A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Efficient Range-Free Monte-Carlo-Localization for Mobile Wireless Sensor Networks

Das Hauptproblem von Lokalisierungsalgorithmen für WSNs basierend auf Ankerknoten ist die Abhängigkeit von diesen. Mobilität im Netzwerk kann zu Topologien führen, in denen einzelne Knoten oder ganze Teile des Netzwerks temporär von allen Ankerknoten isoliert werden. In diesen Fällen ist keine weitere Lokalisierung möglich. Dies wirkt sich primär auf den Lokalisierungsfehler aus, der in diesen Fällen stark ansteigt. Des weiteren haben Betreiber von Sensornetzwerken Interesse daran, die Anzahl der kosten- und wartungsintensiveren Ankerknoten auf ein Minimum zu reduzieren. Dies verstärkt zusätzlich das Problem von nicht verfügbaren Ankerknoten während des Netzwerkbetriebs. In dieser Arbeit werden zunächst die Vor- und Nachteile der beiden großen Hauptkategorien von Lokalisierungsalgorithmen (range-based und range-free Verfahren) diskutiert und eine Studie eines oft für range-based Lokalisierung genutzten Distanzbestimmungsverfahren mit Hilfe des RSSI vorgestellt. Danach werden zwei neue Varianten für ein bekanntes range-free Lokalisierungsverfahren mit Namen MCL eingeführt. Beide haben zum Ziel das Problem der temporär nicht verfügbaren Ankerknoten zu lösen, bedienen sich dabei aber unterschiedlicher Mittel. SA-MCL nutzt ein dead reckoning Verfahren, um die Positionsschätzung vom letzten bekannten Standort weiter zu führen. Dies geschieht mit Hilfe von zusätzlichen Sensorinformationen, die von einem elektronischen Kompass und einem Beschleunigungsmesser zur Verfügung gestellt werden. PO-MCL hingegen nutzt das Mobilitätsverhalten von einigen Anwendungen in Sensornetzwerken aus, bei denen sich alle Knoten primär auf einer festen Anzahl von Pfaden bewegen, um den Lokalisierungsprozess zu verbessern. Beide Methoden werden durch detaillierte Netzwerksimulationen evaluiert. Im Fall von SA-MCL wird außerdem eine Implementierung auf echter Hardware vorgestellt und eine Feldstudie in einem mobilen Sensornetzwerk durchgeführt. Aus den Ergebnissen ist zu sehen, dass der Lokalisierungsfehler in Situationen mit niedriger Ankerknotendichte im Fall von SA-MCL um bis zu 60% reduziert werden kann, beziehungsweise um bis zu 50% im Fall von PO-MCL.

Design and Analysis of Enhanced LEACH based Energy Routing Protocol for Wireless Sensor Network

In recent times, wireless sensor networks, or WSNs, have attracted a lot of attention because of their extensive use in a variety of fields, such as industrial automation, healthcare, and environmental monitoring. Energy efficiency is a major problem for WSNs since sensor nodes frequently run on batteries and have little energy available. Effective routing techniques are essential for extending the life of the network and guaranteeing dependable data transfer. This work focuses on the performance analysis and numerical modeling of a new routing strategy that combines machine learning approaches to improve WSN energy efficiency. The suggested routing algorithm optimizes energy consumption and overall network performance by adjusting its recommendations in real-time in response to environmental and network variables. We assess this machine learning-based routing protocol's performance using large-scale numerical simulations, contrasting it with conventional routing protocols and emphasizing its possible advantages in terms of energy efficiency and dependable data delivery. We investigate a variety of situations in our simulations, taking into account different network topologies, traffic patterns, and environmental factors. We evaluate many measures, including energy consumption, network lifetime, packet delivery ratio, and end-to-end delay, in order to offer a thorough evaluation of the efficacy of the machine learning-based routing protocol. The outcomes show how energy-efficient the protocol is, guaranteeing long-lasting sensor nodes and reliable data transfer while adjusting to changing network conditions.The results of this study highlight how machine learning approaches can completely change how routing protocols are designed and optimized in wireless sensor networks with limited energy. This research helps to construct sustainable and dependable WSNs by enhancing energy efficiency and network performance, which makes it easier to deploy sensor networks in crucial applications

Efficient Low Cost Range-Based Localization Algorithm for Ad-hoc Wireless Sensors Networks

