Special cases of online parallel job scheduling

In this paper we consider the online scheduling of jobs, which require processing on a number of machines simultaneously. These jobs are presented to a decision maker one by one, where the next job becomes known as soon as the current job is scheduled. The objective is to minimize the makespan. For the problem with three machines we give a 2.8-competitive algorithm, improving upon the 3-competitive greedy algorithm. For the special case with arbitrary number of machines, where the jobs appear in non-increasing order of machine requirement, we give a 2.4815-competitive algorithm, improving the 2.75-competitive greedy algorithm

Run-time adaptation of a reconfigurable mobile UMTS receiver

UMTS receivers are mobile devices, which should have a low energy consumption and operates in a frequently changing environment. The idea of this paper is to adapt the amount of signal processing for the reception within an UMTS mobile to this changing environment. In this way the amount of signal processing can be decreased for a good channel to decrease the energy consumption and for a bad channel the signal processing can be increased to guarantee a minimum Quality of Service for the signal. Due to space limitation, this paper only describes the approach. For full details see [1]

Run-time Mapping of Applications to a Heterogeneous SoC

This paper presents an iterative hierarchical approach to map an application to a parallel heterogeneous SoC architecture at run-time. The application is modeled as a set of communicating processes. The optimization objective is to minimize the energy consumption of the SoC, while still providing the required Quality of Service. This approach is flexible, scalable and the performance looks promisin

BER estimation for wireless links using BPSK/QPSK modulation

This paper introduces a method that computes an estimation of the bit error rate (BER) based on the RAKE receiver soft output only. For this method no knowledge is needed about the channel characteristics nor the precise external conditions. Simulations show that the mean error of the estimation is below 2%, with only a small variance. Also an estimation of the BER for a different spreading factor or a different number of RAKE finger can be made. Implementation issues for a practical use of the method are discussed

Cologne/Twente workshop on graphs and combinatorial optimization CTW 2007

The 6th Cologne-Twente Workshop on Graphs and Combinatorial Optimization (CTW 2007) was held at the University of Twente, The Netherlands, 29-31 May, 2007. The CTW started as a series of biennial meetings at the Universities of Cologne in Germany and Twente in the Netherlands. Ever increasing interest has turned the CTW into a now annual event with the Politecnico di Milano, the University of Duisburg-Essen, the Universit degli Studi di Milano, and Ecole Polytechnique in Paris as additional partners. The scope of the workshop comprises the theory and applications of discrete algorithms, graphs, and combinatorial structures in the wide sense. After the workshop, the participants and the research community at large were invited to submit research articles relating to the themes of the workshop. As guest editors, we are pleased to present a collection of articles that were selected from the submissions by the refereeing process. We thank all the contributors for making it so easy to document the workshop and the state-of-the-art with interesting articles and we hope that you, the reader, will find these contributions stimulating as well

Energy-efficient wireless communication for mobile multimedia terminals

This paper presents a control system that adapts a WCDMA receiver at run-time to minimize the energy consumption while providing an adequate Quality of Service (QoS). The adaptation is done at run-time, because of the dynamic environment of a mobile receiver. Simulations show that run-time adaptation to the environment decreases the energy consumption of a receiver and also improves other QoS parameters, such as a higher throughput and a lower frame error rate

Minimizing costs is easier than minimizing peaks when supplying the heat demand of a group of houses

This paper studies planning problems for a group of heating systems which supply the hot water demand for domestic use in houses. These systems (e.g. gas or electric boilers, heat pumps or microCHPs) use an external energy source to heat up water and store this hot water for supplying the domestic demands. The latter allows to some extent a decoupling of the heat production from the heat demand. We focus on the situation where each heating system has its own demand and buffer and the supply of the heating systems is coming from a common source. In practice, the common source may lead to a coupling of the planning for the group of heating systems. On the one hand, the external supply of the energy for heating up the water may have to be bought by an energy supplier on e.g. a day-ahead market. As the price of energy varies over time on such markets, this supplier is interested in a planning which minimizes the total cost to supply the heating systems with energy. On the other hand, the bottleneck to supply the energy also may be the capacity of the distribution system (e.g. the electricity networks or the gas network). As this has to be dimensioned for the maximal consumption, in this case it is important to minimize the maximal peak. The two mentioned coupling constraints for supplying the energy for producing the heat, lead to two different objectives for the planning of the group of heating systems: minimizing cost and minimizing the maximal peak. In this paper, we study the algorithmic complexity of the two resulting planning problems. For minimizing costs, a classical dynamic programming approach is given which solves the problem in polynomial time. On the other hand, we prove that minimizing the maximal peak is NP-hard and discuss why this problem is hard. Based on this, we show that this problem becomes polynomial if all heating systems have the same consumption of energy when turned on. Finally, we present a Fix Parameter Tractable (FPT) algorithm for minimizing the maximal peak which is linear in the number of time intervals