ISSN 1000-9825, CODEN RUXUEW E-mail: jos@iscasaccn Journal of Software, Vol17, No3, March 2006, pp388 395 http://wwwjosorgcn DOI: 101360/jos170388 Tel/Fax: +86-10-62562563 2006 by Journal of Software All rights reserved +,,, (, 100080) A Fault Identification Algorithm for Satellite Networks Based on System Level Diagnosis HOU Xia +, FAN Zhi-Hua, HU Gang, LI Lei (Institute of Software, The Chinese Academy of Sciences, Beijing 100080, China) + Corresponding author: Phn: +86-10-62614140 ext 112, E-mail: helenhou0927@hotmailcom, http://wwwiscasaccn Hou X, Fan ZH, Hu G, Li L A fault identification algorithm for satellite networks based on system level diagnosis Journal of Software, 2006,17(3):388 395 http://wwwjosorgcn/1000-9825/17/388htm Abstract: It is a challenge to support the fault tolerance for satellite networks, in which fault identification is primary After modeling satellite networks with two-level-node graph, a fault identification algorithm based on PMC test invalidation model is presented and proved to be correct The effectiveness of the algorithm in different types of satellite networks is compared and studied by simulations The results of experiments illustrate that the algorithm adapts to arbitrary network topology and has robustness Key words: : system level diagnosis satellite network two-level-node graph fault identification,, PMC,,,, : : TP391 : A [1],,,,, (inter-satellite links, ISLs), [2],,,, [3 6], Supported by the National High-Tech Research and Development Plan of China under Grant No2004AA712032 ( (863)) Received 2004-08-13 Accepted 2005-06-02
: 389 [5] ad-hoc [6],, [7],,, PMC [2], PMC,, 1 11 1,,,,,, [5] ad-hoc [6],,, :,,,,,,,,,,,, [7] 2 G=(S,V,L),S={s 1,s 2,,s m },V={v 1,v 2,, v n }, :v i s p s p v i L e L (e S,e V ),,e S e V,,, 1(c), ((s 1,s 3 ),(v 1,v 4 )) L, (v 1,v 4 ) l 1,4 : ISLs G s =(S,L s ) ISLs G v =(S,L v ),L s L v S 2 S 2 S 2 S 1 S 3 S 4 v 2 v 3 S 5 v 1 v 4 v 6 v 8 S 1 v 5 v 7 v 1 v 4 v 2 v 3 S 3 v 5 v 7 v 6 v 8 S 5 S 1 v 0 2 0 v 3 0 1 v 1 v S 3 4 v 6 v 8 0 0 v 5 0 0 v 7 S 5 S 4 S 4 (a) Composed of G s (t) (b) Composed of G v (t) (c) Theoretic topology graph G(t) (d) Test graph G T (t) (a) (b) (c) (d) Fig1 An example of the theoretic topology graph, composed of G s (t) and G v (t), and its test graph 1, t, G(t)=(S,V,L(t)) G T (t)=(s T,V T,L T (t)), t (t+1), (1) G(t) t L(t), ISLs 1
390 Journal of Software Vol17, No3, March 2006 (c) G(t),(a) (b) G(t) (2) G T (t) t, v i,v j V, v i v j x, (v i,v j ) L(t), l i,j =x 1 (d) (a) 12, : (A1) (A2), (A3) (A4),, [7,8] : (1) : (11) t m tst (12) m tst ( ), m rsp (13),, 0, 1 (14) (t+t out ), ( ) (2), t, G T (t)=(s T,V T,L T (t)), (3) t G(t)=(S,V,L(t)) (4) G(t) G T (t), G T (t), 2 2 21, (fault-free) (faulty), PMC [2] : 0, 1,,,,, x {0,1,2}, 2, PMC, 1 l i,j v i v j G T (t) ( ) 1 Table 1 1 The extended PMC model PMC 22 v i v j l i,j l j,i 0 0 0 0 0 1 1 0,1 1 0 0,1 1 1 1 0,1 0,1 0 or 1 or 2 2 2 2 2 0 or 1 or 2 2 2 1 : (rule1) l i,j =l j,i =0, v i v j ( 0 1)
: 391 (rule2) (rule3) (rule4) (rule5) (rule6) (rule7) l i,j =l j,i =1, v i v j 1 l i,j =1 l j,i =0, v j 1 v j 1 l i,j =0, v i 1 v i 0 l i,j =0, v j 0 v i 0 l i,j =1, v j 1 l i,j =l j,i =2, v i v j 2 (A1),, (rule8): (rule8) v i v j, v i v j, v i v j ( 0 1) 23,,,, V #V=n(# ), V f V V K( ) F1( ) F2( ) U( ), K F1 F2 U=V K,F1 F2, U CoarseSplit,SplitZ Diagnosis (1) CoarseSplit V 1, Z,S,U1,H, Z S U1 H=V Z={(v i,v j ) l i,j =l j,i =0} S={(v i,v j ) l i,j =l j,i =1} U1={(v i,v j ) l i,j l j,i } H={(v i,v j ) l i,j =l j,i =2} (2) SplitZ Z {Z 1,Z 2,,Z h }, Z Z l i,j =l j,i =0,Z Z 1 Z 2 Z h =Z Z i Z j = (i j) δ Z, δ=max (#Z 1,#Z 2,,#Z h ) 1 Z : Z a Z, l (a) l=1, Z a (v i,v j ) rule1,v i v j (b) l>1, (v i,v j ) Z a, Z, (v p,v q ) Z a, (v i,v j ) (v p,v q ), v i v p, rule8,v i v p rule1,v i,v j,v p v q,z a 1 : (rule9) Z Z a, v i Z a x, v j Z a x (3) Diagnosis,,,,v i ownerflag v i (0 1 ) Diagnosis ( ) { 1 K= F1= F2= U U2= 2 for (each (v i,v j ) U1) /* according to rule3 */ if (l i,j =1 and l j,i =0) {F1=F1+v j U2=U2+v i v j ownerflag=1} U h = # Z Z a = δ a a= 1 3 K