Revised version submitted to Ad Hoc NetworksBuilding an efficient node localization system in wireless sensor networks is facing several challenges. For example, calculating the square root consumes computational resources and utilizing flooding techniques to broadcast nodes location wastes bandwidth and energy. Reducing computational complexity and communication overhead is essential in order to reduce power consumption, extend the life time of the battery operated nodes, and improve the performance of the limited computational resources of these sensor nodes. In this paper, we revise the mathematical model,the analysis and the simulation experiments of the Trigonometric based Ad-hoc Localiza-tion System (TALS), a range-based localization system presented previously. Furthermore, the study is extended, and a new technique to optimize the system is proposed. An analysis and an extensive simulation for the optimized TALS (OTALS) is presented showing its cost, accuracy, and efficiency, thus deducing the impact of its parameters on performance. Hence, the contribution of this work can be summarized as follows: 1) Proposing and employing a novel modified Manhattan distance norm in the TALS localization process. 2) Analyzing and simulating of OTALS showing its computational cost and accuracy and comparing them with other related work. 3) Studying the impacts of different parameters like anchor density, node density, noisy measurements, transmission range, and non-convex network areas. 4) Extending our previous joint work, TALS, to consider base anchors to be located in positions other than the origin and analyzing this work to illustrate the possibility of selecting a wrong quadrant at the first iteration and how this problem is overcome. Through mathematical analysis and intensive simulation, OTALS proved to be iterative , distributed, and computationally simple. It presented superior performance compared to other localization techniques

Design Simulation and Perfomance Analysis of Efficient Low Energy Adaptive Clustering Hierarchy Protocol in Wireless Sensor Network

Network life has been defined by the use of nodes to store, process and distribute information, which have restricted energy usage. In other words, all aspects of the node must be designed for extremely energy-efficient applications from sensor module to hardware and protocol. Diminished energy consumption by a factor of two will increase the system's overall utility by doubling the device life. In addition, the protocols should be robust against node failures, tolerant of defects and scalable to optimise device life to minimise energy dissipation. LEACH is the first protocol for network networks that utilises hierarchical routing to enhance network life. All nodes in a network are grouped into local cluster groups, with the cluster head being one node. Although all non-cluster head nodes transmit their data to the cluster head, the cluster head node collects data from all the cluster members, conducts data signal processing (e.g. , data aggregation) functions and transmits data to the remote baseline. As a cluster-head node, it thus takes much more resources than a non-cluster-head node. So all nodes that belong to the cluster lose communication power if a cluster-head node dies. In this research, we introduced clustering as a means of overcoming this energy efficiency problem. Detailed description on the process of LEACH protocols is available. The information on the simulation and the findings have also been discussed

PENGELOMPOKAN PROFIL PEKERJAAN ALUMNI MENGGUNAKAN ALGORITMA K-MEANS

Tracer Study adalah salah satu pelacakan jejak kepada alumni yang umum dilakukan program studi di perguruan tinggi sebagai upaya dalam memperbaiki kualitas penyelenggaraan pendidikan. Terdapat beberapa kuesioner yang ditujukan kepada alumni, namun tanggapan sebagai umpan balik yang diberikan alumni masih terbilang cukup rendah. Penelitian ini bertujuan mengoptimalkan program tracer study yang dilakukan dengan cara mengelompokkan profil pekerjaan alumni agar dapat disesuaikan dengan kebutuhan penyebaran kuesioner. Metode yang digunakan dalam pengelompokkan profil pekerjaan alumni adalah clustering yang dalam penelitian ini menggunakan algoritma K-Means. Hasil dari penelitian ini adalah cluster-cluster profil pekerjaan alumni yang setiap anggota dalam cluster yang sama memiliki kriteria pekerjaan yang mirip.------------- Tracer Study is one of methods used in university to track their alumnus’ traces as an approach to improve the quality of their education management. There exist a few questionnaires aimed at the alumnus, but responses the alumnus given are still quite lacking. This research focused on optimizing tracer study program by separating alumnus’ work profiles into parts so it could suit distribution of the questionnaire. Method used to group the alumnus work profiles is clustering with the help of K Means algorithm. The aforementioned research resulting in clusters of alumnus’ work profiles in which each member of the same cluster has similar work characteristics

Virtual coordinate based techniques for wireless sensor networks: a simulation tool and localization & planarization algorithms

