Ripple-Spreading Network Model Optimization by Genetic Algorithm

Table 2

Comparative results: to generate scale-free network topology.

	NDT	Setup of model parameters	APL	ADEE	CC	ASSO
BA1	Circle dist.	𝜏=0	2.6561	1235.6	0.0600	0.0324
BA2	Circle dist.	𝜏=1	2.5103	1272.5	0.1339	0.1435
BA3	Circle dist.	𝜏=2	1.9350	1279.5	0.6875	0.4213
BA4	Grid dist.	𝜏=0	2.4652	1146.6	0.0725	0.0260
BA5	Grid dist.	𝜏=1	2.3690	1154.5	0.1434	0.1232
BA6	Grid dist.	𝜏=2	1.9224	1143.8	0.6492	0.3930
BA7	Random	𝜏=0	2.2271	1146.7	0.0953	0.0369
BA8	Random	𝜏=1	2.1768	1153.1	0.1549	0.1129
BA9	Random	𝜏=2	1.8991	1151.1	0.6214	0.3033
RSNM7	Circle dist.	𝛽𝑅=5, 𝛽𝐿 = 5.1, 𝛼 = 1036.7, 𝑁SGR = 100, and 𝐸SGR(𝑖)∈[0, 56549]	2.3208	634.5	0.7718	0.3593
RSNM8	Grid dist.	𝛽𝑅 = 5, 𝛽𝐿 = 5.0, 𝛼 = 1036.7, 𝑁SGR = 100, and 𝐸SGR(𝑖)∈[0, 62832]	2.1030	599.9	0.7392	0.3272
RSBM9	Random	𝛽𝑅 = 5, 𝛽𝐿 = 5.1, 𝛼 = 1036.7, 𝑁SGR = 100, and 𝐸SGR(𝑖)∈[0, 62832]	2.1857	564.9	0.7397	0.3234
RSNM10	Circle dist.	𝛽𝑅 = 100, 𝛽𝐿(𝑖)∈[1.1, 15.2], 𝛼 = 1036.7, 𝑁SGR = 100, and 𝐸SGR = 62832	9.8945	213.1	0.5579	0.0916
RSBM11	Grid dist.	𝛽𝑅 = 100, 𝛽𝐿(𝑖)∈[1.0, 10.3], 𝛼 = 1036.7, 𝑁SGR = 100, and 𝐸SGR = 10053	2.0285	693.1	0.8448	0.3445
RSNM12	Random	𝛽𝑅 = 100, 𝛽𝐿(𝑖)∈[0.5, 10.2], 𝛼 = 1036.7, 𝑁SGR = 100, and 𝐸SGR = 13100	2.4119	591.7	0.7648	0.3947
RSNM13	Circle dist.	𝛽𝑅 = 5, 𝛽𝐿 = 5.1, 𝛼(𝑖)∈[439.8, 3141.6], 𝑁SGR = 1, and 𝐸SGR = 2199.1	5.0135	365.7	0.6619	0.0138
RSNM14	Grid dist.	𝛽𝑅 = 5, 𝛽𝐿 = 9.2, 𝛼(𝑖)∈[2585.0, 6911.5], 𝑁SGR = 1, and 𝐸SGR = 9424.8	2.8947	473.5	0.6374	0.1715
RSBM15	Random	𝛽𝑅 = 5, 𝛽𝐿 = 8.7, 𝛼(𝑖)∈[2585.0, 6911.5], 𝑁SGR = 1, and 𝐸SGR = 9419.3	2.1877	547.8	0.7099	0.1956
RSNM16	Random	𝛽𝑅 = 5, 𝛽𝐿 = 0.5, 𝛼 = 471.2, 𝑁SGR = 1, and 𝐸SGR = 7854.0	1.9594	902.1	0.9648	0.9524