DYNAMIC DEPLOYMENT OF SEMANTIC-BASED

SERVICES IN A HIGHLY DISTRIBUTED ENVIRONMENT

Christos E. Chrysoulas and Odysseas Koufopavlou

Electrical and Computer Engineering Department of University of Patras, Rio, 26500, Greece

Keywords: Semantic Service Discovery, Semantic Web Services, Node Model, Dynamic Service Deployment.

Abstract: Today’s Networking Systems tend to increase in both heterogeneity and complexity. So there arises the

need for an architecture for network-based services that provides flexibility and efficiency in the definition,

deployment and execution of the services In this paper we present an approach that applies a Semantic-

based Service deployment framework, which enables the provision of parallel applications as QoS-aware,

whose performance characteristics may be dynamically negotiated between a client application and service

providers. Our component model allows context dependencies to be explicitly expressed and dynamically

managed with respect to the hosting environment, computational resources, and dependencies on other

components.

1 INTRODUCTION

Network and service management fields find

themselves nowadays at crossroads with middleware

technologies, new network architectures and

emerging research directions. Middleware

technologies like web services have reached

maturity enjoying wide deployment and adoption.

Network architectures and infrastructures built for

different purposes are on their way towards IP

convergence giving rise to new integrated and more

complex architectures. Finally, recent ambitious

research directions like autonomic computing and

communications have already made a dynamic

appearance in the networking community raising the

challenges even higher.

This activity has coincided with the end of a

period in network and service management during

which vast experience and lessons learned have been

accumulated based on what constitutes the past state

of the art in telecommunications and in data

networks, realized by many as CORBA-based

distributed management platforms and SNMP-based

platforms, respectively.

This encounter in the making already produces

speculation and activity about redefining/reassessing

the initial requirements that drove the developments

in network and service management during the past

period and about the “shape” of management when

projected into the future.

The most prominent decentralized management

approaches are based on distributed object

technologies as CORBA (Common Object Request

Broker Architecture) (Object Management Group,

2006) and Java RMI (Remote Method Invocation)

(Jae-Oh L, 2000). According to these paradigms,

information can be gathered from any location based

on invocations of distributed remote objects on the

target network element. The afore- mentioned

distributed object technologies allow management

operations to be performed on simple service-

oriented APIs. On the downside they are resource

expensive for large object populations, resulting in

suboptimal object retrieval.

Apart from decentralized approaches based on

agents or distributed object technologies, there are

also approaches offering management capabilities

over the Web. Approaches that are based on the

Common Information Model (CIM), which

encompass a set of common management operations

(Distributed Management Task Force, 2006).

As network infrastructure is shifting towards

service-centric networks a number of architectural

characteristics are likely to influence management

operations and functionality and dictate the specific

choices of technologies that realize thereof. To our

view, three of such characteristics are going to play

a crucial role in the coming years:

416

E. Chrysoulas C. and Koufopavlou O. (2007).

DYNAMIC DEPLOYMENT OF SEMANTIC-BASED SERVICES IN A HIGHLY DISTRIBUTED ENVIRONMENT.

In Proceedings of the Third International Conference on Web Information Systems and Technologies - Web Interfaces and Applications, pages 416-419

DOI: 10.5220/0001278504160419

 SciTePress

1. Federated Network Architectures

In an effort to provide seamless end-to-end

connectivity that meets customer demands,

networks/service providers have started forming

federations of networks wherein a number of

operations like AAA, monitoring and SLA support

are treated in homogeneous way in a heterogeneous

environment.

2. Network architectures with distinct

separation of concerns

The most representative example is the

separation of control from the forwarding plane

(Yang L et al, 2005), which allows the two to evolve

separately of each other. The binding element

between the two is a set of open interfaces that

abstract functionality and allow access to

functionality and resources that are vendor

independent.

3. Distributed Network Node Architectures

Individual network nodes and other devices are

clustered together in order to form more complex

and extensible distributed architectures that operate

as one integrated node. Such constellations provide

the means of adding resources as needed and foster

dynamic service deployment, namely, injecting new

functionality in the network.

In such context, management faces a number of

challenges originating from the increasing

complexity and size of networks, the heterogeneity

of devices and technologies that must coexist and

the high degrees of flexibility required in services.

This has been primarily the motivation of our

research presented in this paper, which touches upon

these issues by exploring potential solutions on the

service deployment and resource management

within a network architecture.

We have based our designs on web services as

the ‘de-facto’ omnipresent standard technology in

networks with high integration capability and one of

the most promising approaches to future

management technologies.

