Novel DV-Hop localization algorithm for wireless sensor networks

Many improved DV-Hop localization algorithm have been proposed to enhance the localization accuracy of DV-Hop algorithm for wireless sensor networks. These proposed improvements of DV-Hop also have some drawbacks in terms of time and energy consumption. In this paper, we propose Novel DV-Hop localization algorithm that provides efficient localization with lesser communication cost without requiring additional hardware. The proposed algorithm completely eliminates communication from one of the steps by calculating hop-size at unknown nodes. It significantly reduces time and energy consumption, which is an important improvement over DV-Hop—based algorithms. The algorithm also uses improvement term to refine the hop-size of anchor nodes. Furthermore, unconstrained optimization is used to achieve better localization accuracy by minimizing the error terms (ranging error) in the estimated distance between anchor node and unknown node. Log-normal shadowing path loss model is used to simulate the algorithms in a more realistic environment. Simulation results show that the performance of our proposed algorithm is better when compared with DV-Hop algorithm and improved DV-Hop—based algorithms in all considered scenarios.     

无线传感器网络SL-n迭代定位算法

无线传感器网络迭代多边定位算法在迭代定位过程中使用全局最小均方估计(MMSE)方法估计盲节点的位置,导致算法定位误差很大,缺乏稳健性。针对此问题,提出了SL-n估计方法,该方法首先把某盲节点的所有参考节点进行分组,通过三边法或局部MMSE方法求出的每组相应样本值,并用这些样本值估计出此盲节点的位置。仿真实验表明,当部分参考节点的参考误差较大时,该方法优于全局MMSE处理方法,可以有效降低定位误差。     

无线传感器网络中能量感知目标定位算法

在传感器网络中节点能量有限,因此设计出能量高效的目标定位算法对于延长网络生命期、增强网络健壮性有着非常重要的意义.提出了一种能量高效的目标定位算法,并提出了在节点稀疏情况下保证定位精确性的方法.仿真表明,使用文中提出算法的传感器网络能大大地降低能量损耗.     

CRWSNP: cooperative range-free wireless sensor network positioning algorithm

Sensing events occur in an area without knowing the events locations, is meaningless. Since there is no priorly knowledge about the locations of most of the sensors which scattered randomly in an area, wireless sensor network localization methods try to find out where sensors are located. A new cooperative and distributed range-free localization algorithm, based on only connectivity information is proposed in this paper. The method first uses convex optimization techniques to find primitive target nodes locations estimation, then nodes cooperate with each other in several iterations to improve the whole network location estimation. CRWSNP converges after a finite number of iterations because of applying two novel heuristic location correction techniques. As well as, results of the algorithm have been compared with six range-free based methods like CPE, DV-hop, APIT; and CRWSNP algorithm provides more accurate results over 50 random topologies for the network, in mean error and maximum error metrics.     

无线传感器网络的分布式能量有效非均匀成簇算法

研究了现有成簇路由算法,提出了分布式能量有效成簇路由算法,该算法主要包括3部分内容:一是选择候选簇头时通过引入平均能量因子来平衡全网节点的剩余能量情况;二是构造了基于能量和距离的能量消耗率函数以平衡节点的能量效率;三是首次提出了基于同构单跳网络的分布式能量有效非均匀成簇路由算法.理论和仿真结果均说明该算法优于EECS,生命周期比EECS延长达到约30%.     

An improvement of DV-Hop localization algorithm for wireless sensor networks

An improved DV-HOP localization algorithm is proposed based on the traditional DV-HOP localization algorithm in the paper. There will be a big error that using the nearest anchor node’s average hop distance instead of the average hop distance of all the anchor nodes that involved in the localizing in the traditional DV-HOP localization algorithm. Therefore, the improved algorithm introduces threshold M, it uses the weighted average hop distances of anchor nodes within M hops to calculate the average hop distance of unknown nodes. In addition, the positioning results are corrected in the improved algorithm. The simulation results show that the new localization algorithm effectively improves the positioning accuracy compared with the traditional DV-HOP localization algorithm, it is an effective localization algorithm in the wireless sensor networks.     

An energy efficient clustering routing algorithm for wireless sensor networks

~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A…     

基于RSSI无线传感器网络空间定位算法

RSSI测距技术在实际应用环境中,由于多径、绕射、障碍物等因素,无线电传播路径损耗使得定位过程中产生距离误差.通过对三维空间定位过程中产生距离误差区域进行分析,提出了基于RSSI新的空间定位算法ERSS,该定位算法计算简单,定位过程中节点间不增加通信开销,无需硬件扩展.仿真实验表明该算法较普通的基于RSSI的测距方法定位精度和响应时间有了明显的改进,适合在通信开销小、硬件要求低的传感器网络节点上应用.     

Improvement of DV-Hop localization algorithm for randomly deployed wireless sensor networks

Telecommunication Systems - The Distance Vector-Hop (DV-Hop) algorithm is a well-known technique for wireless sensor networks node location due to its robustness, simplicity and cost effectiveness....     

A time efficient aggregation convergecast scheduling algorithm for wireless sensor networks

Wireless Networks - We investigated the aggregation convergecast scheduling problem in wireless sensor networks. In order to reduce the time needed for data collection through aggregation...     

无线传感器网络中能量高效的基站位置优选算法

将基站位置选择及节能路由优化联合考虑,定义了最短路径树剖分,分析了二维空间中剖分单元的结构与相邻剖分单元搜索算法,并设计了3种启发式算法.通过仿真实验对算法性能进行了分析与对比,结果表明所提出的启发式算法的性能有效地接近或者收敛于全局最优解.     

