Lifetime elongation for wireless sensor network using queue-based approaches

A wireless sensor network (WSN) is envisioned as a cluster of tiny power-constrained devices with functions of sensing and communications. Sensors closer to a sink node have a larger forwarding traffic burden and consume more energy than nodes further away from the sink. The whole lifetime of WSN is deteriorated because of such an uneven node power consumption patterns, leading to what is known as an energy hole problem (EHP). From open literatures, most research works have focused on how to optimally increase the probability of sleeping states using various wake-up strategies. In this article, we propose a novel power-saving scheme to alleviate the EHP based on the N-policy M/M/1 queuing theory. With little or no extra management cost, the proposed queue-based power-saving technique can be applied to prolong the lifetime of the WSN economically and effectively. A mathematical analysis on the optimal control parameter has been made in detail. Focusing on many-to-one WSN, numerical and network simulation results validate that the proposed approach indeed provides a feasibly cost-effective approach for lifetime elongation of WSN.     

基于Z-Stack协议栈的ZigBee网络节能算法的研究

ZigBee技术是实现无线传感器网络的重要技术手段之一,其中,Z-Stack协议栈是TI公司推出的一种实现ZigBee技术的软件架构,已被广泛使用。以CC2530为硬件平台,Z-Stack协议栈为软件平台,通过对Z-Stack协议栈的分析研究,指出了现有的Z-Stack协议栈在实际应用条件下存在的功耗问题,提出了相应的节能算法:针对终端节点的功率优化调节算法和针对路由器节点的低功耗算法,并通过实验进行验证。实验结果表明,与原始的Z-Stack协议相比,本文提出的基于Z-Stack协议栈的节能算法可以有效地减少节点在工作过程中的能耗,从而提高网络的整体寿命。     

Energy-aware node placement,topology control and MAC scheduling for wireless sensor networks

In the WSNs, the nodes closer to the sink node have heavier traffic load for packet forwarding because they do not only collect data within their sensing range but also relay data for nodes further away. The unbalanced power consumption among sensor nodes may cause network partition. This paper proposes efficient node placement, topology control, and MAC scheduling protocols to prolong the sensor network lifetime, balance the power consumption of sensor nodes, and avoid collision. Firstly, a virtual tree topology is constructed based on Grid-based WSNs. Then two node-placement techniques, namely Distance-based and Density-based deployment schemes, are proposed to balance the power consumption of sensor nodes. Finally, a collision-free MAC scheduling protocol is proposed to prevent the packet transmissions from collision. In addition, extension of the proposed protocols are made from a Grid-based WSN to a randomly deployed WSN, enabling the developed energy-balanced schemes to be generally applied to randomly deployed WSNs. Simulation results reveal that the developed protocols can efficiently balance each sensor node’s power consumption and prolong the network lifetime in both Grid-based and randomly deployed WSNs.     

一种无线传感网的Sink节点移动路径规划算法研究

为寻找传感节点均匀分布时Sink节点的最优移动路径和最大网络生存时间,提出一种无线传感网的Sink节点移动路径规划算法(MPOA).在MPOA算法中,将Sink节点的数据收集范围分解成多个圆环,将监测区域分解成多个网格.根据Sink节点的停留位置和多跳通信方式,采用数学公式表示每一个网格的单位节点能耗,从而获得Sink节点移动的网络生存时间优化模型.采用修正的混合粒子群算法求解该优化模型,获得网络生存时间、Sink节点的停留位置和移动路径的最优方案.仿真结果表明:MPOA算法可寻找到Sink节点的最优移动路径,从而平衡网络能耗,提高网络生存时间.在一定的条件下,MPOA算法比Circle,Rect和Rand算法更优.     

基于数据融合的传感器网络寿命最优路由策略

引入数据融合率来定义传感器网络中节点的融合能力,并提出一种基于数据融合技术的分布式最优路由算法,最大化网络的寿命.将路由决策过程描述为线性规划问题,采用子梯度算法求取最优解,得到了分布式的优化算法.仿真结果表明,该算法可有效减少数据通信量,均衡各个节点的能量消耗,延长网络寿命.     