The remainder of the paper is organized as

follows: Section 2 describes in depth the proposed

architecture regarding the dynamic service

deployment and a user-case scenario of the

deployment of a new service is also presented.

Conclusions and future work are presented in

Section 3.

2 DYNAMIC DEPLOYMENT OF

SERVICES

2.1 Dynamic Service Deployment

Definition

Dynamic Service Deployment refers to a sequence

of steps that must be taken in order to deploy a

service on demand. The necessary steps regarding

the service deployment are service code retrieval,

code installing destination according to

matchmaking algorithms, and service deployment.

The matchmaking algorithms provide the most

efficient use of system resources by examining the

available resources of our system and comparing

them with the resources required by the service to be

deployed.

2.2 Proposed DSD Architecture

Figure 1: Internal architecture of Dynamic Service

Deployment service.

Figure 1 describes the internal architecture of the

Dynamic Service Deployment service:

• Semantic Web-Service Server: The Web-

services server sub-component hosts the

interfaces needed for the communication of

the whole DSD Module with the External

environment. The Web-service server sub-

component has the functionalities needed to

This component also is capable of finding

other Web-service interfaces.

DYNAMIC DEPLOYMENT OF SEMANTIC-BASED SERVICES IN A HIGHLY DISTRIBUTED ENVIRONMENT

417

• DSD Manager: The DSD manager sub-

component has two functions, depending

on whether a user profile is required:

o The DSD manager must download

the user profile, in order to find,

which services must be deployed,

and provides the request to the DSD

controller.

o In the case of a bootstrap process,

the DSD manager passes the

bootstrap services required for

deployment to the DSD controller.

The DSD manager is responsible for

checking whether a user has terminated the

connection, and for undoing the user’s

personal configuration.

• DSD Controller: The DSD controller sub-

component has the following duties: it

receives the service request from the DSD

Manager, communicates with the proper

database in order to download the service

code and the service requirements, retrieves

the available resources from the node

model, performs the matchmaking

algorithm in order to find the most suitable

resources, and finally deploys the service.

The DSD controller is responsible for the

services in three dimensions: download,

deploy, and configure.

• Node Model: The node model is

responsible for keeping all information

regarding our system. It provides a

complete view of the system, and contains

information on available and used physical

resources, as well as data on running

services.

2.3 Semantic Description of Services

The first step to semantically deploy services is to

have a description of services.

The ontology chosen for our service description

is based on standard device property descriptions

and tries to be generic and to cover also implicit

information left out of those classifications.

Figure 2 is a part of this ontology and illustrates

that a service publishes its description and can be

provided by different kind of devices:

Our service ontology is independent of any

service model and implementations and can be

applied to EJBs (Monson-Haefel, 2000), CORBA

Components, Fractal components (Bruneton et al,

2006), OSGiTM bundles/services (OSGI

Figure 2: Proposed ontology.

Alliance, 2005) or Web services (Newcomer, 2002).

Our service description is also independent of

any description languages and can be written in

different standard description languages such as

WSDL (Newcomer, 2002), UDDI/XML

(Newcomer, 2002) or OWL (McGuinness, van

Harmelen, 2004).

2.4 Semantic Description of

Deployment

The second step for the semantic deployment of

services is to define the description of the

deployment itself.

As we have seen in the previous section, each

service has its own semantic description. In the same

way, each execution platform has its own semantic

description. The important description that we add is

the semantic deployment description. This

description is attached to the platform and links the

different services to the platforms they are running.

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418

Figure 3: Proposed platform ontology.

This semantic deployment description can be

instantiate in various different ways that we have

also described in an ontology:

Figure 4: ServiceDeployment ontology.

For instance, figure 4 shows that the deployment

can be optimized according to resources constraints

(such as CPU, memory, etc), or can apply migrations

to follow a user or can be customized by the user.

3 CONCLUSIONS AND FUTURE

WORK

In this paper, we presented an architecture for the

semantic deployment of services in a highly

distributed environment. This architecture, based on

a middleware distributed on each device, specially

includes a Deployment Service interacting with

discovery and interoperability middleware services.

This Deployment Service takes into account the

semantic description of services and the semantic

description of deployment itself to apply a

semantically and timely local deployment strategy.

We presented an architecture that adds a

dynamic perspective to a Web-service-based

infrastructure. Our component-based model

addresses the issue of dynamic deployment of new

services in a highly distributed environment and the

way these address each other in that environment.

We expect that this work is not only relevant to the

Grid community but also to the Web-services and

the network communities as we not only addressed

concerns related to Grid computing but also

discussed architectural issues regarding Web-service

configuration and deployment.

As future work we plan to provide a more

sophisticated model for service deployment and

selection based on QoS properties.

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