An efficient routing algorithm to preserve k-coverage in wireless sensor networks

One of the major challenges in the area of wireless sensor networks is simultaneously reducing energy consumption and increasing network lifetime. Efficient routing algorithms have received considerable attention in previous studies for achieving the required efficiency, but these methods do not pay close attention to coverage, which is one of the most important Quality of Service parameters in wireless sensor networks. Suitable route selection for transferring information received from the environment to the sink plays crucial role in the network lifetime. The proposed method tries to select an efficient route for transferring the information. This paper reviews efficient routing algorithms for preserving k-coverage in a sensor network and then proposes an effective technique for preserving k-coverage and the reliability of data with logical fault tolerance. It is assumed that the network nodes are aware of their residual energy and that of their neighbors. Sensors are first categorized into two groups, coverage and communicative nodes, and some are then re-categorized as clustering and dynamic nodes. Simulation results show that the proposed method provides greater efficiency energy consumption.     

Fuzzy random multi-objective optimization based routing for wireless sensor networks

Wireless sensor networks are deployed in complex and uncertain environments, and multiple objectives of routing algorithms are expected to be optimal. However, routing algorithms based on deterministic single objective optimization may not flexibly meet the above needs of applications. This paper adopts fuzzy random optimization and multi-objective optimization, introduces fuzzy random variables to describe both fuzziness and randomness of link delay, link reliability and nodes’ residual energy, and proposes a routing model based on fuzzy random expected value and standard deviation model. A hybrid routing algorithm based on fuzzy random multi-objective optimization is designed, which embeds fuzzy random simulation into genetic algorithm with Pareto optimal solution. Simulation results show that the presented algorithm, by adjusting the parameters of fuzzy random variables for depicting both fuzziness and randomness, achieves a longer lifetime and wider performances of delay, latency jitter, reliability, communication interference, energy and balanced energy distribution. Therefore, the presented algorithm can meet different application needs of the cluster head network in the two-tiered wireless sensor networks.     

无线传感器网络中能量有效自适应路由算法研究

针对无线传感器网络寿命最大化问题,基于无线传感器节点能耗分布特点和数据传输能耗模型,建立无线传感器网络生存周期的数学优化模型,并针对最小能耗路由的能耗不均衡问题和能量均衡路由的能耗开销问题,综合考虑网络中节点的剩余能量和节点间发送数据的能耗,提出一个适合无线多跳传感器网络的自适应路由算法。仿真结果表明,提出的路由算法能充分地利用有限的能量资源,较大地延长网络生存周期。     

Using artificial intelligence in routing schemes for wireless networks

For the latest 10 years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well-known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes.     

无线传感器网络中能量有效自适应路由算法研究

针对无线传感器网络寿命最大化问题,基于无线传感器节点能耗分布特点和数据传输能耗模型,建立无线传感器网络生存周期的数学优化模型,并针对最小能耗路由的能耗不均衡问题和能量均衡路由的能耗开销问题,综合考虑网络中节点的剩余能量和节点间发送数据的能耗,提出一个适合无线多跳传感器网络的自适应路由算法。仿真结果表明,提出的路由算法能充分地利用有限的能量资源,较大地延长网络生存周期。     

无线传感器/执行器网络中能量有效的实时分簇路由协议

无线传感器/执行器网络(WSANs)主要应用于自动控制领域,实时性问题是其面临的首要挑战.根据实际环境中的节点部署情况,建立了系统模型;研究了分簇策略与功率控制技术对于自组织网络实时性的影响,提出了一种可适用于WSANs的能量有效的实时分簇路由协议--RECRP协议.该协议采用二级成簇策略使网络中的各类节点稳定分簇.分簇后的各类节点具有不同发射功率,利用执行器节点的强大通信能力有效降低网络延时.采用能量有效性算法使网络中的传感器节点轮换担任簇首,从而使网络能量均匀消耗,延长网络的生存时间.实验结果证明,在WSANs中RECRP协议可使网络稳定分簇,并且在网络的实时性与能量有效性方面与现有典型路由协议相比具有更优越的性能.     

Energy-efficient topology control algorithm for maximizing network lifetime in wireless sensor networks with mobile sink

Uneven energy consumption is an inherent problem in wireless sensor networks characterized by multi-hop routing and many-to-one traffic pattern. Such unbalanced energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of prolonging network lifetime in large-scale wireless sensor networks where a mobile sink gathers data periodically along the predefined path and each sensor node uploads its data to the mobile sink over a multi-hop communication path. By using greedy policy and dynamic programming, we propose a heuristic topology control algorithm with time complexity O(n(m + n log n)), where n and m are the number of nodes and edges in the network, respectively, and further discuss how to refine our algorithm to satisfy practical requirements such as distributed computing and transmission timeliness. Theoretical analysis and experimental results show that our algorithm is superior to several earlier algorithms for extending network lifetime.     

