=Paper=
{{Paper
|id=Vol-547/paper-46
|storemode=property
|title=Synchronization in a Multimedia
|pdfUrl=https://ceur-ws.org/Vol-547/142.pdf
|volume=Vol-547
|dblpUrl=https://dblp.org/rec/conf/ciia/Ghomari09
}}
==Synchronization in a Multimedia==
https://ceur-ws.org/Vol-547/142.pdf
Synchronization in a Multimedia
A. Ghomari
Université d’Oran Es-Senia
Faculté des Sciences
Département d’Informatique
BP 1524, El-M’Naouer Oran 31000
ALGERIE
ghomari.abdelghani@univ-oran.dz
Abstract. The paper introduces a class of specialized temporal net models, called
Multimedia P-Time Petri Net (MP-RdPT), to model the synchronization aspects of
multimedia scenarios. Several types of synchronization are introduced, and a
number of temporal relations between multimedia objects are presented. After
translation of the derived MP-RdPT net to an equivalent t-time Petri net, it is
claimed that the proposed approach can be used for verification of specifications by
using the tool Tina.
Keywords: Multimedia synchronization, time Petri net, specification, analysis,
verification.
1 Introduction
Multimedia refers to the presentation of collections of both static and dynamic data (i.e.,
data with natural time dependencies e.g., audio or video) in a specified order and time.
Therefore, their mutual synchronization must assure a proper temporal order of
presentation events. Multimedia synchronization can be defined as a mutual assignment of
data items and time instants. These time instants may be known in advance (e.g., standard
consumer data players) or they can be also results of some unknown function of time
(event driven synchronization) or known with some limited accuracy (e.g., random
network delays).
The modeling and the presentation of multimedia scenarios are challenges of
multimedia applications. Multimedia scenarios are results of temporal composition and
user interactions of multimedia objects in an application domain, and lot of works
discussed this notion [18]. Temporal compositions consist in presenting multimedia
objects which requires synchronization among different media.
Most of specification models are based on Allen’s relations [3]. Allen defined seven
basic relations between two temporal intervals. For example, a TV program starts at 9:00
pm, and finishes at 11:00 pm. The TV program can be considered as one of multimedia
objects. In addition, “interval” is considered as a range from 9:00 pm to 11:00 pm, and
“duration” as two hours. Allen’s relations require this duration of the interval. Before
designing the specification model, interval duration must be known. This means that
multimedia database systems must determine duration of multimedia objects, because
presentations are almost dependent of duration [19].
Our work focuses on scenarios that are a natural means of playing and modeling
temporal composition relations in an application domain. In our approach, the creation of
scenarios is based on extended temporal relations advocated by Allen [3].
The approach presented in this paper is based on the MP-RdPT net for modeling
temporal constraints and user interactions where multimedia objects will be represented as
places, while transitions of the Petri net will be used for synchronization between the
objects. The approach provides the following benefits:
(1) The ability to deal with non-deterministic time intervals, e.g. objects with an unknown
duration, objects whose reproduction can fail and objects that represent user interactions.
(2) The possibility of automatic detection of inconsistent synchronization conditions such
as “A precedes B, B precedes C, C precedes A”.
(3) A graphical notation to describe and simulate the presentation.
(4) An editor which abstracts the internal Petri net representation and allows the user to
think in familiar terms such as “precedence” or “overlap”.
(5) Automatic generation of a MP-RdPT net based on the previous temporal specification.
(6) Automatic analysis of the MP-RdPT properties: safeness, liveness, reversibility and
consistency.
A first version of our approach [12], [13] considers multimedia objects of known or
unknown duration and interactive relations, but doesn’t consider dependency temporal
relations between multimedia objects. This is the main difference between the first version
of our approach and the second one that will be described in this paper.
In this paper, we highlight the following points: related work and background
(Section 2), our scenario temporal specification (Section 3), a formal definition of the MP-
RdPT net (section 4), multimedia scenario representation model (section 5) and analysis
of multimedia scenarios using the tool Tina (section 6).
