Anchor-free Localization Algorithm Research Articles

An Efficient Anchor-Free Localization Algorithm for all Cluster Topologies in a Wireless Sensor Network

A wireless sensor network is a type of network, which has many application domains such as military, civil security, industrial and environmental. Localization of fixed or mobile wireless sensors in wireless sensor networks is a delicate issue that has attracted the attention of many researchers. Indeed, a good estimation of the distances between different wireless sensors allows to derive their precise locations in the network. An ideal solution for locating these wireless sensors is to equip them with localization devices such as GPS. However, this solution is not an energy-efficient. Indeed, GPS is very energy-consuming, and the deployment environment is not easily accessible to humans. So, it is not possible to replace the batteries of these wireless sensors when they are discharged. Therefore, it is necessary to propose an energy-saving anchor-free localization algorithm. Despite the grouping of nodes into clusters (or sub-networks), existing anchor-free localization algorithms suffer from a low rate of node localization, low localization accuracy, and high energy consumption. To improve the proposed solutions in the literature, an Efficient Anchor Free Localization Algorithm (EAFLA) was proposed. Regardless the topology of each cluster, our algorithm allows localization of all wireless sensors with a very low localization error rate and consumes less energy.

A simple efficient anchor-free node localization algorithm for wireless sensor networks

In wireless sensor networks, node localization is the first operation after deployment, and the efficiency of localization can directly influence the performance of the wireless sensor network, so designing an efficient localization algorithm has been an important focus in wireless sensor network research. Currently, anchor-free algorithms are the focus of research in node localization because they have the advantages of flexible structure, low cost, high stability and good extensibility. In this article, related research studies of unique localization-, angle- and distance-obtaining methods are introduced, and existing algorithms are analysed. Based on the analysis of existing research, an anchor-free localization algorithm named ladder diffusion node localization algorithm is proposed, in which sensor nodes are located by directional diffused activation and acknowledgement packets with fixed energy. In ladder diffusion node localization algorithm, the time cost of localization is greatly reduced, the communication tasks in localization are allocated in a more balanced manner, and node locations are obtained mainly by rigorous computation instead of measurement, which can reduce transmission measurement error. Finally, the performance of ladder diffusion node localization algorithm is proved both in theory and by the simulation results of experiments.

An Energy Efficient Anchor-Free Localization Algorithm for No-Identity Wireless Sensor Networks

A wireless sensor network (WSN) model by analyzing the limitations of existing localization algorithm is proposed in this paper. Specifically, neither the anchor nor the ID is required in the proposed model, and the node function is limited. The hardware function of the node in our model is independent of the MAC protocol. Moreover, based on the proposed WSN model, we design an energy efficient anchor-free localization algorithm for no-identity WSN. Instead of multiple measurements, mathematical calculation is adopted to acquire the position information. Subsequently, the effectiveness of the algorithm is confirmed by rigid theory. The simulation results show that the proposed algorithm can improve the performance of localization and energy efficiency in WSN significantly.

Surface-Reflection-Based Communication and Localization in Underwater Sensor Networks

Most communication and localization algorithms in underwater environments have been constrained by dependencies on the Line Of Sight (LOS), which is hard to guarantee due to the inherent node mobility. This constraint hinders node discovery and ad hoc formation in underwater networks and limits the performance of routing protocols. This article introduces a novel Surface-Based Reflection (SBR) model that uses a homomorphic deconvolution technique to establish water-surface-reflected communication links. We then propose a Surface-Based Reflection Anchor-free Localization (SBR-AL) algorithm that can be employed by the individual nodes to establish a relative coordinate system. Our approach also employs a switch-beamed directional antenna model that allows each node to use the LOS estimated from SBR-AL to enable directional communication which is beneficial for higher Signal-to-Noise Ratios (SNR). The relative locations can facilitate the various network operation functions such as geo-routing and collision-free medium access. The simulation results confirm the effectiveness of the proposed approach.

Localization for anchor-free underwater sensor networks

For Underwater Wireless Sensor Networks (UWSN), identifying the location of each sensor node is an important issue, which is also a challenging task. Most of the existing localization schemes assume that the network has a plurality of anchor nodes to assist positioning. Usually, they make use of Autonomous Underwater Vehicle (AUV) or node with special equipment as anchor node, because Global Positioning System (GPS) is invalid in underwater environment. High cost and poor flexibility make them not well suitable for UWSN. In order to overcome this disadvantage, we propose an Anchor-Free Localization Algorithm, called AFLA. It is designed for active-restricted underwater sensor networks. AFLA does not need anchor node’s information, and makes use of the relationship of adjacent nodes. It could be used in both static and dynamic networks. The obtained simulation results indicate that AFLA is an effective localization scheme for UWSN.

