Download DYNAMIC NET DATA: THEORY AND EXPERIMENT

DYNAMIC NET DATA: THEORY AND EXPERIMENT
Philippa Gardner, Nobuko Yoshida, Sergio Maffeis, Alex Ahern
Department of Computing, Imperial College London
WHAT IS DYNAMIC NET DATA?
MODELLING DYNAMIC NET DATA IN Xdπ
Web data, such as XML, plays a fundamental role in the exchange of information
between globally distributed applications. Applications naturally fall into some sort of
mediator approach: systems are divided into peers, with mechanisms based on XML for
interaction between peers. The development of analysis techniques, languages and tools
for web data is by no means straightforward. In particular, although web services allow
for interaction between processes and data, direct interaction between processes is not
well-supported.
We model large scale, peer-to-peer systems for sharing dynamic data over the Net. In
this setting, distribution is on a large scale, with many sites providing and consuming data
using a standardised set of functionalities. The data itself is interlinked and dynamic,
containing calls to web services, forms, scripted code, etc.
Semi-structured
Data
XML, XLink,…
SOAP
Diverse
Languages:
C#, Java, …
Web
Web
Active Pages
Applets
Java/ECMAScript
Java
Peer-to-peer data management systems
are decentralised distributed systems,
where each component offers the same
set of basic functionalities and acts both
as a producer and as a consumer of
information. We model systems where
each peer consists of an XML data
repository and a working space with
active processes.
Our processes can be regarded as agents with a simple set of functionalities; they
communicate with each other, query and update the local repository, and migrate to other
peers to continue execution. Process definitions can be included in documents and can be
selected for execution by other processes. These functionalities are enough to express
most of the dynamic behaviour found in web data, such as web services, distributed (and
replicated) documents, distributed query patterns, hyperlinks, forms, and scripting.
The Xdπ calculus provides a formal description of such systems. It is based on a network of
locations (peers) containing a (semi-structured) data model, and π-like processes for
modelling process interaction, process migration, and interaction with data. The data model
consists of unordered labelled trees, with embedded processes for querying and updating
data, and explicit pointers for referring to other parts of the network.
EXISTING MODELS
•Query languages for semi-structured data (XML) only describe data manipulation without
taking into account the distribution of information.
•Process calculi, whilst good for orchestrating data exchanges between peers and
distributed infrastructure, tend to abstract away from the actual data.
Modelling dynamic Net data requires merging these approaches.
OUR MODEL: Xdπ
•XML-like dynamic-data repositories
•Explicit distribution
•Coordination based on π-calculus
The model consists of a flat space of
locations, where each location contains
(XML) trees and coordination processes.
L2
L1
L3
Processes
Trees
L4
a
c b
P
a
a
c
Processes
Processes
a
c b
@L1:a/c
L1
Data consists of unordered, edge-labelled
trees, containing scripted processes and
L2 pointers to data in other locations.
AN EXAMPLE: WEB SERVICES
We embed in data the process
which represents a call to a web
service get at site L2 with parameter
a/c, a path expression representing a
query on the data of L2.
The stretchable band
between
processes denotes the sharing of a secret
channel name.
= go L2.get<a/c,L1,put>
= (new put)(
= put(x).pastea/e<x>
a
b
e
c
= !get(x,y,w).copyx(z).go y.w<z>
|
)
a
a
c
P
R
b
b
c
c
e
Q
a
b
T
The execution continues with
the service instance reading the
data T from the tree at a/c,
and then migrating to the peer
L1 obtained as a parameter of the
service invocation.
a
b
a
a
c
e
P
R
b
T
b
Q
c
a
c
e
b
T
L1
a
b
L2
c
a
a
c
e
R
b
P
b
Q
T
c
a
c
e
b
T
L1
L2
L2
L1
a
a
We follow the execution: the first
step is the migration of the service call ,
followed by the invocation of the web
service , which spawns a new
service instance .
c
b
c
e
a
a
c
b
R
P
b
Q
a
c
c
e
b
T
L1
a
b
e
L2
c
a
a
c
b
R
P
Q
b
c
e
a
At L1 the required data item is
passed to the result handling code
on the secret channel, and the result
data is inserted in the original tree.
c
c
e
a
a
b
R
T
P
b
Q
c
a
c
e
b
T
L2
L1
a
b
c
a
a
c
e
b
b
T
L1
T
L1
b
c
R
P
Q
b
e
c
a
c
b
T
L2
L2
THE UNIFIED FRAMEWORK
IMPLEMENTATION
We reason about data and the distributed infrastructure in the same framework to:
•understand the system behaviour
•control access to resources
•give schemas/types to documents containing scripts
•propose new optimisations.
Alex Ahern, Philippa Gardner, Gurdish Gill, Ameet Shah.
Several prototypes of Xdπ have been constructed in a variety of languages:
Java Abstract Machine
•Round-robin term evaluation.
•XML used for data structures.
•XPath used as the data query language.
•Migration by web service invocation provided by Apache Axis.
•Browser-based user interface.
•An ongoing student project is to build an API combining Xdπ
communication and thread migration with Java code.
PROCESS BEHAVIOUR
Philippa Gardner, Sergio Maffeis.
We define process equivalence in such a way that when equivalent processes are put in
the same position in a network, the resulting networks are equivalent. This work involved
adapting, in a non-trivial way, bisimulation techniques used for the higher-order π-calculus.
Equational reasoning provides formal proofs of the (partial) correctness of
implementations with respect to specifications. We have studied examples, including the
transparent replication of web services.
SECURITY AND TYPES
Alex Ahern, Philippa Gardner, Jonathan Hayman, Sergio Maffeis, Nobuko Yoshida.
Security is a central concern for systems sharing dynamic data on the Net. We are
currently studying:
•fine-grained access control for web services and documents, extending techniques
studied for the distributed π-calculus, and using spatial logic formulae annotated with read
and write capabilities to describe permissions on data;
•type systems for statically guaranteeing the structure of Xdπ data, adapting techniques
from semi-structured data and π-processes.
O’Caml Abstract Machine
•Functional language.
•Custom data structures.
•Migration by object serialisation and transmission.
•Text-based user interface.
Future Work
Developing a browser for dynamic XML documents. These documents will contain scripted processes which the browser can
interpret and execute. Documents will be queried using XQuery and will be statically typed.
REFERENCES
Modelling Dynamic Web Data, Gardner and Maffeis, Imperial College London Technical
Report Nr.2003/14, October 2003. Extended abstract in Proc. of DBPL'03, LNCS 2921.
Invited submission to the Journal of Theoretical Computer Science.
Behavioural Equivalences for Dynamic Web Data, Maffeis and Gardner, Submitted.
February 2004.
A Language for Updating Web Data, A. Ahern, Master’s Thesis, Imperial College London,
2003.