TY  - JOUR
A1  - Grum, Marcus
A1  - Bender, Benedict
A1  - Alfa, A. S.
A1  - Gronau, Norbert
T1  - A decision maxim for efficient task realization within analytical network infrastructures
JF  - Decision support systems : DSS ; the international journal
N2  - Faced with the increasing needs of companies, optimal dimensioning of IT hardware is becoming challenging for decision makers. In terms of analytical infrastructures, a highly evolutionary environment causes volatile, time dependent workloads in its components, and intelligent, flexible task distribution between local systems and cloud services is attractive. With the aim of developing a flexible and efficient design for analytical infrastructures, this paper proposes a flexible architecture model, which allocates tasks following a machine-specific decision heuristic. A simulation benchmarks this system with existing strategies and identifies the new decision maxim as superior in a first scenario-based simulation.
KW  - Analytics
KW  - Architecture concepts
KW  - Cyber-physical systems
KW  - Internet of things
KW  - Task realization strategies
KW  - Simulation
Y1  - 2018
U6  - https://doi.org/10.1016/j.dss.2018.06.005
SN  - 0167-9236
SN  - 1873-5797
VL  - 112
SP  - 48
EP  - 59
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Lohmann, Dirk
A1  - Guo, Tong
A1  - Tietjen, Britta
T1  - Zooming in on coarse plant functional types-simulated response of savanna vegetation composition in response to aridity and grazing
JF  - Theoretical ecology
N2  - Precipitation and land use in terms of livestock grazing have been identified as two of the most important drivers structuring the vegetation composition of semi-arid and arid savannas. Savanna research on the impact of these drivers has widely applied the so-called plant functional type (PFT) approach, grouping the vegetation into two or three broad types (here called meta-PFTs): woody plants and grasses, which are sometimes divided into perennial and annual grasses. However, little is known about the response of functional traits within these coarse types towards water availability or livestock grazing. In this study, we extended an existing eco-hydrological savanna vegetation model to capture trait diversity within the three broad meta-PFTs to assess the effects of both grazing and mean annual precipitation (MAP) on trait composition along a gradient of both drivers. Our results show a complex pattern of trait responses to grazing and aridity. The response differs for the three meta-PFTs. From our findings, we derive that trait responses to grazing and aridity for perennial grasses are similar, as suggested by the convergence model for grazing and aridity. However, we also see that this only holds for simulations below a MAP of 500 mm. This combined with the finding that trait response differs between the three meta-PFTs leads to the conclusion that there is no single, universal trait or set of traits determining the response to grazing and aridity. We finally discuss how simulation models including trait variability within meta-PFTs are necessary to understand ecosystem responses to environmental drivers, both locally and globally and how this perspective will help to extend conceptual frameworks of other ecosystems to savanna research.
KW  - Traits
KW  - Dryland
KW  - Degradation
KW  - Shrub encroachment
KW  - Simulation
KW  - Eco-hydrological model
KW  - EcoHyD
Y1  - 2018
U6  - https://doi.org/10.1007/s12080-017-0356-x
SN  - 1874-1738
SN  - 1874-1746
VL  - 11
IS  - 2
SP  - 161
EP  - 173
PB  - Springer
CY  - Heidelberg
ER  -