Quantized lower bounds on grid-based localization algorithm for wireless sensor networks

In this paper, we introduce a Quantized Cramer Rao Bound (Q-CRB) method, which adapts the use of the CRB to handle grid-based localization algorithms with certain constraints, such as localization boundaries. In addition, we derive a threshold granularity level which identifies where the CRB can be appropriately applied to this type of algorithm. Moreover, the derived threshold value allows the users of grid-based LSE techniques to probably avoid some unnecessary complexities associated with using high grid resolutions. To examine the feasibility of the new proposed bound, the grid-based least square estimation (LSE) technique was implemented. The Q-CRB was used to evaluate the performance of the LSE method under extensive simulation scenarios. The results show that the Q-CRB provided a tight bound in the sense that the Q-CRB can characterize the behaviour of location errors of the LSE technique at various system parameters, e.g. granularity levels, measurement accuracies, and in the presence or absence of localization boundaries.     

高精确度与高覆盖率的传感器网络定位算法

为了对无线传感器网络中随机分布的节点实施有效定位,针对典型Bounding Box算法的定位准确性与覆盖率较低的不足,提出了一种基于三跳通信环带概念的定位算法C3HR(concentric triple-hop of node communication range).理论分析及仿真结果均表明,该算法优化了对待测节点位置的约束,对于锚节点分布稀疏和不均匀的网络,显著提高了定位的准确性及覆盖率,并能够有效降低节点能耗.     

基于高能效RSSI的WSN定位

传感器自我定位是无线传感器网络中许多和定位有关的技术之一。虽然定位的主要目的是提高定位精度,但是能量消耗对定位提出了新的挑战。文中在考虑估计误差的同时,研究了最优功率分配的参考节点在一定意义上的最小能量消耗。为了对一个参考节点和一个利用了接收信号强度指示器(RSSI)的未知节点之间的相对距离有一个更好的估计,把接收到的信标的平均能量作为一种新的决策度量。基于此得到一个作为精度参数的平方位置误差和一个提高定位性能的优化问题。仿真结果表明,通过优化传输功率的配置可以实现能耗的大幅减少。     

多跳无线传感器网络的高效中继节点快速选择算法

针对多跳无线传感器网络数据收集协议中继转发节点选择算法效率不高的问题,提出了一种能量有效的中继节点快速选择 (EERNFS)算法.EERNFS算法利用分时共享信道的方法维护网络同步和更新节点的邻居信息,使节点在每个网络侦听/睡眠周期依赖一定的概率同步激活唤醒,确保了网络节点瞬时连通度的稳定和一致;基于网络节点的地理优先级、节点价值和链路质量的分布式估计,EERNFS算法采用竞争的方法选择中继转发节点, 使用乘性增加时间窗口的方法,分解候选中继节点间的竞争.理论分析和模拟实验结果表明,EERNFS算法在能效、数据传递的平均时延、分组到达率等网络性能指标上显著优于FFS和GeRaF算法,极大地延长了网络的寿命.     

基于矢量的无线传感器网络节点定位综合算法

基于DV-hop设计了一种节点的定位综合算法,并将其应用于移动节点.利用节点间估计距离和测量距离的差异构建位置校正矢量;通过改进的粒子群优化方法得到节点的校正步长;节点将其与位置校正矢量的乘积作为自身位置的校正值.通过仿真进行算法验证并分析了复杂度和有效性,结果证明该算法可以将DV-hop的定位误差下降75%,并且适用于稀疏网络.     

LIP: an efficient lightweight iterative positioning algorithm for wireless sensor networks

Wireless sensor networks (WSNs) are increasingly being used in remote environment monitoring, security surveillance, military applications, and health monitoring systems among many other applications. Designing efficient localization techniques have been a major obstacle towards the deployment of WSN for these applications. In this paper, we present a novel lightweight iterative positioning (LIP) algorithm for next generation of wireless sensor networks, where we propose to resolve the localization problem through the following two phases: (1) initial position estimation and (2) iterative refinement. In the initial position estimation phase, instead of flooding the network with beacon messages, we propose to limit the propagation of the messages by using a random time-to-live for the majority of the beacon nodes. In the second phase of the algorithm, the nodes select random waiting periods for correcting their position estimates based on the information received from neighbouring nodes. We propose the use of Weighted Moving Average when the nodes have received multiple position corrections from a neighbouring node in order to emphasize the corrections with a high confidence. In addition, in the refinement phase, the algorithm employs low duty-cycling for the nodes that have low confidence in their position estimates, with the goal of reducing their impact on localization of neighbouring nodes and preserving their energy. Our simulation results indicate that LIP is not only scalable, but it is also capable of providing localization accuracy comparable to the Robust Positioning Algorithm, while significantly reducing the number of messages exchanged, and achieving energy savings.     

A new patch and stitch algorithm for localization in wireless sensor networks

Wireless Networks - Patch and stitch is a technique used for localization in wireless sensor networks. It combines the accuracy of centralized schemes with the computational efficiency of...     

多基站无线传感器网络中能量高效的基站位置优选算法

结合节能路由算法,研究以最小化网络总能耗为目标的基站位置选择问题.将基站位置候选集为有限集的情形化归为整数线性规划问题,并将候选集为全空间的情形化归为非线性规划问题.由于问题的NP-完全性质,分别针对2种情形设计了相应的启发式算法.通过仿真实验对所提出算法的性能进行验证,结果表明所提算法性能接近最优解.