Database replication is widely known and used for high availability or load balancing in many practical database systems. In this paper, we show how a replication engine can be used for three important practical cases that have not previously been studied very well. The three practical use cases include: 1) scaling out OLTP/OLAP-mixed workloads with partitioned replicas, 2) efficiently maintaining a distributed secondary index for a partitioned table, and 3) efficiently implementing an online re-partitioning operation. All three use cases are crucial for enabling a high-performance shared-nothing distributed database system. To support the three use cases more efficiently, we propose the concept of asymmetric-partition replication , so that replicas of a table can be independently partitioned regardless of whether or how its primary copy is partitioned. In addition, we propose the optimistic synchronous commit protocol which avoids the expensive two-phase commit without sacrificing transactional consistency. The proposed asymmetric-partition replication and its optimized commit protocol are incorporated in the production versions of the SAP HANA in-memory database system. Through extensive experiments, we demonstrate the significant benefits that the proposed replication engine brings to the three use cases.

GNSS (Global Navigation Satellite System) supported navigation with smartphones is an established technique. Solutions for position estimation for GNSS-shaded areas are developed more and more in the research field of the indoor navigation. The MEMS (MicroElectroMechanical Systems) sensors integrated into smartphones will be used increasingly for this. The aim of the research group at the HCU is the autonomous navigation only with MEMS sensors, favors are accelerometer, gyroscope and barometer. The quality of MEMS inertial sensors based position estimate decreases with time. Additional information should be used as support which is a prerequisite to realize a navigation application. A support is therefore possible with the available map data or the routing graph. In most approaches, the low-cost sensors are fused with the help of particle filter and Kalman filter at present. This serves the simple integration of external support, such as maps. In this work an approach without these filters is presented. A position estimate based on the routing nodes and edges shall be realized, only with the integrated MEMS inertial sensors in the smartphone. A fusion with further supports is not provided. The position estimate is calculated on the path network which is normally the basis for the routing to calculate the path. The position on a routing edge is derived from the acceleration sensors and the gyroscopes with step detection and orientation comparison. At a routing node, the sensor data is used to choose the probably nearest routing edge. For comparison purposes, approaches with Kalman filter and particle filter are applied to the same data set.

In the art scene, low-cost sensors like Arduino are often being used to create or support a range of different effects. Live-Art installations must be often made very favorably due to low budget. In this article the function of a module for orientation is being described as it works in an artistic project, a Ph.D. - thesis is based on. The project is based on different people's memories and stories. “Museum of the moment” deals with the aesthetic effects of performative collections such as the various visual animations of people's memories. Different people are being videotaped while describing important moments in their lives. These portraits are being presented on large screens in the gallery. The viewers equipped with radio-controlled headphones look at the images and also listen to the different stories, not necessarily knowing who of the portrayed people has told which story. The orientation module based on the Arduino is supposed to identify the screen automatically and communicate with the acoustic server, in order to create the effect, that only the screen, that is being looked at by the viewer will trigger an acoustic signal which is the story that the viewer can listen to. Arduino is being used in this setting to enable orientation in the gallery space in the first place. Secondly, it makes sure to identify positions. Arduino-Nanos with a MPU 9150 are being used. These include an accelerometer, gyroscope and magnetic field sensor. To set and identify positions Wi-Fi is being used. Therefore signal strength and fingerprinting algorithms were examined. The final configuration of the screens does not necessarily need an estimation of position.

Global Navigation Satellite Systems (GNSS)-based navigation with smartphones is very popular. But in areas where no GNSS signal is found navigation could be useful. Examples are navigation in shopping malls, in big offices, in train stations or museums. The goal is to estimate the position in GNSS shaded areas to make navigation possible. The MEMS sensors (Micro Electro Mechanical System) installed in current smartphones, such as accelerometer, gyroscope, magnetic field sensor and barometer allow now navigation also in GNSS shadowed areas. Due to the low quality of these sensors, however, support of the position estimate is needed. In this work, a concept is presented for the construction of an indoor navigation system based on low-cost sensors of smartphones. The position estimate from the available sensor data forms the basis of the position determination. So position estimation is always possible independent of location. First results with Kalman filter and particle filter are shown. The presented concept serves as a basis for the construction of a smartphone-based navigation solution for indoor use. Therefore the available MEMS sensors should be used as a position estimator and a wide variety of supporting information can be processed. A first approach for implementation on a smartphone is shown as an example.

The HafenCity University has been working for quite some time with the possibilities for indoor positioning with the focus on the use of current smartphones. Latest smartphones, as in this paper the Samsung Galaxy Nexus, include necessary sensors for relative positioning. These sensors will be analyzed before implementing an indoor navigation by using a smartphone. Hereinafter the gyroscope and the barometer are investigated. An approach for the calibration of the gyroscopes using a total station as well as a view on the possibility of storey detection via air pressure measurements will be shown in the following.