### Table 2. The distribution of the data in non-uniformly

1992

"... In PAGE 22: ... Table2 shows the distribution of the data in the non-uniformly distributed #0Cles among 3 disks. Number of Data Distribution on Disks Records Number of Blocks Number of Blocks Number of Blocks in Files on Disk 1 on Disk 2 on Disk 3 1000 14 13 14 10000 138 138 137 15000 209 210 208 20000 279 279 279 Table 1.... In PAGE 22: ... Table 1 shows that the data in the uniformly distributed #0Cles is evenly distributed among disks. Table2 shows that the data in the non-uniformly distributed #0Cles is nearly equally distributed among disks even without using any rebalancing algorithm. Performance of range query processing.... ..."

Cited by 38

### Table 7: Non-uniform Input

1998

"... In PAGE 9: ...93 0.9506 66990 Table 6: Di#0Berent Symbol Ratios InputClass = Uniform, m =2;n= 1000;k =2;p=#28Ratio; 1 , Ratio#29 Table7 shows selected experiments with input generated from non-uniform probability distributions The probability distribution of each0; 1-input string is described by a linear functions de#0Cned over its length. For simpli#0Ccation, this function is de#0Cned by the line connecting the probabilityvalues of the leftmost string symbol p l and the rightmost string symbol p r .... ..."

Cited by 1

### Table 2: Parameters for non-uniform distribution

### Table 3: Parameters for non-uniform capacity

### Table2. Computational results of non-uniform traffic demand

1996

"... In PAGE 6: ...he second system tested has a non-uniform demand. It has 12 nodes and its reception capacity is 3. We generate 20 different traffic demands in the range of 2 - 6. Table2 is the computational results of our ... ..."

### Table 5 - Computed Stresses (Non-Uniform Model)

"... In PAGE 8: ...able 4 - Computed Stresses (Uniform Model)............................... 29 Table5... In PAGE 37: ... For the linearly decreasing pressure case it occurs at 41%, and for the linearly increasing pressure case it is roughly 28%. Table5 lists the maximum Von Mises stresses achieved for each load case at each level of deterioration investigated using the non-uniform model. The data are also presented in graphical form in Figure 13.... ..."

### Table 4: CPU time (hours) to detect 80% of total faults. non-uniform A uniform non-uniform B

2000

"... In PAGE 17: ... Now consider an evaluation of e ciency for exposing 80% of the faults for each type of fault distribution and each execution strategy. Table4 presents the CPU time required to detect 80% of all faults in a program for the three fault distribution patterns and six execution patterns. Overall, uniform execution of the code with a uniform fault distribution takes less CPU time to expose 80% of the faults; biased executions take less CPU time for those programs with non- uniform fault distributions.... ..."

Cited by 1

### TABLE III Average retrieval cost with non-uniform file size

2003

Cited by 20

### Table 1: Comparison of Average Costs for Non-Uniform distribution

1996

"... In PAGE 23: ... During this period, if the system designer uses LU-PC instead of adaptive, the network load (in terms of number of messages) will increase by 12%. For the given call and mobility distribution (shown in Figure 14 and Figure 13), the total savings of adaptive over LU-PC is 4% and over LU-JU is 17% (as shown in Table1 ). Thus, the results show that a simple adaptive location management algorithm as shown in Figure 12 performs better than the static location management strategies for a wide range of call-mobility patterns.... ..."

Cited by 14

### Table 1: Comparison of Average Costs for Non-Uniform distribution

1996

"... In PAGE 23: ... During this period, if the system designer uses LU-PC instead of adaptive, the network load (in terms of number of messages) will increase by 12%. For the given call and mobility distribution (shown in Figure 14 and Figure 13), the total savings of adaptive over LU-PC is 4% and over LU-JU is 17% (as shown in Table1 ). Thus, the results show that a simple adaptive location management algorithm as shown in Figure 12 performs better than the static location management strategies for a wide range of call-mobility patterns.... ..."

Cited by 14