无线传感网中一种智能数据融合算法的实现及仿真分析

在无线传感网中,传感器节点一般都由自身装配的电池供电,难以进行电量补充,因此节约电量对于无线传感网来说至关重要.为了提高无线传感网能量使用效率,延长网络生存时间,提出了一种结合遗传算法和粒子群算法优化BP神经网络的智能数据融合算法 GAPSOBP(BP Neural Network Data Fusion algorithm optimized by Genetic algorithm and Particle swarm).GAPSOBP算法将无线传感网的节点类比为BP神经网络中的神经元,通过神经网络提取无线传感网采集的感知数据并结合分簇路由对收集的传感数据进行融合处理,从而大幅减少发往汇聚节点的网络数据量.仿真结果表明,与经典LEACH算法和PSOBP算法相比,GAPSOBP算法能有效减少网络通信量,节约节点能量,显著延长网络生存时间.     

On mitigating hotspots to maximize network lifetime in multi-hop wireless sensor network with guaranteed transport delay and reliability

In wireless sensor networks (WSNs), sensor nodes close to the sink consume more energy than others because they are burdened with heavier relay traffic destined for the sink and trend to die early, forming hotspots or energy holes in WSNs. It has a serious impact on network lifetime. In this paper, three optimization algorithms are proposed to mitigate hotspots and prolong network lifetime for adaptive Mary Phase Shift Keying (MPSK) based wireless sensor networks while transport delay and reliability can be still guaranteed. Based on the insight gained into the relationship between nodal data load and energy consumption in different regions, the first algorithm (GlobalSame) can extend considerably the network lifetime by selecting the optimal nodal transmission radius r, bit error rate ε and transmission rate allocations in bits per symbol (BPS) τ. The second algorithm (RingSame) can further improve network lifetime by comparison to the GlobalSame algorithm, which by selecting different ε _i and τ _i for nodes in different regions under constraints of total BER and transport delay . While the third algorithm (NodeDiff) can further improve the network lifetime by adopting different BER ε and BPS τ parameters of the same node for data packets received according to its distance to the sink. Extensive simulation studies show that our algorithms do considerably prolong the network lifetime.     

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。     

密集型传感器网络中移动sink的路径选择机制

针对密集型无线传感器网络,以最大化网络寿命为优化目标,将网络转换成相应的网络流图,利用网络最大流问题估算sink采用不同路径下的网络寿命并以此为标准进行路径选择,提出了一种基于网络流理论的高效sink路径选择机制。仿真结果表明,本方案同采用固定路径采集及类似解决方案相比,能有效均匀网络能耗,延长网络寿命,取得了较好的网络性能。     

基于区域分簇的大规模无线传感器网络生命周期优化策略

针对环境监测、电网冰灾监测等大规模监测系统中监测区域覆盖广、传感器数量大等特性,为节约网络能耗以延长生命周期,提出了一种基于区域分簇的大规模无线传感器网络生命周期优化策略(RCS).该策略首先利用传感器节点的位置信息进行凝聚的层次聚类(AGNES)算法将大规模网络分区以优化簇首的分布;其次,候选簇首节点竞选簇首成功后进行不均匀分簇,同时加入时间阈值来均衡簇首节点的能耗;最后,采用簇间多跳路由,根据节点剩余能量、与汇聚点距离计算网络能耗代价来构建最小生成树进行路由选择.在仿真实验中,该策略与经典的低功耗自适应分簇(LEACH)协议和能量高效的非均匀分簇(EEUC)算法比较,簇首能耗平均分别减少了45.1%和2.4%,网络生命周期分别延长了38%和3.7%.实验结果表明,RCS在大规模网络中能有效均衡整体网络能耗,显著延长了网络的生命周期.     