2 Related work and background
Existing temporal models for multimedia may be decomposed into two classes:
instant-based and interval-based [26]. In instant-based models, the elementary units are
instants in a time space. Each event in the model has its associated time instants. The time
instants arranged according to some relations such as precede, simultaneous or after form
complex multimedia presentations. An example of the instant-based approach is timeline,
in which media objects are placed on several time axes called tracks, one per each media
type. All events such as the beginning or the end of a segment are totally ordered on the
timeline.
Several approaches support instant-based models such as Hy-Time [16] or [14],
[10]. The model is well suited for temporal composition of media segments of known
durations; however it falls short for unknown durations. Other authors have proposed to
use relations between interval end points for temporal composition of multimedia
(temporal point nets [6], MME [8]). However, their use is difficult and results in
complicated, unstructured graphs. In addition to that, their use may led to an inconsistent
specification in which contradictory conditions are specified for intervals. In this case, a
verification algorithm (called sometimes a temporal formatter) must check for
inconsistency [6].
Interval-based models consider elementary media entities as time intervals
ordered according to some relations. Existing models are mainly based on the relations
defined by Allen for expressing the knowledge about time [3]. Giving any two intervals,
they can be arranged according to seven relations: before, meets, overlaps, finishes,
during, starts, equals. However, using Allen’s relations for multimedia composition faces
several problems. First, the relations were designed to express existing relationships
between intervals of fixed duration and not for specifying relationships that must be
always satisfied even when interval durations are changed.
Another problem with the Allen relations is their descriptive character. They allow
expression of an existing, a posteriori arrangement of intervals, but they do not express
any causal or functional relation between intervals. So, the Allen relations can be useful
for characterizing an existing, instantiated presentation (a presentation for which all start
and termination instants of media segments are known).
The third problem with the Allen relations is related to inconsistent specifications that
can be introduced to a multimedia presentation. Detecting inconsistent specification
requires algorithms of complexity [O(N2)], where N is the number of intervals [3].
Many approaches are based on time interval. For example Little and Ghafoor
proposes an OCPN model equivalent to Allen’s relations [21]. They do not take into
account possible unknown durations of intervals and to prepare an instantiated
presentation (a presentation in which all interval end points are determined), they must
traverse the tree of interval relations to get deadlines used to schedule the presentation.
King proposes a different formalism based on a temporal logic [20]. He shows how
the Allen relations can be expressed using temporal logic formula. Although his
formalism has solid mathematical bases, composition of multimedia presentations using
declarative formula is awkward. Logic formulas do not correspond to the mental image
that an author uses in conception. Moreover, to be useful, the formalism must be
supported by a consistency checker and an interpreter to execute a given temporal
specification. [11] develops a software architecture for multimedia object synchronization
and communications called SAMOCS. The object-oriented database management system
VODAK [1] supports temporal operations.
Courtiat and De Oliveria [8] presented a synchronization model for the formal
description of multimedia documents. This model automatically translates the user
formalization into a real-time LOTOS formal specification and verifies a multimedia
document aiming to identify potential temporal inconsistencies. Described through a
hierarchical model, multimedia documents allow incomplete timing. The model also
represents user interaction and expresses a media object as one logical unit. The model
provides a set of synchronization patterns, formal semantics, and a verification technique.
Blakowski and Steinmetz [5] recognized an event-based representation of a
multimedia scenario as one of the four categories for modeling a multimedia presentation.
Events are represented in the Hypermedia/Time-Based Structuring Language (HyTime)
and Hypermedia Office Document Architecture (HyperODA). Events are defined in
HyTime as presentations of media objects along with the playout specifications and finite
coordinate system (FCS) coordinates. HyperODA events happen instantaneously and
mainly correspond to start and end of media objects or timers.
All these approaches suffer from poor semantics conveyed by the events. Moreover,
they don’t provide any scheme for composition and consumption architectures. You’ll
find and interesting survey on authoring models and approaches elsewhere [17].