能量捕获无线传感网的吞吐量最大化路由

能量捕获无线传感器网络(EH-WSNs)具有从环境中捕获能量的能力,可以无限期持续工作,因此具有非常广泛的应用前景。目前已有的大多数EH-WSNs路由方案往往侧重于如何有效地节能,而吞吐量作为EH-WSNs重要的性能指标之一却几乎没有得到考虑。首先建模出EH-WSNs端到端吞吐量最大化路由问题,为 深入了解该问题 提供理论基础,然后提出了一种EH-WSNs端到端吞吐量最大化路由方案。相比最小跳数路由方案,本路由方案能显著提高数据流的端到端吞吐量。     

一种带有能量自补给节点的异构传感器网络分簇路由算法

针对现有无线传感器网络分簇路由算法的网络生命周期短、能量消耗不均衡等问题,结合节点的能量采集技术,提出了一种带有能量自补给节点的异构传感器网络分簇路由算法。考虑到实际环境中节点能量补给不稳定,根据节点的剩余能量和当前能量自补给状态,设计了能量均衡的簇头选举机制和簇间多跳机制。仿真结果表明,在延长网络生命周期和均衡全网能量消耗方面,该算法优于采用相同能量补给规律的传统分簇路由算法(LEACH算法和SEP算法)和其他基于能量自补给的分簇路由算法(PHC算法和EBCS算法)。     

基于混合量子进化算法的高效节能无线传感器网络路由算法

在无线传感器网络中,层次型路由算法能减少节点能量消耗和延长网络生存周期.因此在LEACH算法和PEGASIS算法的基础上,提出了一种基于混合量子进化算法的高效节能的无线传感器网络路由算法HERA.该算法中把网络分为多个簇,每个簇中的节点连接成为一条多跳通讯链路,并使用混合量子进化算法来得到最优的分簇组链方式,以减少链路...     

Joint routing, scheduling, and power control for multichannel wireless sensor networks with physical interference

Reliability and real-time requirements bring new challenges to the energy-constrained wireless sensor networks, especially to the industrial wireless sensor networks. Meanwhile, the capacity of wireless sensor networks can be substantially increased by operating on multiple nonoverlapping channels. In this context, new routing, scheduling, and power control algorithms are required to achieve reliable and real-time communications and to fully utilize the increased bandwidth in multichannel wireless sensor networks. In this paper, we develop a distributed and online algorithm that jointly solves multipath routing, link scheduling, and power control problem, which can adapt automatically to the changes in the network topology and offered load. We particularly focus on finding the resource allocation that realizes trade-off among energy consumption, end-to-end delay, and network throughput for multichannel networks with physical interference model. Our algorithm jointly considers 1) delay and energy-aware power control for optimal transmission radius and rate with physical interference model, 2) throughput efficient multipath routing based on the given optimal transmission rate between the given source-destination pairs, and 3) reliable-aware and throughput efficient multichannel maximal link scheduling for time slots and channels based on the designated paths, and the new physical interference model that is updated by the optimal transmission radius. By proving and simulation, we show that our algorithm is provably efficient compared with the optimal centralized and offline algorithm and other comparable algorithms.     

线型无线传感器网络中一种联合优化中继节点选择策略

在无线传感器网络中,时延与功耗性能往往是一对不可兼得的指标,如何优化和平衡这两个指标是路由和MAC算法中的难点.线型无线传感器网络由于拓扑结构的线型性,功耗-时延的均衡问题显得更加突出.基于线型无线传感器网络拓扑模型,理论分析了能耗最优传输距离,然后基于节点剩余能量,构建联合优化目标函数.进一步地,将数据包类型在时间敏感性方面分为紧急数据包和普通数据包,并相应调整发射功率,以便在当前通信范围内找到最优下一跳中继节点.最终提出了一个功率可调的时延-能耗自适应优化中继节点选择算法(LEARS).通过仿真实验将该算法与经典及类似算法比较,LEARS能够在保证紧急数据包传输实时性的同时,进一步降低网络的整体功耗,延长网络的生命周期.     

Self-organized routing for wireless microsensor networks

In this paper, we develop an energy-aware self-organized routing algorithm for the networking of simple battery-powered wireless microsensors (as found, for example, in security or environmental monitoring applications). In these networks, the battery life of individual sensors is typically limited by the power required to transmit their data to a receiver or sink. Thus, effective network-routing algorithms allow us to reduce this power and extend both the lifetime and the coverage of the sensor network as a whole. However, implementing such routing algorithms with a centralized controller is undesirable due to the physical distribution of the sensors, their limited localization ability, and the dynamic nature of such networks (given that sensors may fail, move, or be added at any time and the communication links between sensors are subject to noise and interference). Against this background, we present a distributed mechanism that enables individual sensors to follow locally selfish strategies, which, in turn, result in the self-organization of a routing network with desirable global properties. We show that our mechanism performs close to the optimal solution (as computed by a centralized optimizer), it deals adaptively with changing sensor numbers and topology, and it extends the useful life of the network by a factor of three over the traditional approach.     