392 Journal of Software Vol17, No3, March 2006 4 for (each v i K) v i ownerflag=0 5 while (U V K F1 F2) { U=V K F1 F2 /* ports set with unknown states */ for (each Z a Z){ if (any v i (F1 Z a )) { For (each v i Z a ) v i ownerflag=1 F1=F1+Z a Z=Z Z a } if (any v i (K Z a )) { for (each v i Z a ) v i ownerflag=0 K=K+Z a Z=Z Z a } } /* according to rule8 */ for (each v i (Z S U2)) { if (v i ownerflag==0) K=K+v i if (v i ownerflag==1) F1=F1+v i } /* according to rule8 */ for (each (v i,v j ) S) /* according to rule2 */ if (v i K) {F1=F1+v j S=S (v i,v j ) v j ownerflag=1} for (each (v i,v j ) H) /* according to rule7 if (v i (K F1)) {F2=F2+v j H=H (v i,v j )} } /* end while */ } /* diagnosis result is K, F1, F2, and U */ 24,,,, PMC, Diagnosis, 2~ 4 :(1) rule3 U1 F1(2) Z,while 5,, : Z, Diagnosis 3 1 #V f β, Z Z i,δ=#z i δ>β, : Z i 1,Z i δ, #V f δ>β #V f β, δ>β,z i, Diagnosis 3, 2 Z Z i,δ=#z i #V f <β, β=#(s U1 H)/2 #(S U1)+δ #((S U1 H) Z i ) : S U1,H,, S U1 S 1 U1 1, S 0 U1 0 H H 0,H 1,H 2 (A) f A, #(S U1 H) f #(S U1) f +#H 2 =#S 1 +#U1 1 #(S 1 U1 1 )+#H 2 #S 1 +#U1 1 +#H 2 #(S U1) (1) rule2,rule3 rule7 S,U1 H, #S+#U1+#H=(#S 0 +#S 1 )+(#U1 0 +#U1 1 )+(#H 0 +#H 1 +#H 2 ) 2#S 1 +2#U1 1 +2#H 2 (2) (1) (2) #(S U1 H) #S+#U1+#H Z i Z,Z i Z, (S U1 H Z)=V, #(S U1 H) f #(S U1 H)/2 #(S U1) (3) #(S U1 H Z i ) f #V f (4)
: 393 Z i, 1,Z i δ (1)~ (3) #(S U1 H Z i ) f #(S U1 H)/2 #(S U1)+δ #((S U1 H) Z i )=β (4) #V f β #V f <β, Z i δ 1 2, Diagnosis 3 4, F1 3 walker [1], walker i:t/p/s, i,t,p,s, T/P, 20/4 64/8, 80 256 4, 2 3, LEO 36/6,MEO 4/2, 172 MEO, MEO MEO ISLs MEO LEO ISLs Fig2 The topology of LEO networks Fig3 An example of MEO/LEO network 2 LEO 3 MEO/LEO, ( ),,, f % p (1) f%: #V f =n f % f% 0%~60%, 10% (2) p PMC, B(1,p): 0 p 1 (1 p), B(1,p 2 ): 0 p 2 1 (1 p 2 ) p 05 025,,, f% p, f% p, C% N, C%=[(n #U)/n] 100%,N m tst m rsp 50, C% N, 2, f% 50%,p f%>50%,p=05 p=025
394 Journal of Software Vol17, No3, March 2006 Table 2 Statistical results of experiments 2 Single-layer LEO network(20/4) Single-layer LEO network(64/8) Two-layer MEO/LEO network f% p=05 p=025 p=05 p=025 p=05 p=025 N C% N C% N C% N C% N C% N C% 0 160 100 160 100 512 100 512 100 538 100 538 100 10 15052 8897 15080 8913 49340 9411 49408 9439 52655 9804 66608 9540 20 14644 8625 14722 8596 48368 9216 48426 9178 51316 9570 66020 9380 30 14272 8295 14128 8133 47004 8831 47008 8702 50342 9397 64092 9145 40 14168 7770 14012 7729 45964 7739 45990 7411 48825 9164 61236 8717 50 13704 7188 13784 6625 45552 6465 45344 5986 47512 8899 60276 8529 60 13272 3860 13432 2555 43512 4117 43978 2746 46757 8515 58560 7978 4 5 p=05,3 f % C% N 4,N N 5,C%, f %>50%, C% f% 50%, 1 2, K F1 f%>50%, 1 2, F1,,, N 600 500 400 300 200 100 20/4 64/8 MEO/LEO 0 10 20 30 40 50 60 f % C% 100 80 60 40 20 64/8 20/4 MEO/LEO 0 10 20 30 40 50 60 f % Fig4 Relation of f % and N when p=05 4 p=05 f % N Fig5 Relation of f % and C% when p=05 5 p=05 f % C%, MEO/LEO, f%>50%,,,, (v i,v j ) H, v i v j, (v i,v j ) H,(v i,v k ) U1, v i, rule7,v j,h 4, PMC, PMC,, 30%, 3 80,,,,
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