Declarative Routing: Extensible Routing with Declarative Queries

Transcription

1 elrtive Routing: Extensile Routing with elrtive Queries Boon Thu Loo 1 Joseph M. Hellerstein 1,2, Ion toi 1, Rghu Rmkrishnn3, 1 University of Cliforni t Berkeley, 2 Intel Reserh Berkeley, 3 University of Wisonsin-Mison

2 Motivtion Lk of extensiility n flexiility in toy s Internet routing Hr to /improve/upte routing protools

3 Two Our Gol Extremes : Hr-oe protools: + - Effiieny, sfety - Flexiility, evolvility - Ative Networks -+ Flexiility, evolvility - fety, effiieny - elrtive Routing: + Flexiility, evolvility, sfety Restrite instntition of Ative Networks for the ontrol plne

4 Key Ie Reursive query lnguge for expressing routing protools: tlog: elrtive reursive query lnguge Well-reserhe in the tse ommunity Well-suite for querying properties of grphs

5 Avntges Expressiveness: Compt n len representtion of protools fety: tlog hs esirle sfety properties on termintion Effiieny: No funmentl overhe when exeuting stnr protools.

6 Usge enrios IP ministrtors Run ifferent protools for ifferent noes Moify existing protools in routers En-hosts et up ustomize routes for ifferent qulity-of-servie n poliy requirements of pplitions

7 Romp Exeution Moel Introution to tlog Pth-Vetor Protool Exmple Avntges: Expressiveness fety Effiieny Evlution

8 Centrlize Exeution Moel tore entire network stte into entrlize tse Issue tlog queries on the entrlize tse for ustomize routes

9 istriute Exeution Moel tlog Queries Query Proessor Routing erive Protool Tuples Input Tles Output Result Tuples Tles Neighor Tle uptes Forwring Tle uptes Neighor Tle Forwring Tle Routing Infrstruture Noe Routing Infrstruture elrtive Tritionl Routers Routing

10 Introution to tlog tlog rule syntx: <he> <preonition1>, <preonition2>,, <preonitionn>.

11 All-Pirs Rehility R1: rehle(,) (,) R2: rehle(,) (,Z), rehle(z,) is from noe to noe (,) For ll,, there If (,) exists, generte rehle(,) rehle(,) noe n reh noe For ll noes,, If there is from to, then n reh. Input: (soure, estintion) Output: rehle(soure, estintion)

12 All-Pirs Rehility R1: rehle(,) (,) R2: rehle(,) (,Z), rehle(z,) For ll, n Z, If (,Z) exists AN rehle(z,) exists, generte rehle(,). For ll noes, n Z, If there is from to Z, AN Z n reh, then n reh. Input: (soure, estintion) Output: rehle(soure, estintion)

13 All-Pirs Rehility R1: rehle(,) (,) R2: rehle(,) (,Z), rehle(z,) Query: rehle(m,n) All-Pirs Input tle: rehle rehle rehle Output tle (Roun 1): E.g. R1: rehle(,) (,)

14 All-Pirs Rehility R1: rehle(,) (,) R2: rehle(,) (,Z), rehle(z,) Query: rehle(m,n) Input tle: rehle rehle rehle Output tle (Roun 2): R2: rehle(,) (,), rehle(,)

15 All-Pirs Rehility R1: rehle(,) (,) R2: rehle(,) (,Z), rehle(z,) Query: rehle(m,n) Input tle: Output tle (Roun 3): rehle rehle rehle Reursive queries re nturl for Reursive queries re nturl for querying grph topologies querying grph topologies

16 Romp Exeution Moel Introution to tlog Pth-Vetor Protool Exmple istriute tlog Exeution Pln Protool Avntges: Expressiveness fety Effiieny Evlution

17 istriute tlog R1: rehle(,) (,) R2: rehle(,) (,), rehle(z,) Query: rehle(m,n) Input tle: rehle rehle rehle Output tle:

18 Pth Vetor Protool Exmple R1: pth(,,p) (,), P=(,). R2: pth(,,p) (Z,), pth(z,,p 2 ), P=+P 2. Query: pth(,,p) Input: (soure, estintion) Query output: pth(soure, estintion, pthvetor)

19 tlog Exeution Pln R1: pth(,,p) (,), P=(,). R2: pth(,,p) (Z,), pth(z,,p 2 ), P=+P 2. Mthing vrile Z = Join Reursion Pseuooe t noe Z: R2.=pth. R1 (,) en pth. pth(,,p) while (reeive<pth(z,,p2)>)) 2 { for eh neighor { for eh neighor newpth = pth(,,+p2) newpth sen newpth = pth(,,+p to neighor 2 ) } sen newpth to neighor } } }

20 Query Exeution R2.=pth. en pth. R1: pth(,,p) (,), P=(,). (,) R1 pth(,,p) R2: pth(,,p) (Z,), pth(z,,p 2 ), P=+P 2. Query: pth(,,p,c) Neighor tle: Forwring tle: pth pth pth P P P (,) (,) (,)

21 Query Exeution R2.=pth. pth. R1: pth(,,p) (,), P=(,). (,) R1 pth(,,p) R2: pth(,,p) (,Z), pth(z,,p 2 ), P=+P 2. Query: pth(,,p,c) Neighor tle: p(,,[,,]) p(,,[,,]) Forwring tle: pth pth pth P P P (,) (,) (,) (,,) (,,)

22 Query Exeution R2.=pth. pth. R1: pth(,,p) (,), P=(,). (,) R1 pth(,,p) R2: pth(,,p) (,Z), pth(z,,p 2 ), P=+P 2. Query: pth(,,p,c) Neighor tle: p(,,[,,,]) Forwring tle: pth pth pth Communition ptterns re ientil to those in the tul pth vetor protool P P P Communition ptterns re ientil to (,) (,) (,) those in (,,) the tul pth (,,) vetor protool (,,,)

23 Romp Exeution Moel Introution to tlog Pth-Vetor Protool Exmple istriute tlog Exeution Pln Protool Avntges: Expressiveness fety Effiieny Evlution

24 Expressiveness Best-Pth Routing istne Vetor ynmi oure Routing Poliy eisions Qo-se Routing Link-stte Multist Overlys (ingle-oure & CBT) Minor vrints give mny options!

25 Expressiveness All-pirs ll-pths: R1: pth(,, P,C) (,,C), P=(,). R2: pth(,, P,C) (,Z,C 1 ), pth(z,, P 2,C 2 ), C=C 1 +C 2, P=+P 2. Query: pth(,, P,C)

26 Expressiveness Best-Pth Routing: R1: pth(,,p,c) (,,C), P= (,). R2: pth(,,p,c) (,Z,C 1 ), pth(z,,p 2,C 2 ), C=C 1 +C 2,P= +P 2. R3: estpthcost(,,min<c>) pth(,,z,c) R4: estpth(,,z,c) estpthcost(,,c), pth(,,p,c) Query: estpth(,,p,c)

27 Expressiveness Best-Pth Routing: R1: pth(,,p,c) (,,C), P= (,). R2: pth(,,p,c) (,Z,C 1 ), pth(z,,p 2,C 2 ), C=FN(C 1,C 2 ), P=+P 2. R3: estpthcost(,,agg<c>) pth(,,z,c) R4: estpth(,,z,c) estpthcost(,,c), pth(,,p,c) Query: estpth(,,p,c) Customizing C, AGG n FN: lowest RTT, lowest loss rte, highest ville nwith, est-k

28 Expressiveness All-pirs ll-pths: R1: pth(,, P,C) (,,C), P=(,). R2: pth(,, P,C) (,Z,C 1 ), pth(z,, P 2,C 2 ), C=C 1 +C 2, P=+P 2. Query: pth(,, P,C)

29 Expressiveness istne Vetor: R1: pth(,,,c) (,,C) R2: pth(,, Z,C) (,Z,C 1 ), pth(z,, W,C 2 ), C=C 1 +C 2 R3: shortestlength(,,min<c>) pth(,,z,c) R4: nexthop(,,z,c) nexthop(,,z,c), shortestlength(,,c) Query: nexthop(,, Z,C) Count to Infinity prolem?