The interval-based models face some disadvantages. Firstly, the temporal relations are
designed to specify relations between multimedia objects of determined duration, but they
are not designed for specifying relations that are not explicitly determined by the user.
Secondly, the temporal relations describe existing arrangement of multimedia objects, but
do not describe dependency relations between multimedia objects. For example, x meets y
means that the end of multimedia object x coincides with the end of multimedia object y,
but it does not describe whether multimedia object x starts multimedia object y, or
whether multimedia object y stops multimedia object x. So, the majority of current models
are interesting for describing presentations in which all start and end instants of
multimedia objects are determined and fixed, but they are not appropriate when the
duration of multimedia objects is not fixed. Thirdly, the detection of inconsistent
specifications that may be introduced into a multimedia presentation requires complex
processes.
To resolve theses disadvantages, a recent approach [27], considered in some
systems such as STORM [2], is proposed to allow temporal specification of dependency
relations between multimedia objects of unknown duration. It defines a set of operators
expressing causal relations between multimedia objects. It can be used to form nested
multimedia object duration.
One disadvantage of this approach is that not all scenarios can be expressed by means
of those operators. For example, the scenario presented below cannot be described,
because of interleaved start and stop actions on parallel branches. Temporal point nets,
such as [9] and [6] can describe such scenarios, however, the resulting graph become
complex and difficult to modify.
x
z
y
w
v
Fig. 1. Example of difficult scenario
Another disadvantage of this approach is its dependency aspects. It allows the
expression of causal or dependent relation between multimedia objects. So, if a
multimedia object fails, all the multimedia objects that depend on the failed multimedia
object fail too. If x fails, the multimedia objects y, z, w, v that depend on the failed
multimedia object x, fail too (see Fig. 1). For these reasons, we propose a model based on
both time-interval and Weiss causal relations.
3 Our Scenario temporal specification
We will present a model for temporal composition of multimedia objects. The model
is based on time-interval [3] and Weiss relations [27]. We consider the seven relations of
Allen [3] (equals, meets, finishes, starts, overlaps, during) with the following features:
Firstly, the temporal relations are designed to specify relations between multimedia
objects of both deterministic and non-deterministic duration. Secondly, the temporal
relations describe both existing arrangement of multimedia objects, and dependency
relations between multimedia objects. For example, x meets y means that the end of
multimedia object x coincides with the end of multimedia object y, or it describes whether
multimedia object x starts multimedia object y, or whether multimedia object y stops
multimedia object x. Thirdly, the detection of inconsistent specification is not necessary.
3.1 Interval
Our elementary entities are time intervals. Time interval I is defined by the end points
(Ibegin ≤ Iend) as I = {t | Ibegin≤ t ≤ Iend }. The duration of interval I is d=Iend - Ibegin , and can
be constant (e.g. 5 seconds), dependent on the intrinsic playing time of the medium (e.g.
playing time of a video segment) or unspecified (e.g. user interaction or live feed). In this
paper each interval corresponds to the presentation of one object (e.g. an image or a music
selection). In that sense, the beginning and the end of an interval are logical times which
will really correspond to physical time during the effective presentation to the user.
In our temporal specification language, an interval I is declared in this way:
multimedia-object (min, opt, max): media-type, where min, opt and max are respectively
the minimum, optimal and maximum admissible duration of the related interval.
3.2 Temporal relations
Several relationships have been defined on time intervals: before, meet, equal, overlap,
during, start, finish [3]. Usually, they are binary relationships but can be easily extended
to n-ary ones [22]. Sequential relationships combine intervals which share the same
timeline (mutual exclusion), occurring one after the other with (before) or without delay
(meet) between them. Parallel relationships relate intervals which have their own timeline.
In our model these relations are used for composing and synchronizing multimedia
objects in presentations.
3.3 Interactive relations specifications
Our approach synchronizes the scenario with the user (i.e. an expert of the application
domain). The interaction takes the form of temporal interaction (start, stop, pause,
reverse, and forward) and browsing interactions.