DRAD:一种基于异步休眠调度的无线传感器网络数据收集协议

数据收集是无线传感器网络的基本功能之一,被大量应用到环境监测。如何降低网络能耗、延长网络生命周期是环境监测中数据收集的首要问题。大多数应用都选择使用休眠调度,通过监听空闲侦听的时间来节省能量,而这通常是在MAC层进行。本文则在网络层路由中考虑休眠调度的影响,将路由和休眠调度综合起来考虑,提出了一种基于异步休眠调度的无线传感器网络数据收集协议DRAD。DRAD通过异步休眠调度避免了时间同步的消耗,节点只需维护与邻居节点间的时间差,通过顺带时间差修正机制解决时间偏移问题,降低了能量开销。实验用占空比来衡量系统能量消耗,结果显示DRAD可以稳定在预先设定的占空比,有效降低网络能耗,延长网络寿命。     

高数据融合的非均匀分簇无线传感器网络路由协议*

探讨了基于非均匀分簇的无线传感器网络路由协议,提出了一种高数据融合的非均匀分簇无线传感器网络路由协议。仿真实验结果表明,该路由协议有效地平衡了无线传感器网络的节点能耗,延长了网络的存活时间。     

一种基于网格的无线传感器网络分簇路由协议

为延长网络生存时间,提出了一种基于网格的无线传感器网络分簇路由协议.整个网络分成若干个虚拟网格,每个虚拟网格形成一个簇,采用唯一簇头选举法产生簇头,且簇内成员可以根据局部的信息调整簇的大小,达到节省能量的目的.仿真实验和分析表明:该协议能均衡网络能量,延长网络的生存时间.     

Termite-hill: Performance optimized swarm intelligence based routing algorithm for wireless sensor networks

A wireless sensor network (WSN) is a large collection of sensor nodes with limited power supply, constrained memory capacity, processing capability, and available bandwidth. The main problem in event gathering in wireless sensor networks is the formation of energy-holes or hot spots near the sink. Due to the restricted communication range and high network density, events forwarding in sensor networks is very challenging, and require multi-hop data forwarding. Improving network lifetime and network reliability are the main factors to consider in the research associated with WSN. In static wireless sensor networks, sensors nodes close to the sink node run out of energy much faster than nodes in other parts of the monitored area. The nodes near the sink are more likely to use up their energy because they have to forward all the traffic generated by the nodes farther away to the sink. The uneven energy consumption results in network partitioning and limit the network lifetime. To this end, we propose an on-demand and multipath routing algorithm that utilizes the behavior of real termites on hill building termed Termite-hill which support sink mobility. The main objective of our proposed algorithm is to efficiently relay all the traffic destined for the sink, and also balance the network energy. The performance of our proposed algorithm was tested on static, dynamic and mobile sink scenarios with varying speed, and compared with other state-of-the-art routing algorithms in WSN. The results of our extensive experiments on Routing Modeling Application Simulation Environment (RMASE) demonstrated that our proposed routing algorithm was able to balance the network traffic load, and prolong the network lifetime.     

可充电无线传感网络能量均衡路由算法

针对可充电无线传感网络中的能量均衡路由问题,提出在稳定功率无线充电和监测数据收集网络场景下的多路径路由算法和机会路由算法,以实现网络的能量均衡。首先,通过电磁传播理论构建了无线传感节点的充电和接收功率关系模型;然后,考虑网络中无线传感节点的发送能耗和接收能耗,基于上述充电模型将网络能量均衡的路由问题转化为网络节点运行时间的最大最小化问题,通过线性规划得到的各链路流量用以指导路由中数据流量分配;最后,考虑一种更加现实的低功耗的场景,并提出了一种基于机会路由的能量均衡路由算法。实验结果表明,与最短路径路由（SPR）和期望周期最短路由（EDC）算法相比较,所提出的两种路由算法均能有效提高采集能量的利用率和工作周期内的网络生命周期。     

基于进化算法的无线传感器网络任播路由算法

在无线传感器网络WSN(Wireless Sensor Networks)中存在无线链路容易失效的现象,但大多数学者在设计路由算法时较多地关注网络生存期问题,而忽略路由健壮性问题.提出一种基于进化算法的WSN任播路由算法.该算法以网络生存期和路由健壮性为优化目标,并通过多目标进化算法寻找到两者的最佳适应值.实验验证了该算法的有效性,实验数据表明:相比较基于单目标优化(网络生存期)的任播路由算法,所提算法的网络生存期及路由健壮性两个性能的综合优化值优于前者;相比较传统单路径任播路由算法,所提算法的网络生存期、路由健壮性和可扩展性优于前者.     

基于移动代理的大规模无线传感器网络路由算法

大规模传感器网络中常见路由算法耗能严重,不利于网络生命期最大化。在抽象出传感器网络移动代理路由模型的基础上,将移动代理路由归结为一个优化问题。为了优化移动代理路由,结合混沌搜索的全局空间能力和模拟退火算法的快速寻优能力,设计了一种具有记忆功能和多种邻域搜索方法的混沌模拟退火算法。理论分析和模拟实验表明,随着传感器网络规模增大,算法在优化结果、收敛速度及时间效率方面均优于遗传算法和粒子群算法,明显延长了网络的生命期。