30 Expressiveness istne Vetor with plit Horizon: R1: pth(,,,c) (,,C) R2: pth(,,z,c) (,Z,C 1 ), pth(z,,w,c 2 ), C=C 1 +C 2, W!= R3: shortestlength(,,min<c>) pth(,,z,c) R4: nexthop(,,z,c) nexthop(,,z,c), shortestlength(,,c) Query: nexthop(,,z,c)

31 Expressiveness istne Vetor with Poisone Reverse: R1: pth(,,,c) (,,C) R2: pth(,,z,c) (,Z,C 1 ), pth(z,,w,c 2 ), C=C 1 +C 2, W!= R3: pth(,,z,c) (,Z,C 1 ), pth(z,,w,c 2 ), C=, W= R4: shortestlength(,,min<c>) pth(,,z,c) R5: nexthop(,,z,c) nexthop(,,z,c), shortestlength(,,c) Query: nexthop(,,z,c)

32 Expressiveness All-pirs ll-pths: R1: pth(,,p,c) (,,C), P= (,). R2: pth(,,p,c) (,Z,C 1 ), pth(z,,p 2,C 2 ), C=C 1 +C 2, P=+P 2. Query: pth(,,p,c)

33 Expressiveness ynmi oure Routing (R): R1: pth(,,p,c) (,,C), P= (,). R2: pth(,,p,c) (Z,,C 2 ), pth(,z,p 1,C 1 ), C=C 1 +C 2, P= P 1 +. Query: pth(,,p,c) withing Right-reursion to Left-reursion exeution => Pth vetor protool to R.

34 Expressiveness Best-Pth routing istne Vetor ynmi oure Routing Poliy-se routing Qo-se routing Link-stte Multist Overlys (ingle-oure & CBT)

35 fety Queries re sn-oxe within query engine Queries use input tles to proue output tles No sie-effets on existing input tles Pure tlog gurntees termintion: Nturl oun on resoure onsumption of queries tti termintion heks for our extene tlog: Ientify reursive efinitions n hek for termintion E.g., monotonilly inresing/eresing ost fiels whose vlues re upper/lower oune Orthogonl seurity issues: enil-of-servie ttks, ompromise routers

36 Effiieny Explore well-known tse tehniques Aggregte seletions: voi sening unneessry pths to neighors Limit omputtion to portion of network Few soures n estintions Mgi sets + left-right reursion rewrite Multi-query shring: Ientify similr queries, shre their omputtions Reuse previously ompute pths

37 Queries uner Churn Long-running ontinuous queries Mintin ll intermeite erive tuples for query urtion Inrementl uptes: Link filures re trete s uptes with ost=infinity. Pths invlite (ost=infinity), n new pths re inrementlly reompute.

38 Evlution etup PIER: istriute reltionl query proessor Eh noe runs the query engine of PIER Initilize neighor tle iretly essile y PIER. imultion: Bnwith n lteny ottleneks Trnsit-stu topologies PlnetL 72 PIER noes Rnom, lotion-wre topologies Long-running queries

39 ummry of Results imultions: When ll noes issue the sme query, lility properties show similr trens s tritionl V/PV protools When few noes issue the sme query, Overhe is reue using stnr query optimiztions PlnetL experiments: Long-running ll-pirs shortest RTT pths query Aility to hnle RTT hnges Inue filures (up to 20% of noes) Reovery time: <1s (mein), <3.6s (verge)

40 Conlusion elrtive routing: Express routing protools using reursive query lnguge Better lne etween routing extensiility n sfety Future work: Expressing poliies s elrtive rules Run-time query optimiztions: Cost-se eisions on query rewrites Multi-query shring tti heker for routing protools Run-time monitoring of routing protools elrtive Networks Reserh gen: peify n onstrut networks elrtively P2: Implementing elrtive Overlys (OP 2005)

41 Thnk You