25,687 research outputs found
Localization in Long-range Ultra Narrow Band IoT Networks using RSSI
Internet of things wireless networking with long range, low power and low
throughput is raising as a new paradigm enabling to connect trillions of
devices efficiently. In such networks with low power and bandwidth devices,
localization becomes more challenging. In this work we take a closer look at
the underlying aspects of received signal strength indicator (RSSI) based
localization in UNB long-range IoT networks such as Sigfox. Firstly, the RSSI
has been used for fingerprinting localization where RSSI measurements of GPS
anchor nodes have been used as landmarks to classify other nodes into one of
the GPS nodes classes. Through measurements we show that a location
classification accuracy of 100% is achieved when the classes of nodes are
isolated. When classes are approaching each other, our measurements show that
we can still achieve an accuracy of 85%. Furthermore, when the density of the
GPS nodes is increasing, we can rely on peer-to-peer triangulation and thus
improve the possibility of localizing nodes with an error less than 20m from
20% to more than 60% of the nodes in our measurement scenario. 90% of the nodes
is localized with an error of less than 50m in our experiment with
non-optimized anchor node locations.Comment: Accepted in ICC 17. To be presented in IEEE International Conference
on Communications (ICC), Paris, France, 201
User Review-Based Change File Localization for Mobile Applications
In the current mobile app development, novel and emerging DevOps practices
(e.g., Continuous Delivery, Integration, and user feedback analysis) and tools
are becoming more widespread. For instance, the integration of user feedback
(provided in the form of user reviews) in the software release cycle represents
a valuable asset for the maintenance and evolution of mobile apps. To fully
make use of these assets, it is highly desirable for developers to establish
semantic links between the user reviews and the software artefacts to be
changed (e.g., source code and documentation), and thus to localize the
potential files to change for addressing the user feedback. In this paper, we
propose RISING (Review Integration via claSsification, clusterIng, and
linkiNG), an automated approach to support the continuous integration of user
feedback via classification, clustering, and linking of user reviews. RISING
leverages domain-specific constraint information and semi-supervised learning
to group user reviews into multiple fine-grained clusters concerning similar
users' requests. Then, by combining the textual information from both commit
messages and source code, it automatically localizes potential change files to
accommodate the users' requests. Our empirical studies demonstrate that the
proposed approach outperforms the state-of-the-art baseline work in terms of
clustering and localization accuracy, and thus produces more reliable results.Comment: 15 pages, 3 figures, 8 table
Space-Time Hierarchical-Graph Based Cooperative Localization in Wireless Sensor Networks
It has been shown that cooperative localization is capable of improving both
the positioning accuracy and coverage in scenarios where the global positioning
system (GPS) has a poor performance. However, due to its potentially excessive
computational complexity, at the time of writing the application of cooperative
localization remains limited in practice. In this paper, we address the
efficient cooperative positioning problem in wireless sensor networks. A
space-time hierarchical-graph based scheme exhibiting fast convergence is
proposed for localizing the agent nodes. In contrast to conventional methods,
agent nodes are divided into different layers with the aid of the space-time
hierarchical-model and their positions are estimated gradually. In particular,
an information propagation rule is conceived upon considering the quality of
positional information. According to the rule, the information always
propagates from the upper layers to a certain lower layer and the message
passing process is further optimized at each layer. Hence, the potential error
propagation can be mitigated. Additionally, both position estimation and
position broadcasting are carried out by the sensor nodes. Furthermore, a
sensor activation mechanism is conceived, which is capable of significantly
reducing both the energy consumption and the network traffic overhead incurred
by the localization process. The analytical and numerical results provided
demonstrate the superiority of our space-time hierarchical-graph based
cooperative localization scheme over the benchmarking schemes considered.Comment: 14 pages, 15 figures, 4 tables, accepted to appear on IEEE
Transactions on Signal Processing, Sept. 201
STCP: Receiver-agnostic Communication Enabled by Space-Time Cloud Pointers
Department of Electrical and Computer Engineering (Computer Engineering)During the last decade, mobile communication technologies have rapidly evolved and ubiquitous network connectivity is nearly achieved. However, we observe that there are critical situations where none of the existing mobile communication technologies is usable. Such situations are often found when messages need to be delivered to arbitrary persons or devices that are located in a specific space at a specific time. For instance at a disaster scene, current communication methods are incapable of delivering messages of a rescuer to the group of people at a specific area even when their cellular connections are alive because the rescuer cannot specify the receivers of the messages. We name this as receiver-unknown problem and propose a viable solution called SpaceMessaging. SpaceMessaging adopts the idea of Post-it by which we casually deliver our messages to a person who happens to visit a location at a random moment. To enable SpaceMessaging, we realize the concept of posting messages to a space by implementing cloud-pointers at a cloud server to which messages can be posted and from which messages can fetched by arbitrary mobile devices that are located at that space. Our Android-based prototype of SpaceMessaging, which particularly maps a cloud-pointer to a WiFi signal fingerprint captured from mobile devices, demonstrates that it first allows mobile devices to deliver messages to a specific space and to listen to the messages of a specific space in a highly accurate manner (with more than 90% of Recall)
WLAN Location Sharing through a Privacy Observant Architecture
In the last few years, WLAN has seen immense growth and it will continue this trend due to the fact that it provides convenient connectivity as well as high speed links. Furthermore, the infrastructure already exists in most public places and is cheap to extend. These advantages, together with the fact that WLAN covers a large area and is not restricted to line of sight, have led to developing many WLAN localization techniques and applications based on them. In this paper we present a novel calibration-free localization technique using the existing WLAN infrastructure that enables conference participants to determine their location without the need of a centralized system. The evaluation results illustrate the superiority of our technique compared to existing methods. In addition, we present a privacy observant architecture to share location information. We handle both the location of people and the resources in the infrastructure as services, which can be easily discovered and used. An important design issue for us was to avoid tracking people and giving the users control over who they share their location information with and under which conditions
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