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Partitioning Multimedia Objects for Optimal Allocation in
Distributed
Cornputing Systems
Abstract
1 Introduction
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2 The Object Data Models
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0 rleternline the allocation unit for each site within a,
network cluster?
0 determinc the ot)ject characteristics and properties thai are
~~ecessary a.nd sufficient for. cleveloping the criteria for
gwera.ting t hc allocation unit,s'?
0 determine the cffccts of local or rem0t.e accessihilities?
0 develop the efficient algorithms and processes to a.chieve onr
ohjec- tives?
0 demonst.ra.te the rcalization of O u r clusterimtion
technir~ncs?
4 Object Creation and Allocation Requirements The objects of the
models are dynamically created a.1~1 stored i l 1 t.lle systern.
At. the creation of a, LIE, complex object, or a.ttrihut.e, the
user or applica.tion tnust specify whether the object is limited to
local access (class-L ob.icet), r ~ ~ u o t . e access (c2as.q-R
abject), or hoth accesses. Otlly loca,l or remote access is legal;
therefore, wl1en a.n object l m bot11 a.ccessihilities, rcmote
a.ccess takes precedence.
4.1 Creation and Allocation Requirements of MOAM Ob- jects
t figllre
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oe 5
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For a composite o1)ject with considera.ble mn1ber of DES
relative t~ the nlunbcr of ta.rget. sites, the IDDA ma.y not be
possible.
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A6 -. - A7 As
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A1S
Alfi
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Fignre 4: A composite ollject t.0 he creat,ed.
In the case of sllarcd ohjects, we precede ea.ch sl1a.red
attrilmte with a st.ring formed from the synthol "#" a.ad the
sIIa,ring ohjects.
5 Problem Analysis
5.1 The MOAM Objects -1s ive sta.ted previously, we must specify
the degrce of allocation for cla,ss-R. o1)jwts of a. conlposil,e
object for efficient a.lloca.t.ion. Since eau11 Dl; in cla.ss- K is
snsceptible to concurrent multiple a,ccesses frorn any nunrher of'
users, a.pplica.tions. or sites. the overwhelming motivation will
he t.o u t ilizc IDDA for ew11 cla,ss-R ollject of a. composite
object. The clunulativc ~l l l~nher of targpt nodes is t.he most
important limiting factor for the 11t.iliza.t.ion of the
11)1).2.
5.1.1 Inter DE and Complex Object Degrees of Allocation
Tllcre axe certain conditions that must be sa.tisfictl for an
effective utilization of eit.llcr the IDDA or IC'DA. If the number
of class-H. objects il1 a. composite object is greater tllan t1he
number of ta.rget, nodcs. then ~ v e cnnuol. store the composite
object with IDDA. If the 1111uher of romples ol).jects in a
co~nposite object exceeds the numher of nodcs, then we ca.nnot
store the class-R 0bject.s of i.hc composite object with TCDA.
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5.2.1 Utilizing Sub-graphs and Multigraphs
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6.1.1 Partitioning for Other Degrees of Allocation I"1.om the
discussions i n Section .5.1.2, we kao\r tha i in or t lc~ t.o
huiltl the storage units for t11es~ tlegrees of allocation. WC mnst
genemte and condine a numher of sets of J ) T k Precisely, we need
to the followiag:
1. huild the DES of ea.ch of the applicable comples object,
2. generate conlhillations of DES of different complex o1)ject.s
Imed on the degrce of aIloca.tion specifed,
3 . selcct a, nu~ul)er of sets fronl step 2 such t.11a.t. the
resultallt sets form a. valid cover for al1 the a,pplica.ble
DES,
-1. if st-ep 3 fadltd, t.11en rquest for coakscing a.nd go hack
1.0 stcp 2 until coalescing becornes impossible.
The a.na.lysis of t h process sllo~vs tlmt the t. i lnc3 of
execution is I)oanded by the nmximurn nnn1l)cr of sets generated.
In otller words. if is the degrcle of alloca.tion, O#""" the number
of DES i n a. given composite ohject, a,nd T ( O ) the time of
pa.rtitioning O, therefore,
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Figure 7: A salnple bipa.rt.ite gra.ph a.ud optimal
allocations.
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7.1 The ABBM Bbjects We necd to analyze t . 1 ~ axera.ge binding
strengtlls within each clllster or site. l'hc esperiments consist
of a, numher of composite object,s wrl~osc~ constituent nnulher of
romples olj-ject.s a,nd at.trihutes are ra.ndo1nly generatcd. In
t.he first case, we wa.nt to observe the distribution of abjects
with respect ta ca.ch network cluster a.nd then, with respect to
each site. We 11se the a.vera.ge cnnlulative binding sitrength of
al1 the objects a.lloca.t,ed i n a. cluster to deter- lnine the
degree of distribution. In the second case, we want. to compare Our
ya.rt.itioning st.ra.tegy wit.11 commonly used met.hods, i.e.,
either sequent.ia.lly allocaiing ol>jects or size-bahncing
allocations.
l'igtlre 8: Object distribution (left.) and Comparative ollject
distribution ( richi ).
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8 Conclusions
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