Temporal interactions concern user elementary operations such as pause/resume,
reverse and forward. In pause/resume operations, the system records the current state of
presentation modeled by a MP-RdPT net, and when resume operation is executed; the
system loads the amount of time that the presentation had paused, and starts the
presentation again from where it stopped. The reverse operation is specified in terms of
temporal skip given by the user. Example “goes back 15 minutes”.
When the reverse operation is requested, then the Petri net deals with objects
associated with places currently being presented. If the reverse operation involves objects
that are further behind a place Pi in the presentation graph, the presentation graph is
traversed backward until the target object is reached. The forward operation is similar to
the reverse operation.
Other approaches have been implemented for interactive movies by using the
hypertext paradigm [7]. The essence of hypertext is a non-linear interconnection of
information, unlike the sequential access of conventional text. Data is linked via cross-
referencing between keywords to other parts of data. One hypertext called Petri Net-
Based-Hypertext (PNBH) [24] describes data units as net places and links as net arcs.
Transitions in PNBH indicate the navigation through relations.
In Fig.2 we present the Backus-Naur Form (BNF) of the grammar of our temporal
specification language:
::= scenario declarations
{}*assigns{}* interactions
{}* relations {}* end.
::=
::= [(TimeInterval>)] :
;
| : SCENARIO;
| : BUTTON;
::= /* OID */
::= [integer,integer] /* Time */
:: =audio | video | image | text | animation | button
:: = assign ( , )
::= interaction (ButtonObject, )
::= [:=]{ |
| | | | | |
| | }
:: = equals ();
::= meets ();
::= before (,);
::= starts(, );
::= during(, );
::= finishes(, );
::= overlaps(, );
::= par_min();
::= par_max();
::= par_master();
::= ,
::= | |
|
Fig.2. The BNF form of the grammar
4 Formal definition of the MP-RdPT net
Let ℑ be a temporal domain. A MP-RdPT on ℑ is a tuple (P, T, B, F, M0, IS, SYN, MP,
R), where:
- (P, T, B, F, M0) defines a Petri Net where P is a non empty finite set of places, T is a
non empty finite set of transitions, with P∩T = ∅, B : P x T → N is the backward
function, similarly, F : R x T → N is the forward function, M0 : P → N is the initial
marking.
As usual, we denote by:
def def
{ p ∈P | F(p, t) ≥ 1 } the set = {p ∈ P | B(p, t) ≥ 1 } the set of ingoing places and t• = •t
def def
{ t ∈ = { t ∈ T | F(p, t) ≥ 1 } and p• = of outgoing places of a transition t. Similarly, •p
T | B(p, t) ≥ 1 } are the sets of ingoing transitions and outgoing transitions of a place p.
The set of markings a MP-RdPT can reach from its initial marking Mo will be denoted as
R (Mo).
- ∀ p ∈P, ∀ M ∈ R(Mo), M(p) ≤1 (a MP-RdPT is safe),
- IS: is the static interval function
IS : P → (Q+ ∪ 0) (Q+ ∪ 0) ∪ (Q+ ∪ ∞), Such as : ∀p∈P : IS(pi) = [a, n, b] with 0 ≤ a
≤n ≤ b.
The IS function associate with each ingoing place a static validity time interval, where (a,
n, b), associated with a place, represents respectively the earliest, nominal, and the latest
firing times.
- SYN is the synchronization function that defines the firing rule associated to a transition,
SYN: T → Rules, with Rules = def {strong_or, weak_and, master}, the set of
synchronization rules. This synchronization semantics defines synchronization instants
from a place statically or dynamically chosen. -MP is the function which indicates the
master place of each transition from which the rule of transition requires a master, defined
by : MP : Tmaster =def {t | SYN(t) = master} → •t,
If we note α = {ai | [ai, bi] ∈ IM}, β = {bi | [ai, bi] ∈ IM}, then, according to the case of
SYN (T), we consider that:
The strong_or synchronization rule is driven by the earliest stream. If either one of the
two streams finishes, the other one has to stop, and [min (α), min (β)] is the
sensibilisation interval.
