Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past two decades. Most radio-based solutions require a process of site survey, in which radio signatures are collected and stored for further comparison and matching. Site survey involves intensive costs on manpower and time. In this work, we study unexploited RF signal characteristics and leverage user motions to construct radio floor plan that is previously obtained by site survey. On this basis, we design WILL, an indoor localization approach based on off-the-shelf WiFi infrastructure and mobile phones. WILL is deployed in a real building covering over 1600 m2, and its deployment is easy and rapid since site survey is no longer needed. The experiment results show that WILL achieves competitive performance comparing with traditional approaches.

WILL: Wireless Indoor Localization without Site Survey

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints on cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use mobile anchor nodes (MANs), which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. A considerable body of research has addressed the mobile anchor node assisted localization (MANAL) problem. However, to the best of our knowledge, no updated surveys on MAAL reflecting recent advances in the field have been presented in the past few years. This survey presents a review of the most successful MANAL algorithms, focusing on the achievements made in the past decade, and aims to become a starting point for researchers who are initiating their endeavors in MANAL research field. In addition, we seek to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful advances in this research field.

/pdf/a-survey-on-mobile-anchor-node-assisted-localization-in-cye1ebv78f.pdf

A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks

Indoor localization is of great importance for a range of pervasive applications, attracting many research efforts in the past two decades. Most radio-based solutions require a process of site survey, in which radio signatures are collected and stored for further comparison and matching. Site survey involves intensive costs on manpower and time. In this work, we study unexploited RF signal characteristics and leverage user motions to construct radio floor plan that is previously obtained by site survey. On this basis, we design WILL, an indoor localization approach based on off-the-shelf WiFi infrastructure and mobile phones. WILL is deployed in a real building covering over 1600m2, and its deployment is easy and rapid since site survey is no longer needed. The experiment results show that WILL achieves competitive performance comparing with traditional approaches.

/pdf/will-wireless-indoor-localization-without-site-survey-srk10dfb4s.pdf

WILL: Wireless indoor localization without site survey

Localization is an important aspect in the field of wireless sensor networks (WSNs) that has developed significant research interest among academia and research community. Wireless sensor network is formed by a large number of tiny, low energy, limited processing capability and low-cost sensors that communicate with each other in ad-hoc fashion. The task of determining physical coordinates of sensor nodes in WSNs is known as localization or positioning and is a key factor in today’s communication systems to estimate the place of origin of events. As the requirement of the positioning accuracy for different applications varies, different localization methods are used in different applications and there are several challenges in some special scenarios such as forest fire detection. In this paper, we survey different measurement techniques and strategies for range based and range free localization with an emphasis on the latter. Further, we discuss different localization-based applications, where the estimation of the location information is crucial. Finally, a comprehensive discussion of the challenges such as accuracy, cost, complexity, and scalability are given.

Localization in Wireless Sensor Networks: A Survey on Algorithms, Measurement Techniques, Applications and Challenges

Internet of Things (IoT) is a novel design paradigm, intended as a network of billions to trillions of tiny sensors communicating with each other to offer innovative solutions to real time problems. These sensors form a network named as wireless sensor networks (WSNs) to monitor physical environment and disseminate collected data back to the base station through multiple hops. WSN has the capability to collect and report data for a specific application. The location information plays an important role for various wireless sensor network applications. A majority of the applications are related to location-based services. The development of sensor technology, processing techniques, and communication systems give rise to a development of the smart sensor for the adaptive and innovative application. So a single localization technique is not adequate for all application. In this paper, a recent extensive analysis of localization techniques and hierarchical taxonomy and their applications in the different context is presented. This taxonomy of the localization technique is classified based on presence of offline training in localization, namely self-determining and training dependent approaches. Finally, various open research issues related to localization schemes for IoT are compared and various directions for future research are proposed.

Location of Things (LoT): A Review and Taxonomy of Sensors Localization in IoT Infrastructure

Generalization is a well-known method for privacy preserving data publication. Despite its vast popularity, it has several drawbacks such as heavy information loss, difficulty of supporting marginal publication, and so on. To overcome these drawbacks, we develop ANGEL,1 a new anonymization technique that is as effective as generalization in privacy protection, but is able to retain significantly more information in the microdata. ANGEL is applicable to any monotonic principles (e.g., l-diversity, t-closeness, etc.), with its superiority (in correlation preservation) especially obvious when tight privacy control must be enforced. We show that ANGEL lends itself elegantly to the hard problem of marginal publication. In particular, unlike generalization that can release only restricted marginals, our technique can be easily used to publish any marginals with strong privacy guarantees.

