Kristian Torp

Effective timestamping in databases

Abstract. Many existing database applications place various timestamps on their data, rendering temporal values such as dates and times prevalent in database tables. During the past two decades, several dozen temporal data models have appeared, all with timestamps being integral components. The models have used timestamps for encoding two specific temporal aspects of database facts, namely transaction time, when the facts are current in the database, and valid time, when the facts are true in the modeled reality. However, with few exceptions, the assignment of timestamp values has been considered only in the context of individual modification statements.This paper takes the next logical step: It considers the use of timestamping for capturing transaction and valid time in the context of transactions. The paper initially identifies and analyzes several problems with straightforward timestamping, then proceeds to propose a variety of techniques aimed at solving these problems. Timestamping the results of a transaction with the commit time of the transaction is a promising approach. The paper studies how this timestamping may be done using a spectrum of techniques. While many database facts are valid until now, the current time, this value is absent from the existing temporal types. Techniques that address this problem using different substitute values are presented. Using a stratum architecture, the performance of the different proposed techniques are studied. Although querying and modifying time-varying data is accompanied by a number of subtle problems, we present a comprehensive approach that provides application programmers with simple, consistent, and efficient support for modifying bitemporal databases in the context of user transactions.

EcoMark 2.0: empowering eco-routing with vehicular environmental models and actual vehicle fuel consumption data

Eco-routing is a simple yet effective approach to substantially reducing the environmental impact, e.g., fuel consumption and greenhouse gas (GHG) emissions, of vehicular transportation. Eco-routing relies on the ability to reliably quantify the environmental impact of vehicles as they travel in a spatial network. The procedure of quantifying such vehicular impact for road segments of a spatial network is called eco-weight assignment. EcoMark 2.0 proposes a general framework for eco-weight assignment to enable eco-routing. It studies the abilities of six instantaneous and five aggregated models to estimating vehicular environmental impact. In doing so, it utilizes travel information derived from GPS trajectories (i.e., velocities and accelerations) and actual fuel consumption data obtained from vehicles. The framework covers analyses of actual fuel consumption, impact model calibration, and experiments for assessing the utility of the impact models in assigning eco-weights. The application of EcoMark 2.0 indicates that the instantaneous model EMIT and the aggregated model SIDRA-Running are suitable for assigning eco-weights under varying circumstances. In contrast, other instantaneous models should not be used for assigning eco-weights, and other aggregated models can be used for assigning eco-weights under certain circumstances.

EcoTour: Reducing the Environmental Footprint of Vehicles Using Eco-routes

Reduction in greenhouse gas emissions from transportation is essential in combating global warming and climate change. Eco-routing enables drivers to use the most eco-friendly routes and is effective in reducing vehicle emissions. The EcoTour system assigns eco-weights to a road network based on GPS and fuel consumption data collected from vehicles to enable ecorouting. Given an arbitrary source-destination pair in Denmark, EcoTour returns the shortest route, the fastest route, and the eco-route, along with statistics for the three routes. EcoTour also serves as a testbed for exploring advanced solutions to a range of challenges related to eco-routing.

Stratum approaches to temporal DBMS implementation

Previous approaches to implementing temporal DBMSs have assumed that a temporal DBMS must be built from scratch, employing an integrated architecture and using new temporal implementation techniques such as temporal indexes and join algorithms. However, this is a very large and time-consuming task. The paper explores approaches to implementing a temporal DBMS as a stratum on top of an existing non-temporal DBMS, rendering implementation more feasible by reusing much of the functionality of the underlying conventional DBMS. More specifically, the paper introduces three stratum meta-architectures, each with several specific architectures. Based on a new set of evaluation criteria, advantages and disadvantages of the specific architectures are identified. The paper also classifies all existing temporal DBMS implementations according to the specific architectures they, employ. It is concluded that a stratum architecture is the best short, medium, and perhaps even long-term, approach to implementing a temporal DBMS.

EcoSky: Reducing vehicular environmental impact through eco-routing

Reduction in greenhouse gas emissions from transportation attracts increasing interest from governments, fleet managers, and individual drivers. Eco-routing, which enables drivers to use eco-friendly routes, is a simple and effective approach to reducing emissions from transportation. We present EcoSky, a system that annotates edges of a road network with time dependent and uncertain eco-weights using GPS data and that supports different types of eco-routing. Basic eco-routing returns the most eco-friendly routes; skyline eco-routing takes into account not only fuel consumption but also travel time and distance when computing eco-routes; and personalized eco-routing considers each drivers past behavior and accordingly suggests different routes to different drivers.

