Even for the case where random subchannel allocation is assumed, i.e., non-iterative selection, a certain degree of fairness between users can be obtained by using the utility-based water-filling.
We collected experienced utility data by using the Health Utility Index (8) and by eliciting time tradeoff (TTO) utilities for overall experience (7).
RMSG algorithm discussed in Section 5 minimizes the total transmit power in the network defined by (9) using the utility function (23) in a noncooperative manner.
Comparing the results from Configuration 2.1 and Configuration 2.2, we can conclude that increasing the number of VMs by 50%% using the utility based approach resulted in nearly the same percentage of overall SLA violations, while the energy consumption is increased by about 50%%.
By using the aforementioned utility, every sector of the hard drive is overwritten with zeros, thereby destroying all data.
If that doesn't work, you can re-set the whole TCP/IP stack back to its original state by using the NetShell utility, netsh, and try again.
Note that by using the above utility function, each user selects the transmit beamformer t m ∈ Δ m to maximize its own "normalized" SINR, t m H H m, m H R m - 1 H m, m t m.
Note that both distributions of afterslips and 1-σ standard errors are shown after optimal Delaunay triangulation and gridding by using the "triangulate" utility included in the Generic Mapping Tools (Wessel and Smith, 1998) so that they are plotted on grid points with an interval of 5 min. Green triangles indicate the land GPS and offshore PG stations whose data are used for inversions.
In the case when implementing spatial multiplexing, each MS-n ranks each RS-r from its subset S n by using the following utility function: begin{array}{*{20}l} U_{nr_text{capacity}}(T_{text{target}})&={P_{text{simo}}}(T_{text{target}}) &quad-{P_{text{mimo}_text{capacity}}}(T_{text{target}}), end{array} (30).
Based on this information, RSs are able to rank their subset of MSs, S r, by using the following utility function when diversity is enhanced: begin{array}{*{20}l} U_{rn_text{diversity}} eta_{text{target}})&=P_{text{circ}}left(frac{P_{t} eta_{text{target}}) |w_{text{rs}}|^{2}}{M_{t}}right) &quad-P_{text{circ}}left(frac{P_{t} eta_{text{target}}) |w_{text{ms}}|^{2}}{M_{t}} right).
The white matter mask was obtained by using the segmentation utility in SPM5 (http://www.fil.ion.ucl.ac.uk/spm/software/spm5) to segment the white matter in the native space of each individual subject.