ANGEL: Enhancing the Utility of Generalization for Privacy Preserving Publication

The localization of the sensor node is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from a GPS device or by virtue of being manually placed. In this paper, we propose two distributed methods to localization of sensor nodes using a single moving beacon where sensor nodes compute their position estimate based on the range-free technique. The first method uses the arrival and departure information of a walking beacon and the second method exploits the variance of the received signal strength (RSS) from the beacon. We provide the upper bound of the estimation error for these methods in an ideal environment. Critical to the location accuracy of sensor nodes are two more parameters, the radio transmission range of the beacon, and how often the beacon broadcasts its position. Simulation results show the location estimate error of sensor nodes applying the proposed two methods. The results are consistent to the theoretical analysis and the average estimate errors could be within one meter.

/pdf/a-walking-beacon-assisted-localization-in-wireless-sensor-3lfsp5mean.pdf

A Walking Beacon-Assisted Localization in Wireless Sensor Networks

Skyline computation is a hot topic in database community due to its promising application in multi-criteria decision making. In sensor network application scenarios, skyline is still useful and important in environment monitoring, industry control, etc. To support energy-efficient skyline monitoring in sensor networks, this paper first presents a naive approach as baseline, and then proposes an advanced approach that employs hierarchical thresholds at the nodes. The threshold-based approach focuses on minimizing the transmission traffic in the network to save the energy consumption. Finally, we conduct extensive experiments to evaluate the proposed approaches on simulated data sets, and compare the threshold-based approach with the naive approach. Experimental results show that the proposed threshold-based approach outperforms the naive approach substantially in energy saving.

Towards energy-efficient skyline monitoring in wireless sensor networks

The construction of backbone is a fundamental problem in sensor networks. As being critical to routing, data fusion and query broadcasting, the backbone should contain as fewer nodes as possible. Meanwhile, it also should be power-efficient in order to prolong its lifetime. In this paper, we propose a novel design of backbone for sensor networks by minimizing its total transmission cost. We term this kind of backbone Minimum-Weight Backbone (simply MWB). The construction of MWB is proved to be NP-Complete. Two heuristic algorithms (one is centralized and the other is distributed) are developed for constructing such backbone. The centralized algorithm, executed at the base station, is to find an optimal backbone by using the information of all nodes and links in the network. The distributed algorithm run at each node, however, uses the information of its neighbors and two-hop neighbors to determine whether it should be included in the backbone. Simulated experiments are conducted to evaluate the novel backbone, and performance comparisons are also done with the existing schemes.

/pdf/a-novel-energy-efficient-backbone-for-sensor-networks-51b4tqjf5r.pdf

A novel energy-efficient backbone for sensor networks

The localization of sensor nodes is a fundamental problem in sensor networks and can be implemented using powerful and expensive beacons. Beacons, the fewer the better, can acquire their position knowledge either from GPS devices or by virtue of being manually placed. In this paper, we propose a distributed method to localization of sensor nodes using a single moving beacon, where sensor nodes compute their position estimate based on the range-free technique. Two parameters are critical to the location accuracy of sensor nodes: the radio transmission range of the beacon and how often the beacon broadcasts its position. Theoretical analysis shows that these two parameters determine the upper bound of the estimation error when the traverse route of the beacon is a straight line. We extend the position estimate when the traverse route of the beacon is randomly chosen in a real-world situation, where the radio irregularity might cause a node to miss some crucial coordinate information from the beacon. We further point out that the movement pattern of the beacon plays a pivotal role in the localization task for sensors. To minimize estimation errors, sensor nodes can carry out a variety of algorithms in accordance with the movement of the beacon. Simulation results compare variants of the distributed method in a variety of testing environments. Real experiments show that the proposed method is feasible and can estimate the location of sensor nodes accurately, given a single moving beacon.

/pdf/distributed-localization-using-a-moving-beacon-in-wireless-f48xjcyb8a.pdf

Distributed Localization Using a Moving Beacon in Wireless Sensor Networks

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