2013 Summer.Includes bibliographical references.Wireless sensor Networks (WSNs) are deployments of smart sensor devices for monitoring environmental or physical phenomena. These sensors have the ability to communicate with other sensors within communication range or with a base station. Each sensor, at a minimum, comprises of sensing, processing, transmission, and power units. This thesis focuses on virtual coordinate based techniques in WSNs. Virtual Coordinates (VCs) characterize each node in a network with the minimum hop distances to a set of anchor nodes, as its coordinates. It provides a compelling alternative to some of the localization applications such as routing. Building a WSN testbed is often infeasible and costly. Running real experiments on WSNs testbeds is time consuming, difficult and sometimes not feasible given the scope and size of applications. Simulation is, therefore, the most common approach for developing and testing new protocols and techniques for sensor networks. Though many general and wireless sensor network specific simulation tools are available, no available tool currently provides an intuitive interface or a tool for virtual coordinate based simulations. A simulator called VCSIM is presented which focuses specifically on Virtual Coordinate Space (VCS) in WSNs. With this simulator, a user can easily create WSNs networks of different sizes, shapes, and distributions. Its graphical user interface (GUI) facilitates placement of anchors and generation of VCs. Localization in WSNs is important for several reasons including identification and correlation of gathered data, node addressing, evaluation of nodes' density and coverage, geographic routing, object tracking, and other geographic algorithms. But due to many constraints, such as limited battery power, processing capabilities, hardware costs, and measurement errors, localization still remains a hard problem in WSNs. In certain applications, such as security sensors for intrusion detection, agriculture, land monitoring, and fire alarm sensors in a building, the sensor nodes are always deployed in an orderly fashion, in contrast to random deployments. In this thesis, a novel transformation is presented to obtain position of nodes from VCs in rectangular, hexagonal and triangular grid topologies. It is shown that with certain specific anchor placements, a location of a node can be accurately approximated, if the length of a shortest path in given topology between a node and anchors is equal to length of a shortest path in full topology (i.e. a topology without any voids) between the same node and anchors. These positions are obtained without the need of any extra localization hardware. The results show that more than 90% nodes were able to identify their position in randomly deployed networks of 80% and 85% node density. These positions can then be used for deterministic routing which seems to have better avg. path length compared to geographic routing scheme called "Greedy Perimeter Stateless Routing (GPSR)". In many real world applications, manual deployment is not possible in exact regular rectangular, triangular or hexagonal grids. Due to placement constraint, nodes are often placed with some deviation from ideal grid positions. Because of placement tolerance and due to non-isotropic radio patterns nodes may communicate with more or less number of neighbors than needed and may form cross-links causing non-planar topologies. Extracting planar graph from network topologies is known as network planarization. Network planarization has been an important technique in numerous sensor network protocols--such as GPSR for efficient routing, topology discovery, localization and data-centric storage. Most of the present planarization algorithms are based on location information. In this thesis, a novel network planarization algorithm is presented for rectangular, hexagonal and triangular topologies which do not use location information. The results presented in this thesis show that with placement errors of up to 30%, 45%, and 30% in rectangular, triangular and hexagonal topologies respectively we can obtain good planar topologies without the need of location information. It is also shown that with obtained planar topology more nodes acquire unique VCs

Reducing energy consumption in mobile ad-hoc sensor networks

PhD ThesisRecent rapid development of wireless communication technologies and portable mobile devices such as tablets, smartphones and wireless sensors bring the best out of mobile computing, particularly Mobile Ad-hoc Sensor Networks (MASNETs). MASNETs are types of Mobile Ad-hoc Networks (MANETs) that are designed to consider energy in mind because they have severe resource constraints due to their lack of processing power, limited memory, and bandwidth as in Wireless Sensor Networks (WSNs). Hence, they have the characteristics, requirements, and limitations of both MANETs and WSNs. There are many potential applications of MASNETs such as a real-time target tracking and an ocean temperature monitoring. In these applications, mobility is the fundamental characteristic of the sensor nodes, and it poses many challenges to the routing algorithm. One of the greatest challenge is to provide a routing algorithm that is capable of dynamically changing its topology in the mobile environment with minimal consumption of energy. In MASNETs, the main reason of the topology change is because of the movement of mobile sensor nodes and not the node failure due to energy depletion. Since these sensor nodes are limited in power supply and have low radio frequency coverage, they easily lose their connection with neighbours, and face diffi culties in updating their routing tables. The switching process from one coverage area to another consumes more energy. This network must be able to adaptively alter the routing paths to minimize the effects of variable wireless link quality, topological changes, and transmission power levels on energy consumption of the network. Hence, nodes prefer to use as little transmission power as necessary and transmit control packets as infrequently as possible in energy constrained MASNETs. Therefore, in this thesis we propose a new dynamic energy-aware routing algorithm based on the trans- mission power control (TPC). This method effectively decreases the average percentage of packet loss and reduces the average total energy consumption which indirectly pro- long the network lifetime of MASNETs. To validate the proposed protocol, we ran the simulation on the Avrora simulator and varied speed, density, and route update interval of mobile nodes. Finally, the performance of the proposed routing algorithm was measured and compared against the basic Ad-hoc On-demand Distance Vector (AODV) routing algorithm in MASNETs.The Ministry of Education of Malaysia: The Universiti Malaysia Sarawak