Service Composition Based Middleware Architecture for

Mobile Grid

M.A. Maluk Mohamed and D. Janakiram

Distributed & Object Systems Lab,

Dept. of Computer Science & Engg.

Indian Institute of Technology Madras, Chennai, India

Abstract. Service Composition refers to the construction of complex services

with the help of more primitive and easily executable services or components.

With the proliferation of wireless communication and the mobile Internet, the

demand for mobile data services has increased. In addition the recent spurt of e-

services and m-services has increased the importance of service composition. We

envisage service composition to play a crucial role in providing mobile devices

access to complex services. The basis for our proposed approach is to virtualize

the individual system resources as services that can be described, discovered and

dynamically conﬁgured at runtime to execute an application. The paper discuss a

novel paradigm which integrates mobile devices into the traditional grid, with the

capability for composition of services. To accomplish such a global service com-

position in the new model we propose to add functional layers over the already

proposed Anonymous Remote Mobile Cluster Computing model. The idea be-

hind such middleware is to use the available resources efﬁciently and to hide the

complexity inherent in managing heterogeneous services. This paper describes

the unique capabilities of the proposed middleware and gives the layered view of

the proposed architecture.

1 Introduction

The recent wave of innovation in computing, wireless communications, networking and

electronics has embedded processing power, storage space and communication capabil-

ities in electronic devices of day-to-day use, leading to the era of ubiquitous computing

[1]. This trend has led to the pervasiveness [2], invisibility [3] and mobility of com-

puting nodes. This has seen the availability of services also on the mobile devices in

addition to the services available in the ﬁxed network. This lead to the idea of integrat-

ing mobile devices into the grid, forming a new paradigm known as Mobile Grid.

The recent past has seen very fast growth in processing and networking capacity

around the world. This has increased the need for software that can operate across

multi-organizational resources at a higher level of abstraction than network protocols

and independent interactive applications. Grid Computing [4] has emerged as a tech-

nology for coordinated large-scale resource sharing and problem solving among many

autonomous groups. In Grids resource model, the resource sharing relationships are dy-

namic, attendants can join or leave multiple relationships at any time. However, Grid

A. Maluk Mohamed M. and Janakiram D. (2005).

Service Composition Based Middleware Architecture for Mobile Grid.

In Proceedings of the 2nd International Workshop on Ubiquitous Computing, pages 39-46

DOI: 10.5220/0002571400390046

 SciTePress

requires a stable quality of service and the changing of sharing relationship can never

happen frequently. There are many technical concerns that are addressed to produce ef-

fective grid computing. This may include information services, security, scheduling and

resource management, performance, remote data access and archiving, and program-

ming model. To this end, the model works for a conventional distributed environment

but is challenged in the highly variational wireless mobile environment.

With the growing demand for mobile data services, novel value-added services and

content provisioning will be the driving force behind the development and deployment

of future communication networks and mobile Internet. As the Internet evolves and ex-

pands to include next-generation, data-enabled mobile devices, it is important to make

data services available on these devices rapidly. It is essential to enable quick and ﬂex-

ible development and deployment of end application functionality. Such functionality

should be enabled in the presence of a wide variety of heterogeneous access networks.

Service mobility is the feature where the user can access the same set of services seam-

lessly, independent of the access network and the access device. To achieve this, it is

necessary to personalize and adapt content to end-user devices with varying capabili-

ties. Thus we consider the idea of composition.

Service Composition refers to the construction of complex services from primitive

ones, thus providing rapid and ﬂexible creation of new services. Fixed broker-based

or ﬁxed central-entity based service composition techniques cannot be applied as a

solution to compose services on the ﬂy as the clients can be mobile. The client may also

use a service which may be mobile and connected through wireless network. This is due

to the fact that such approaches presuppose the existence of a persistent central entity or

coordinator in the clients neighbourhood, which is reliable and constantly available on

request. Thus service composition can be deﬁned as a dynamic integration of multiple

services available in an mobile grid environment in response to a request from a client.

The proposed research intends to study the key issues involved in building a middleware

for service composition in a dynamic distributed mobile computing environment, and

comes out with a layered architecture for the infrastructure of such a model.

The rest of the paper is organized as follows: section 2 gives a overview of the

related work. Section 3 gives the implication of integrating mobile devices into the grid.

Section 4 gives an overview of the proposed approach, that includes the motivation,

design issues and principles. Section 5 describes the layered architecture of the service

composition middleware architecture for mobile grid and in section 6 we conclude.

2 Related Work

In mobile environment, networks are unstable, mobile nodes can join and leave fre-

quently. The quality of connection is unpredictable, even network itself can be ad-hoc.