Anchor-Free Localization through Flip-Error-Resistant Map Stitching in Wireless Sensor Network

In patch-and-stitch localization algorithms, a flip error refers to the kind of error in which a patch is stitched to the map as being wrongly reflected. In this paper, we present an anchor-free localization algorithm which tries to detect and prevent flip errors. The flip error prevention is achieved by two filtering mechanisms: the flip ambiguity test and the flip conflict detection. Based on two techniques, we devised an anchor-free localization algorithm and evaluated the performance of the proposed algorithm though simulations. The results show that our algorithm achieves significant performance improvement over the existing algorithms.

The Effects of Stitching Orders in Patch-and-Stitch WSN Localization Algorithms

A "patch-and-stitchrdquo localization algorithm divides the network into small overlapping subregions. Typically, each subregion consists of a node and all or some of its neighbors. For each subregion, the algorithm builds a local map, called a patch, which is actually an embedding of the nodes it spans in a relative coordinate system. Finally, the algorithm stitches those patches to form a single global map. In a patch-and-stitch algorithm, the stitching order makes an influence on both the performance and the complexity of the algorithm. In this paper, we present a formal framework to deal with stitching orders in patch-and-stitch localization algorithms. In our framework, the stitching order is determined by a stitching scheme and the stitching scheme consists of a stitching policy and a potential function. The potential function is to predict how well a patch will be stitched if patches are stitched according to a given partial order. The stitching policy is a mechanism that determines the stitching order based on the predictions by the potential function. We present various stitching schemes and evaluate them through simulations. In addition, we apply the patch-and-stitch strategy into the anchor-based localization and propose a clustering-based localization algorithm. A potential function is used to partition the network into clusters each of which is centered at an anchor node. For each cluster, a cluster map is constructed via the anchor-free localization algorithm. Then, those cluster maps are combined to form a single global map. We propose a stitching technique for combining those cluster maps and analyze the performance of the algorithm by simulations.

Localization through Map Stitching in Wireless Sensor Networks

Node localization is an essential problem in ad hoc wireless sensor networks. Map stitching is a type of localization algorithm that has received a great deal of attention recently. In this algorithm, the network is divided into small overlapping sub-regions, each of which creates a local map. Then, the local maps are stitched together to form a single global map. In this paper, we first propose a new technique for map-to-map stitching that exploits every available distances between two maps. Next, we propose a few anchor-free localization algorithms based on our stitching technique. We experimentally studied the performance of our algorithms under various settings. The results show that our method achieves a significant performance improvement upon the existing method.

Co-designed anchor-free localization and location-based routing algorithm for rapidly-deployed wireless sensor networks

We consider a wireless sensor network consisting of a single sink node at the center of a field of randomly distributed sensors. A simple anchor-free localization algorithm is proposed, in which the sink node imparts radial location information through the phased-array transmission of a series of beacons. Each individual sensor uses the knowledge of received beacons as well as information from neighbors to continue partitioning current sectors and identifying sub-sectors in which it resides until an accuracy requirement is satisfied. An energy-preserving routing algorithm is then proposed which uses the localization results as the basis for selecting relay nodes. We present the localization algorithm, analyze its partition errors as well as its impact on communication energy consumption, and then present the location-based routing algorithm. Simulation results indicate that the performance of our co-designed localization and routing algorithm in the presence of severe noise is as good as that provided by a shortest-path routing algorithm under ideal assumptions; therefore, our co-designing approach can achieve high performance with lightweight algorithms.

Energy cost and error performance of range-aware, anchor-free localization algorithms

Many applications that use sensor data from a wireless sensor network (WSN) require corresponding node position information as well. Therefore, it is not surprising that a common figure of merit for localization algorithms is the accuracy of the position estimate produced. Similarly, the amount of communication required by a localization algorithm is often of paramount interest as well since it is common knowledge that communication expends the most energy in a WSN. However, localization algorithms seldom characterize their communication cost. Furthermore, when they do it is often merely qualitative and is typically described as “expensive”. For two types of range-aware, anchor-free localization algorithms we found the opposite to be true. Rather than being expensive, the communication costs were quite modest. So much so that we maintain range-aware, anchor-free localization algorithms should be chosen on the basis of the accuracy required by the intended application independent of the communication cost. In this paper, we examine the effect of node degree, node distribution, range error and network size on distance error and communication cost for both incremental and concurrent versions of range-aware, anchor-free algorithms. The concurrent algorithm is twice as accurate as the incremental, but less efficient. Furthermore, node degree influences the energy cost of the algorithms the most, but neither algorithm uses more than a surprisingly small 0.8% of a 560 mA h battery. This result indicates less energy efficient localization algorithms can be tolerated, especially if they provide better accuracy. Furthermore, if energy does need to be conserved, there is not much savings available within the localization algorithm and savings must be found in other areas such as the MAC protocol or routing algorithm.