A fuzzy logical controller for traffic load parameter with priority-based rate in wireless multimedia sensor networks

In wireless multimedia sensor networks (WMSNs), sensor nodes use different types of sensors to gather different types of data. In multimedia applications, it is necessary to provide reliable and fair protocols in order to meet specific requirements of quality of service (QoS) demands in regard to these different types of data. To prolong the system lifetime of WMSNs, it is necessary to perform adjustments to the transmission rate and to mitigate network congestion. In previous works investigating WMSNs, exponential weighted priority-based rate control (EWPBRC) schemes with traffic load parameter (TLP) schemes in WMSNs were used to control congestion by adjusting transmission rates relative to various data types. However, when the TLP is fixed, a large change in data transmission causes a significant difference between input transmission rate and the estimated output transmission rate of each sensor node. This study proposes a novel fuzzy logical controller (FLC) pertaining to TLP schemes with an EWPBRC that estimates the output transmission rate of the parent node and then assigns a suitable transmission rate based on the traffic load of each child node, with attention paid to the different amounts of data being transmitted. Simulation results show that the performance of our proposed scheme has a better transmission rate as compared to PBRC: the delay and loss probability are reduced. In addition, our proposed scheme can effectively control different transmission data types insofar as achieving the QoS requirements of a system while decreasing network resource consumption.     

基于网络编码感知的能量均衡的ZigBee路由策略

ZigBee网络通常通过电池提供能源,某些节点的电池能量消耗较大,会导致网络分割和节点过早死亡,影响整个网络的生存。为了实现ZigBee网络的能量优化,延长网络生存时间,提出一种基于网络编码感知的能量均衡的ZigBee路由策略NCEBR（ Network Coding-aware based Energy-Balanced Routing）。该策略能够选择具有最小总能耗和最小剩余能量的路径传输分组以均衡网络节点能量消耗,同时通过网络编码降低节点能耗。仿真结果表明,与传统的ZigBee路由协议相比,NCEBR策略能够减少死亡节点数,均衡网络能量消耗,延长网络生存时间。     

无线传感器网络权衡生存时间与数据分组跳数的分流路由算法

无线传感器网络的节点大多采用电池供电.因而节能对无线传感器网络就显得至关重要.该文提出一种能耗感知的优化网络生存时间的路由算法,称之为分流路由算法(DTRA,Diffluent Traffic Routing Algorithm).DTRA算法采用一个优化模型以优化每个节点发出的数据比例,从而达到权衡网络生存时间和数据分组跳数.此外,采用一个简单的遗传算法求解该优化问题.仿真结果表明:DTRA算法能显著地提高网络的生存时间,同时将数据分组平均跳数保持在一个较低的水平;在网络生存时间上,DTRA算法比一些已有的知名算法更优.     

基于事件优先级的蛇形时隙存储算法

针对WSN中的以数据为中心的平面型存储算法没有考虑在数据传输过程中节点的能量消耗问题,考虑到节点数据的重要程度,赋予相应的优先级,在蛇形时隙的节能存储算法(SLPS)基础上,提出基于事件优先级和动态散列位置的蛇形时隙算法(P-SLPS).P-SLPS算法通过划分网格区域,将特定类型的数据存储在相应的网格中,通过定义事件优先级,将高优先级的事件存储在距离查询节点更近的网络区域,保证高优先级事件优先被搜索.根据监测节点和存储映射地址计算动态散列位置,将检测事件存储在同一优先级区域内离监测节点最近的存储网格.从网络生命周期和网络的节点存活数两方面进行仿真,结果表明P-SLPS算法在能量消耗方面低于SLPS算法,延长了无线传感网络的生命周期.     

Network lifetime bounds for hierarchical wireless sensor networks in the presence of energy constraints

In previous years, one popular problem that is constantly being researched into is how to prolong the lifetime of wireless sensor networks (WSNs). Many approaches to maximize network lifetime have been proposed and each approach provides different levels of energy savings and are efficient in their own aspects. However, these proposed algorithms are not suitable for use in a hard network lifetime environment where participating sensors should be working till the strict network lifetime requirement. The predictability of the network lifetime plays an important role in supporting guaranteed network lifetime services. This can be provided through the schedulability test that complements the online operations of safe and critical sensor network systems. In this paper, we focus on the study of the predictability of the network lifetime to enable the High Energy First clustering algorithm (HEF) to work in a hard lifetime environment and present a schedulability test to verify whether HEF can make the set of sensors schedulable in terms of N-of-N and K-of-N alive nodes.     