Moreover, mobile nodes have limited local resources and battery life. Although grid

computing hasn’t addressed these problems extensively, research in mobile computing

provides solutions attacking these mobility issues. There are few infrastructures like

Legion Grid computing infrastructure [5] that has come up to support resource het-

erogeneity ranging from supercomputers to small, handheld devices. There are many

issues regarding mobile and wireless computing that are only solved in an application-

speciﬁc manner and not by a general-purpose computing infrastructure. Nomadic nature

of mobile devices which includes moving within and between environments poses some

unique requirements. The foremost among them is the ability to locate available ser-

vices and resources in or near a new location. In the vision of interconnecting diverse

resources under a common framework, many research challenges arise, such as uni-

form ubiquitous connectivity, heterogeneity of sources, effective and precise resource

discovery [6].Thus, we have investigated the relevant technologies to support building

middleware for grid system that incorporates wireless and mobile devices.

To the best of our knowledge very few works such as [7] [8] [9] are done in mo-

bile grids. But none of these papers address the issues due to mobility, which leads

to availability problem. They had also speciﬁcally looked only at the computing na-

ture of the mobile grid. [7] discusses about the challenges that arises due to integrating

mobile devices into a grid. [8] provides an proxy-based approach for sharing of com-

puting power among the participating mobile devices. The model considers only the

mobile adhoc networks. [9] comes out with an architecture using mobile agent (MA)

technology, where the mobile agents are used as a communication primitive. The paper

discusses with the focus on mobile devices using the grid and not as a member of the

grid.

3 Implication of Mobile Devices on Grid

The characteristics of the mobile devices such as the resource poor nature and low band-

width connectivity (wireless) must be addressed if these devices are to be integrated as

computational resources in a grid. The system must be capable to operate on constrained

hardware. The sporadic and dynamic network environment must be handled gracefully.

The grid should be ﬂexible and reﬂective, to allow users to make trade offs and select

the combination of services that is best suited for their purpose. This has led to the

requirement of dynamic query and adjust, at runtime. The system should also be capa-

ble to support computation and service migration, replication, run-time monitoring, and

application recovery. The disconnection of a given node in the grid should not disrupt

service availability. In addition, the system should be able to ofﬂoad computations if

the device is likely to become unavailable soon.

4 Proposed Approach

Our aim is to integrate heterogeneous mobile wireless devices into the grid to form

a new paradigm known as Mobile Grid. In addition we also aim to change the logic

of adopting grid for single specialized high-demanding applications, and make it more

general to allow many simple users to transparently access the distributed computing

and storage resources, anyhow, anywhere and anytime. Thus increasing the user base

of the grid. The mobile grid is visualized as cluster of clusters.

4.1 Motivation

There are many potential applications for our proposed mobile grid. Of particular inter-

est is the earth science application. In earth science the geologist generally do ﬁeldwork

and mapping of some kind to study structure and dynamics of the earth. The work that

is done so far by these ﬁeld workers is manual, where they collect the data and return

back to their ofﬁce and do the collaboration at a central ofﬁce. With the help of mobile

grid, if the geologists are provided with some kind of mobile device, then collaboration

with the globally distributed geologist becomes feasible. Thus the mobile grid helps in

providing a integrated ubiquitous tool and environment to enhance collaboration among

distantly located knowledge workers such as scientists and engineers. By collaborating

they can work on solving problems assisted by the advanced collaboration and compu-

tation. This also helps in providing real time data gathering for collaborative ﬁeld geol-

ogy. This mechanism also helps to go out in the ﬁeld as a group, collect data and share

the data instantaneously with each other and with data fusion collaboratives hundreds

of miles away. Can also have on demand access to large database, data summarization,

and visualization resources at these centers to request site speciﬁc data. Provides group

intelligence with the ability to monitor the data and the location of the data gatherers

instantaneously. Gathered data can be fused immediately so that anomalies or missing

information can be investigated while the data gatherers are still within the physical

vicinity.

To achieve the above mentioned idea we attempt to identify key design issues, prin-

ciples and layers of abstraction. Architecturally, the central idea of our approach is

to virtualize the individual system resources of the mobile grid, such as data, com-

putational cycles, wired and wireless bandwidth, or storage, as services that can be

described, discovered and dynamically conﬁgured at runtime to execute an application.

The system adds the available resources to the networked pool from which the resources

needed to complete a given task can be aggregated dynamically. We propose to build a

functional layer around the Anonymous Remote Mobile Cluster Computing kernel [10]

to perform service composition for application execution.

An aggregated collection of resources operates as an assembly only for the period

required to complete the collective task, after which the resources return to the network

pool. We assume that nodes willing to share a certain subset of their resources use

mechanisms to announce their availability, possibly stating the term of usage, to the

rest of the mobile grid in which they are willing to collaborate. Individual nodes may

be motivated to share resources for several reasons, such as to provide or gain access to

unique data or to trade temporarily underutilized resources for proﬁt or for the beneﬁt

of being able to draw upon the collective resources to handle their own peak loads.

