Publications by Immanuel Trummer

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Query plans offer diverse tradeoffs between conflicting cost metrics such as execution time, energy consumption, or execution fees in a multi-objective scenario. It is convenient for users to choose the desired cost tradeoff in an interactive process, dyna ...

Commercial services for provisioning software components and virtual infrastructure in the cloud are emerging. For customers, this creates a multitude of possibilities for outsourcing part of the IT-stack to third parties in order to run their applications ...

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

Various algorithms have been proposed for the problem of quality-driven service composition. They differ by the quality of the resulting executable processes and by their processing costs. In this paper, we study the problem of service composition from an ...

The goal of multi-objective quality-driven service selection (QDSS) is to find service selections for a workflow whose quality-of-service (QoS) values are Pareto-optimal. We consider multiple QoS attributes such as response time, cost, and reliability. A s ...

The D-Wave adiabatic quantum annealer solves hard combinatorial optimization problems leveraging quantum physics. The newest version features over 1000 qubits and was released in August 2015. We were given access to such a machine, currently hosted at NASA ...

Classical query optimization compares query plans according to one cost metric and associates each plan with a constant cost value. In this paper, we introduce the Multi-Objective Parametric Query Optimization (MPQ) problem where query plans are compared a ...

The goal of query optimization is to map a declarative query (describing data to generate) to a query plan (describing how to generate the data) with optimal execution cost. Query optimization is required to support declarative query interfaces. It is a co ...

The goal of multi-objective query optimization (MOQO) is to find query plans that realize a good compromise between conflicting objectives such as minimizing execution time and minimizing monetary fees in a Cloud scenario. A previously proposed exhaustive ...

Participatory sensing (PS) is becoming a popular data acquisition means for interesting emerging applications. However, as data queries from these applications increase, the sustainability of this platform for multiple concurrent applications is at stake. ...

In Quality-Driven Service Composition, tasks from an ab- stract work ow are assigned to concrete services such that work ow QoS are optimized. The following three proper- ties are desirable for a corresponding algorithm. First, the run time is ideally boun ...

The goal of multi-objective query optimization (MOQO) is to find query plans that realize a good compromise between conicting objectives such as minimizing execution time and minimizing monetary fees in a Cloud scenario. A previously proposed exhaustive MO ...

This invention relates to the field of multi-objective workflow optimization. Certain exemplary embodiments of the invention are applicable in cases where workflow descriptions contain choice variables relating for instance to the selection of a specific s ...

Immanuel Trummer

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An Incremental Anytime Algorithm for Multi-Objective Query Optimization

Cost-Optimal Outsourcing of Applications into the Clouds

Parallelizing Query Optimization on Shared-Nothing Architectures

Dynamically Selecting Composition Algorithms for Economical Composition as a Service

Multi-Objective Quality-Driven Service Selection-A Fully Polynomial Time Approximation Scheme

Multiple Query Optimization on the D-Wave 2X Adiabatic Quantum Computer

Multi-Objective Parametric Query Optimization

From Massive Parallelization to Quantum Computing: Seven Novel Approaches to Query Optimization

Approximation Schemes for Many-Objective Query Optimization

Utility-driven Data Acquisition in Participatory Sensing

The RADO approach to Quality-Driven Service Composition - Approximating the Pareto-Frontier in Polynomial Time

Approximation schemes for many-objective query optimization

A Fast Randomized Algorithm for Multi-Objective Query Optimization

Optimizing the Tradeoff between Discovery, Composition, and Execution Cost in Service Composition

Method for multi-objective quality-driven service selection