Algorithm 1. Edge-Aided Attribute-Based Cluster Algorithm

Input: input $\theta$, $U$$V$, $B^S$, $EN$

Output: $CL=\left(C{L}_1,C{L}_2,\dots ,C{L}_l\right)$   1: Calculate all $Dist\left(E{N}_l,{\theta }_j\right)$   2: for $l=1$ to $j$ do   3:     if $M_{EN}$ $=1, C{P}_{{\theta }_j}\le C{P}_{E{N}_l}$$, \min Dist\left(E{N}_l,{\theta }_j\right)$   4:     $E{N}_l$ become cluster head for $C{L}_l$   5:    updates the set of clusters $CL$   6: end for   7: Calculate all $D\mathrm{i}st\left(u_i,{\theta }_j\right)$,$Dist\left(v_n,{\theta }_j\right)$,$Dist\left(b^S{}_n,{\theta }_j\right)$   8: for $i=1$ $u$, do   9:     if min $D\mathrm{i}st\left(u_i,{\theta }_j\right)$$, {\mathrm{Re}}_{u_i}^{{\theta }_j}<B_{{\theta }_j}$  10:     $u_i$ joins the cluster $C{L}_l$  11:    end if  12: end for  13: for $m=1$, $v=1$ to $n$, do  14:    if min $Dist\left(v_n,{\theta }_j\right)$$,C_{{\theta }_j}^{V_A}<B_{{\theta }_j}$  15:     $v_n$ joins the cluster $C{L}_l$  16:    if min $Dist\left(b^S{}_n,{\theta }_j\right)$$,C_{{\theta }_j}^{B^S}<B_{{\theta }_j}$  17.     $b^S{}_n$ joins the cluster $C{L}_l$  18:    end if  19: end for  20: Return all cluster $CL=\left(C{L}_1,C{L}_2,\dots ,C{L}_l\right)$