However, reduction in the transmission power increases the number of forwarding nodes in the multicast tree. This negatively impacts the QoS in terms of propagation delay, delay jitter, and packet loss etc. In wireless networks, there is a trade-off between the energy consumption and the QoS guarantees provided by the network. We unify these requirements into a multiobjective framework referred to as Energy Efficient QoS Multicast Routing (E²QoSMR). The goal is to simultaneously optimize the total power consumption and the QoS parameters in the multicast tree. We extend two algorithms based on metaphor of swarm intelligence for finding an energy efficient multicast tree satisfying the QoS guarantees. Extensive simulations have been conducted to validate the correctness and efficiency of the algorithms. The simulation result of the algorithms is compared with the nondominated sorting genetic algorithm, NSGA-III. The experimental results are consolidated by statistical analyses that demonstrate the ability of the algorithms to generate the Pareto optimal solution set.