Architecture of a large scale location service

Many mobile applications require some knowledge about the current geographic locations of the mobile objects involved. Therefore, services exist that can store and retrieve the position of mobile objects in an efficient and scalable way. More advanced location-aware applications, however, require additional functionality, like determining all mobile objects inside a certain geographic area (range query). This functionality is not supported by existing services on a large scale yet. In this paper, we present a generic large-scale location service. We describe the location service model, defining the semantics of position, range and nearest neighbor queries. A hierarchical distributed architecture is presented, which can efficiently process these queries, and the structure of a main-memory database for efficiently storing and retrieving position information on a location server. Finally, through measurements on a first prototype of this architecture, we show the feasibility of such a location service

Processing continuous range queries with spatiotemporal tolerance

Continuous queries are often employed to monitor the locations of mobile objects (MOs), which are determined by sensing devices like GPS receivers. In this paper, we tackle two challenges in processing continuous range queries (CRQs): coping with data uncertainty inherently associated with location data, and reducing the energy consumption of battery-powered MOs. We propose the concept of spatiotemporal tolerance for CRQ to relax a query's accuracy requirements in terms of a maximal acceptable error. Unlike previous works, our definition considers tolerance in both the spatial and temporal dimensions, which offers applications more flexibility in specifying their individual accuracy requirements. As we will show, these tolerance bounds can provide well-defined query semantics in spite of different sources of data uncertainty. In addition, we present efficient algorithms that carefully control when an MO should sense or report a location, while satisfying these tolerances. Thereby, we particularly reduce the number of position sensing operations substantially, which constitute a considerable source of energy consumption. Extensive simulations confirm that the proposed algorithms result in large energy savings compared to nontolerant query processing. © 2006 IEEE.published_or_final_versio

A map-based dead reckoning protocol for updating location information

An important aspect of location-aware services is the management of location information. To this end, location information needs to be transferred from a mobile device, which determines this information by means of a local positioning sensor (such as GPS), to a location service, where the location information can be queried by applications. Because bandwidth in wide area mobile communications is still scarce and expensive, it is important to use an update protocol that requires as few messages as possible while still guaranteeing a desired accuracy of the location information. To decrease the number of necessary update messages, so-called dead-reckoning strategies have been proposed. In this paper we give an overview of different variants of dead-reckoning protocols for updating location information and propose a new map-based protocol. While a simple dead-reckoning protocol already reduces the number of update messages by up to 83, the map-based protocol further reduces their number by again up to 60

A Line-Of-Slight Sensor Network for Wide Area Video Surveillance: Simulation and Evaluation

Substantial performance improvement of a wide area video surveillance network can be obtained with the addition of a Line-of-Sight sensor. The research described in this thesis shows that while the Line-of-Sight sensor cannot monitor areas with the ubiquity of video cameras alone, the combined network produces substantially fewer false alarms and superior location precision for numerous moving people than video. Recent progress in the fabrication of inexpensive, robust CMOS-based video cameras have triggered a new approach to wide area surveillance of busy areas such as modeling an airport corridor as a distributed sensor network problem. Wireless communication between these cameras and other sensors make it more practical to deploy them in an arbitrary spatial configuration to unobtrusively monitor cooperative and non-cooperative people. The computation and communication to establish image registration between the cameras grows rapidly as the number of cameras increases. Computation is required to detect people in each image, establish a correspondence between people in two or more images, compute exact 3-D positions from each corresponding pair, temporally track targets in space and time, and assimilate resultant data until thresholds have been reached to either cause an alarm or abandon further monitoring of that person. Substantial improvement can be obtained with the addition of a Line-of-Sight sensor as a location detection system to decoupling the detection, localization, and identification subtasks. That is, if the where can be answered by a location detection system, the what can be addressed by the video most effectively

Event management for mobile users

This technical report presents the results of the project "Event Management for Mobile Users", a research cooperation between Universität Stuttgart and Microsoft. In Vienna, Microsoft chief executive Bill Gates recently expressed his vision of a seamless interaction of different computing devices, from PC to mobile phone, that proactively support the users wherever they go. Among other things, he said: "For example, if you want to be notified about something that's changing, that's important to you, software should know which device you have with you and should know what you're doing, know the context to understand if interrupting you with this new information is appropriate or not." (Bill Gates, January 28, 2004, [Los Angeles Times 2004]) This project may present one step towards realizing his vision. It is about event support for mobile users. Depending on their current context, they want to be informed about events that occur in the world around them - the physical as well as the virtual world of digital information systems. So, to optimally support its users, future generations of web services will need information about the real-world context of the user, especially their spatial context. This project was carried out in close cooperation with the Nexus project at Universität Stuttgart, whose goal is to support mobile context-aware applications based on a distributed spatial world model. Events of special interest in this context are spatial events, i.e. events that occur when a certain spatial constellation of objects is reached, e.g. when two people meet or when a customer enters a shopping mall. As the underlying world model is distributed, the events have to be observed on a distributed model. The number of potential spatial events is not restricted, e.g. the event that a user enters an area could be of interest for arbitrary areas. Also, as the spatial world model is distributed over many servers, a local observation is no longer sufficient. Therefore, the well-known publish-subscribe paradigm, in which the observation occurs implicitly within local observers, has to be extended. We propose an observation-notification paradigm, in which the observation of events has to be explicitly initiated by interested clients. The event service that conforms to the new paradigm consists of two components: an observation service, which observes events through a distributed model, and a notification service, which efficiently delivers event notifications. This paradigm applies to all scenarios in which the data needed for the observation of events is distributed over multiple sources. The user wants the specification of events to be as simple and easy as possible. He only wants to specify what event is to be observed, not how the observation of the event is realized. Therefore the distribution aspects should be transparent to the user. However, these aspects have a strong influence on the accuracy of the model and thereby directly affect the accuracy of event observation. We propose that the user specifies an event as a predicate, which becomes true when the event has occurred, plus a threshold probability. If the probability that the event has occurred is above the threshold probability, the event is considered to have occurred and an event notification is sent. The above sketched solution requires calculating the probability with which an event has occurred. We first show which parameters influence the accuracy of the data. We then present update protocols that guarantee a certain accuracy of data in the observer model, i.e. the model where the event is actually observed. Finally we show, how the occurrence probability can be calculated. Based on the identified parameters, the placement of the observation in the system can also be optimized with regard to the accuracy of the data. We have implemented the event service and integrated it into the Nexus platform. As the Nexus platform is intended as an open platform with possibly world-wide scale, scalability, efficiency and interoperability have been important requirements for the design of the components. To support interoperability, we have built on standard technologies like XML, HTTP and SOAP. The evaluation of the event service within the Nexus context shows the feasibility of the approach. We were able to show that the event service performs adequately in certain example scenarios. Experiments with a large-scale scenario are the next steps on our agenda