The weak-and synchronization rule is driven by the latest stream. All the streams are
presented completely, and [max (α), max (β)] is the sensibilisation interval.
The master synchronization rule is driven by the master stream. If two streams are
presented simultaneously, when the higher priority stream finishes, the other has to stop.
The multimedia continues after that, and [am, bm] is the sensibilisation interval, with pm
which indicates the master place. We define am, bm by: let MP (t) = pm and IM (pm) = [am,
bm].
- R: P → {r1, r2 …}, a mapping from the set of places to a set of resources.
5 Multimedia scenarios representation model
Our approach is composed of a core and a series of functionalities which revolve around it
(see Fig. 3). The core is a formal representation model built on the MP-RdPT model. As
for the functionalities, they relate to the management of the temporal non determinism, the
editing/creation of the scenarios, the presentation and the properties analysis of the
scenarios.
E d itio n b y a s p e c ific a tio n
la n g u a g e
C r e a tio n
M a n a g e m e n t o f P e tri n e t b a s e d
th e te m p o ra l n o n P r e s e n ta tio n
R e p re s e n t a tio n
d e t e r m in is m M o d e l M p - R d P T
P ro p e rt ie s
A n a l y s is
Fig. 3. The various elements of our approach.
5.1 Petri net generation
To create the MP-RdPT net, each temporal relation is associated with a Petri net as
illustrated by [15], and modeled in several approaches, such as in OCPN [21]. This
mapping is helpful for automatic creation of a MP-RdPT net. In fig 4, Tα, Tβ, Tδ model
respectively the duration of places Pα, Pβ and Pδ.
Temporal relations MP-RdPT Causal relations MP-RdPT
Pα Pβ
Tδ Tα Tβ Tα
Tδ Pα
Pαα
Pα
before(Pα,Pβ, Tδ) Pα Pδ Pβ
Pα Pβ Tα
Tβ Weak-and
Pβ
meets(Pα, Pβ) Pα PβPβ Tβ
Tα Strong-or
Pα Pα Pβ
Par-min(Pα, Pβ)
Pβ Tβ
begin(Pα, Pβ) Pβ Pα
Pδ
Weak-and Tα
Pα Tα
Pα
Pα Weak_and
Pβ
equal(Pα, Pβ) Tβ Pα
Tδ Pβ
Pβ
Tδ Pα Pβ
Tα Weak-and Strong-or
Pβ Weak_and Tβ
Pδ Pα
finishes(Pα,Pβ, Tδ) Tβ Par-max(Pα, Pβ) Pβ
Pβ
Tα
Tδ Master Pα
Tδ Pα
Pβ Pδ Pα Tα
during(Pα, Pβ, Tδ) Tβ
Pβ
Tβ Pα
Master
Tδ Tδ Pβ Pδ
Pβ Master
Pδ Pβ
Pα Tα Tβ
Par-master(Pα, Pβ)
overlaps(Pα, Pβ, Tδ) Pβ
Pα
Fig. 4. MP-RdPT associated with temporal and causal relations
Before approaching these two stages, we present the two principles, inspired by those of
[15], which guide the process of the Petri net creation. These principles are based on an
association diagram between the temporal relations and the Petri nets (see Fig. 4).
5.2 Principles
Principle 1: For each temporal relation between two intervals, there is an equivalent Petri
net model.
The Fig. 4 presents associations of temporal relations between intervals and the Petri nets.
Each Petri net is composed of places representing the intervals. The delays used in the
temporal relations like before, overlaps, during, finishes, are represented by places with
validity time interval: [min, opt, max] = [delay, delay, delay].
Principle 2 is a generalization of principle 1.
Principle 2: A complex and arbitrary multimedia scenario, composed of temporal
relations, can be built with Petri nets by replacing the temporal relations by the associated
Petri nets. Principle 2 has guided to the development of the creation algorithm of the Petri
net.
The creation of the Petri net starts at the end of the lexical, syntactic and semantics
analysis of the editing program, if no error was detected.