Path-based queries on trajectory data

In traffic research, management, and planning a number of path-based analyses are heavily used, e.g., for computing turn-times, evaluating green waves, or studying traffic flow. These analyses require retrieving the trajectories that follow the full path being analyzed. Existing path queries cannot sufficiently support such path-based analyses because they retrieve all trajectories that touch any edge in the path. In this paper, we define and formalize the strict path query. This is a novel query type tailored to support path-based analysis, where trajectories must follow all edges in the path. To efficiently support strict path queries, we present a novel NET work-constrained TRAjectory index (NETTRA). This index enables very efficient retrieval of trajectories that follow a specific path, i.e., strict path queries. NETTRA uses a new path encoding scheme that can determine if a trajectory follows a specific path by only retrieving data from the first and last edge in the path. To correctly answer strict path queries existing network-constrained trajectory indexes must retrieve data from all edges in the path. An extensive performance study of NETTRA using a very large real-world trajectory data set, consisting of 1.7 million trajectories (941 million GPS records) and a road network with 1.3 million edges, shows a speed-up of two orders of magnitude compared to state-of-the-art trajectory indexes.

Layered Temporal DBMS: Concepts and Techniques

A wide range of database applications manage timevarying data, and it is well-known that querying and correctly updating time-varying data is dificult and error-prone when using standard SQL. Temporal extensions of SQL ofSeer substantial benefits over SQL when managing time-varying data. The topic of this paper is the effective implementation of temporally extended SQL’s. Traditionally, it has been assumed that a temporal DBMS must be built from scratch, utilizing new technologies for storage, indexing, query optimization, concurrency control, and recovery. In contrast, this paper explores the concepts and techniques involved in implementing a temporally enhanced SQL while maximally reusing the facilities of an existing SQL implementation. The topics covered span the choice of an adequate timestamp domain that includes the time van’able “NOW,” a comparison. of query processing architectures, and transaction processing, the latter including how to ensure ACID properties and assign timestamps to updates.

RelaXML: bidirectional transfer between relational and XML data

In modern enterprises, almost all data is stored in relational databases. Additionally, most enterprises increasingly collaborate with other enterprises in long-running read-write workflows, primarily through XML-based data exchange technologies such as Web services. However, bidirectional XML data exchange is cumbersome and must often be hand-coded, at considerable expense. This paper remedies the situation by proposing RELAXML, an automatic and effective approach to bidirectional XML-based exchange of relational data. RELAXML supports re-use through multiple inheritance, and handles both export of relational data to XML documents and (re-)import of XML documents with a large degree of flexibility in terms of the SQL statements and XML document structures supported. Import and export are formally defined so as to avoid semantic problems, and algorithms to implement both are given. A performance study shows that the approach has a reasonable overhead compared to hand-coded programs.

An Open-Source Based ITS Platform

In this paper, a complete platform used to compute travel times from GPS data is described. Two approaches to computing travel time are proposed one based on points and one based on trips. Overall both approaches give reasonable results compared to existing manual estimated travel times. However, the trip-based approach requires more GPS data and of a higher quality than the point-based approach. The platform has been completely implemented using open-source software. The main conclusion is that large quantity of GPS data can be managed, with a limited budget and that GPS data is a good source for estimating travel times, if enough data is available.

A split operator for now-relative bitemporal databases

The timestamps of now-relative bitemporal databases are modeled as growing, shrinking or rectangular regions. The shape of these regions makes it a challenge to design bitemporal operators that (a) are consistent with the point-based interpretation of a temporal database, (b) preserve the identity of the argument timestamps, (c) ensure locality and (d) perform efficiently. We identify the bitemporal split operator as the basic primitive to implement a wide range of advanced now-relative bitemporal operations. The bitemporal split operator splits each tuple of a bitemporal argument relation, such that equality and standard nontemporal algorithms can be used to implement the bitemporal counterparts with the aforementioned properties. Both a native database algorithm and an SQL implementation are provided. Our performance results show that the bitemporal split operator outperforms related approaches by orders of magnitude and scales well.