基于相关性感知的无线视频传感器网络路由协议

无线视频传感器网络（ WVSNs）节点的能量十分有限,为了降低传感器节点的能耗,延长网络生存时间,提出了一种基于相关性感知的视频传感器网络通信协议。首先对当前经典无线视频传感器网络路由协议的不足进行分析;然后从簇首节点的选择、簇的形成、节点感知方向的调整、簇内通信以及簇间通信等几个方面进行改进和优化;最后在Matlab 2012平台进行了仿真对比测试。仿真结果表明：该协议不仅能够延长无线视频传感器网络生命周期,而且提高了监测区域覆盖率。     

Satisfying the target network lifetime in wireless sensor networks

Generally, the lifetime of a wireless sensor network (WSN) is defined as the duration until any sensor node dies due to battery exhaustion. If the traffic load is not properly balanced, the batteries of some sensor nodes may be depleted quickly, and the lifetime of the WSN will be shortened. While many energy-efficient routing schemes have been proposed for WSNs, they focus on maximizing the WSN lifetime. In this paper, we propose a scheme that satisfies a given ‘target’ lifetime. Because energy consumption depends on traffic volume, the target lifetime cannot be guaranteed through energy-efficient routing alone. We take an approach that jointly optimizes the sensing rate (i.e., controlling the sensor-traffic generation or duty cycle) and route selection. Satisfying the target lifetime while maximizing the sensing rate is a NP-hard problem. Our scheme is based on a simple Linear Programming (LP) model and clever heuristics are applied to compute a near-optimal result from the LP solution. We prove that the proposed scheme guarantees a 1/2-approximation to the optimal solution in the worst case. The simulation results indicate that the proposed scheme achieves near-optimality in various network configurations.     

基于最短路径树的优化生存时间路由算法

为提高无线传感网的生存时间,提出基于最短路径树的优化生存时间路由算法(LORA_SPT).该算法引入节点分类概念,构造基于链路能耗因子、自身节点剩余能量因子、邻居节点剩余能量因子和类型权重因子等多个因子的权值函数.针对不同类型的节点采用不同的权重因子,最后利用dijkstra算法完成最短路径树,所有节点沿着最短路径树将...     

基于蚁群的无线传感网最大化生存时间路由

为提高无线传感网的生存时间,对基于蚁群算法的最大化生存时间路由(MLRAC)进行了研究。该路由利用链路能耗模型和节点发送数据概率,计算一个数据收集周期内节点总能耗。同时考虑节点初始能量,建立了最大化生存时间路由的最优模型。为求解该最优模型,在经典蚁群算法的基础上,提出修正的蚁群算法。该算法采用新的邻居节点转发概率公式、信息素更新公式和分组探测方法,经过一定的迭代计算获得网络生存时间的最优值和每个节点的最优发送数据概率。最后,Sink节点洪泛通知网络中所有节点。节点根据接收到的最优概率,选择数据分组未经过的邻居节点发送数据。仿真实验表明,经过一定时间的迭代,MLRAC的生存时间可以收敛到最优值。该算法能延长网络生存时间,在一定的条件下,MLRAC算法比PEDAP、LET、Ratio-w、Sum-w等算法更优。     

EEMC: An energy-efficient multi-level clustering algorithm for large-scale wireless sensor networks

Wireless sensor networks can be used to collect environmental data from the interested area using multi-hop communication. As sensor networks have limited and non-rechargeable energy resources, energy efficiency is a very important issue in designing the topology, which affects the lifetime of sensor networks greatly. In this paper, the energy consumption is modeled and compared under the flat scheme and the clustering scheme, respectively. Motivated by the analysis, we propose an energy-efficient multi-level clustering algorithm called EEMC, which is designed to achieve minimum energy consumption in sensor networks. The cluster head election scheme is also considered in EEMC. EEMC terminates in O(log log N) iterations given N nodes. When the path loss exponent is 2, EEMC also achieves minimum latency. We focus on the case where sink node is remotely located and sensor nodes are stationary. Simulation results demonstrate that our proposed algorithm is effective in prolonging the network lifetime of a large-scale network, as well as low latency and moderate overhead across the network.