5.3 t-Time Petri net
A t-time Petri net is a tuple (P, T, B, F, M0, IS), where:
(P, T, B, F, M0) defines a Petri net, and IS: T → Q+ x (Q+ ∪ {∝}) is the static time
interval function. The application IS associate with each transition t of the net an interval
with rational bounds IS(t) = [min, max] with 0 ≤ min ≤ max, and max can be ∝. For
further details, see [23].
5.4 Rules of translations
The created MP-RdPT net is then translated to an equivalent t-time Petri net for analyzing
by the tool Tina [4]. For this, we use three rules of translation (see Fig. 5) inspired from
[25]:
P ’1 (y 2 - x 2 , y 2 - x 2 ) P 1 ’’
(x 1,y 1) (0 , 0 )
P 1 (x 1, n 1, y 1)
P 1
(0 ,+ )
P 3 P 3
S Y N (t)
(0 , 0 )
P 2
(a ) (0 , 0 )
(x 2, n 2, y 2 )
P 2 (x 2, y 2) P ’2 (y 2-x 2, y 2-x 2) P 2 ’’
(x 1, y 1) (b )
P 1 P 1’ (y 1-x 1, y 1-x 1) P 1 ’’ ( 0 , 0 )
P 1 (x 1, y 1) P 1’ (y 2-x 2, P 1 ’’ (0 , 0 )
P 3
(0 , )
(0 , )
(0 , 0 ) P 3
(0 ,+ )
(0 , ) (0 , 0 )
P 2 (x 2, y 2) P ’2 ( y 2 - x 2 , y 2 - x 2 ) P 2 ’’
P 2 (x 2, y 2) P ’2 (y 2-x 2, y 2-x 2) P 2 (0 , 0 )
(c ) (d )
Fig. 5. Translation of an inter-stream synchronization schema of a MP-RdPT net
(a) in the form of a t-time Petri net (b, c, d) according to inter-stream synchronization
(b) transition of the type «master », (c) transition of the type « weak_and», (d) transition of the
type « strong_or ».
6 Analysis of multimedia scenarios using the tool Tina
Tina (Time Petri Net Analyser) [4] is a software environment to edit and analyze Petri Net
and t-time Petri Net [23]. In addition to the usual editing and analysis facilities of such
environments (computation of marking reachability sets, coverability trees, semi-
flows), Tina offers various abstract state spaces constructions that preserve specific
classes of properties of the concrete state spaces of the nets. Classes of properties
may be general properties (reachability properties, deadlock freeness, liveness),
specific properties relying on the linear structure of the concrete space state properties
relying on the linear concrete space state (linear time temporal logic properties).
After generating the t-time Petri net, the author investigates the scenario specification
before it is delivered to the reader by using the analysis tool Tina. Currently, the following
characteristics can be verified by the analysis tool: terminate state existence (i.e., if a state
m exists in which non transitions are enabled), safeness (i.e., if every place has only one
token), liveness (i.e., if blocking will never occur), reversibility (i.e., if the Petri net come
back to its initial state whatever state it reaches), consistency (is a necessary condition for
the reversibility that is a difficult property to establish.
7 Conclusion
Many existing specification models of multimedia temporal composition are based on
Allen’s relations. However, the current implementations of Allen’s relations are not
appropriate enough for some real world temporal compositions. The multimedia object
duration must be known before designing the scenario, and any change in the duration
may modify the temporal relations that exist between the multimedia objects. So, we
proposed a temporal composition model based on an optional temporal duration. In our
temporal specification, the user has the possibility to define a temporal specification
which may be either relations depending on multimedia object duration or relations
reflecting causal dependency between multimedia objects when the duration is unknown.
Finally, a powerful Mp-RdPT model based on temporal specifications is used to specify
multimedia scenarios. In addition, MP-RdPT is translated to an equivalent t-time Petri net
for the analysis of multimedia scenarios properties by using the tool Tina. Tina allows the
author to investigate the document specification before it is delivered to the reader.
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