Sequencing geographical data for efficient query processing on air in mobile computing.

Three cost models are derived to measure Data Broadcast Wait (DBW), Data Access Time in the multiplexing scheme (ATDataMul) where both data and indices are broadcast in the same channel, and Data Access Time in the separate channel scheme (ATDataSep) where data and indices are broadcast in two separate channels. Hypergraph representations are used to represent the spatial relationships of both point data and graph data. The broadcast data placement problem is then converted to the graph layout problem. A framework for classifying ordering heuristics for different types of geographical data is presented. A low-polynomial cost approximation graph layout method is used to solve the DBW minimization problem. Based on the proven monotonic relationship between ATData Sep and DBW, the same approximation method is also used for AT DataSep optimization. A novel method is developed to optimize ATDataMul. Experiments using both synthetic and real data are conducted to evaluate the performance of the ordering heuristics and optimization methods. The results show that R-Tree traversal ordering heuristic in conjunction with the optimization methods is effective for sequencing point data for spatial range query processing, while graph partition tree traversal ordering heuristic in conjunction with the optimization methods is suitable for sequencing graph data for network path query processing over air.Geographical data broadcasting is suitable for many large scale dissemination-based applications due to its independence of number of users, and thus it can serve as an important part of intelligent information infrastructures for modern cities. In broadcast systems, query response time is greatly affected by the order in which data items are being broadcast. However, existing broadcast ordering techniques are not suitable for geographical data because of the multi-dimension and rich semantics of geographical data. This research develops cost models and methods for placing geographical data items in a broadcast channel based on their spatial semantics to reduce response time and energy consumption for processing spatial queries on point data and graph data

Mobility-awareness in complex event processing systems

The proliferation and vast deployment of mobile devices and sensors over the last couple of years enables a huge number of Mobile Situation Awareness (MSA) applications. These applications need to react in near real-time to situations in the environment of mobile objects like vehicles, pedestrians, or cargo. To this end, Complex Event Processing (CEP) is becoming increasingly important as it allows to scalably detect situations “on-the-fly” by continously processing distributed sensor data streams. Furthermore, recent trends in communication networks promise high real-time conformance to CEP systems by processing sensor data streams on distributed computing resources at the edge of the network, where low network latencies can be achieved. Yet, supporting MSA applications with a CEP middleware that utilizes distributed computing resources proves to be challenging due to the dynamics of mobile devices and sensors. In particular, situations need to be efficiently, scalably, and consistently detected with respect to ever-changing sensors in the environment of a mobile object. Moreover, the computing resources that provide low latencies change with the access points of mobile devices and sensors. The goal of this thesis is to provide concepts and algorithms to i) continuously detect situations that recently occurred close to a mobile object, ii) support bandwidth and computational efficient detections of such situations on distributed computing resources, and iii) support consistent, low latency, and high quality detections of such situations. To this end, we introduce the distributed Mobile CEP (MCEP) system which automatically adapts the processing of sensor data streams according to a mobile object’s location. MCEP provides an expressive, location-aware query model for situations that recently occurred at a location close to a mobile object. MCEP significantly reduces latency, bandwidth, and processing overhead by providing on-demand and opportunistic adaptation algorithms to dynamically assign event streams to queries of the MCEP system. Moreover, MCEP incorporates algorithms to adapt the deployment of MCEP queries in a network of computing resources. This way, MCEP supports latency-sensitive, large-scale deployments of MSA applications and ensures a low network utilization while mobile objects change their access points to the system. MCEP also provides methods to increase the scalability in terms of deployed MCEP queries by reusing event streams and computations for detecting common situations for several mobile objects

Architecture of a Large-scale Location Service

Many mobile applications require some knowledge about the current geographic locations of the mobile objects involved. Therefore, services exist that can store and retrieve the position of mobile objects in an efficient and scalable way. More advanced location-aware applications, however, require additional functionality, like determining all mobile objects inside a certain geographic area (range query). This functionality is not supported by existing services on a large scale yet. In this paper, we present a generic large-scale location service. We describe the location service model, defining the semantics of position, range and nearest neighbor queries. A hierarchical distributed architecture is presented, which can efficiently process these queries, and the structure of a main-memory database for efficiently storing and retrieving position information on a location server. Finally, through measurements on a first prototype of this architecture, we show the feasibility of such a location service