4.2 Design Issues

We have identiﬁed the following key design issues for building the service composition

middleware for mobile grid

– Handling hardware and software resources as a pool of services.

– Service Discovery - Optimal service discovery architecture must be able to ﬁnd

out all services conforming to a particular functionality, irrespective of its way of

invocation.

– Service Coordination and Management - Must have some entity coordinating the

different services involved in the composition.

– Verifying the performance of the components in composition.

– Uniform Information Exchange mechanisms to realize a heterogeneous service

composition platform.

– Adaptability of the composed service to network and user dynamics.

– Compositions across independent service provider.

– Dealing with heterogeneity in protocols and data formats.

– Handling dynamic gluing of services at runtime, with capabilities to handle load

balancing.

– Must be able to control and manage an aggregated set of services for completing a

task.

– Fault Tolerance and Scalability

4.3 Design Principles

The two key design principles that have been identiﬁed for the design of the middle-

ware architecture are: embedding intelligence in the network and create self-conﬁgu-

ring, self-organizing network structures. It is seen from previous research experience

that distributing intelligence tends to improve scalability. The self-organizing and self-

conﬁguring aspects contributes to both scalability and resiliency by creating ad-hoc

networks of currently available nodes and resources. Improved scalability and perfor-

mance result largely from the preference for use of local resources. Using local re-

sources tends to shorten communication distances between the data source, its point of

processing, and optional presentation to the user. This helps in reduced latency and a

bias toward consuming edge bandwidth rather than the backbone bandwidth needed to

communicate with remote centralized servers. Distributing intelligence into the network

also tends to distribute the load across many processing points, as opposed to creating

congestion at a few heavily used points.

5 Proposed Architecture

5.1 Layered Architecture

Figure 1 shows the key network services and abstraction layers of the proposed service

composition middleware for the mobile grid. The central idea of the architecture is

taken from [11], which debates on using the internet as distributed computing platform.

The service composition middleware for mobile grid is proposed keeping the key issues

identiﬁed and the design goals in mind.

The lower most layer represents the communication infrastructure, namely both

wired and wireless network. This layer represents the underlying communication in-

frastructure being used to communicate between different services in our system. It

allows the use of different protocols for transferring messages. Thus this layer can en-

capsulate any communication mechanism and allows seamless integration of different

network protocols in our system.

The Resource Virtualization layer represents the mechanisms through which ser-

vices express themselves and concentrates primarily on the use of resource sharing in

Composition / Orchestration

Local

Resources

Local

Resources

Discovery

Dynamic Configuration and Binding

(runtime)

Applications

Resource Virtualization and Management

Communication (Wired and Wireless)

(publishing, description)

Fig.1. Layered Reference Architecture for Service Composition in Mobile Grid

the grid. Resource Virtualization is thought of as an abstraction of some deﬁned func-

tionality and its public exposure as a service through an interface that applications and

resource managers can remotely invoke. We consider the service to be a virtualized

software functional component. Services can be advertised and discovered using di-

rectories and inspection. Once discovered, an invoking entity can bind to the selected

service and start communicating with its externally visible functions, through platform

independent protocols. Each such virtualized component can be abstracted, discovered

and bound to. In the same way this can be extended to virtualize hardware resources.

Thus a planetary-sized pool of composable hardware and software resources can be

envisioned.

Discovery is the fundamental component, as the system must ﬁnd a service before

it could use it. Traditional systems often implicitly discover or ﬁx it at conﬁguration or

compile time. In case of mobile grids which has to accommodate both mobile and static

devices with dynamic aggregated environments, it should be able to support a ﬂexible

service advertisement and discovery mechanism. Applications can discover services

based on their functionality, characteristics, cost or location. Dynamic discovery en-

ables devices to adaptively cooperate and extend functionality.

Dynamic conﬁguration depends upon the capability to bind components at runtime,

in contrast to the binding at design time. Runtime binding can be implemented with

the assistance of service discovery mechanisms. This helps in decoupling application

design from the detailed awareness of the underlying system conﬁguration and connec-

tivity. Dynamic conﬁguration facilitates application portability across a wide range of

platforms and networks conﬁgurations. Runtime binding also enables load balancing

and improved reliability.

Resource Orchestration deals with control and management of the aggregated set of

resources for completing a task. It also includes the communication and synchronization

necessary for coordination and collation of partial results. On completion of a task, the

system releases the resources back to the pool for allocation to other users.

5.2 Service Coordination and Management

The proposed mobile grid is organized as a cluster of clusters as illustrated in ﬁgure

2. Each cluster maintains a cluster head, which maintains the required repositories as-

sociated with the cluster. The cluster head using trading services maintain the services

available within the cluster. The cluster head communicates with each other in a peer-to-

peer fashion in contrast to the usual hierarchical organization. The mobile devices using

the exporter daemon sends the available services to the MSS, which in turn passes it to

the cluster head.

CLUSTER 1

MSS

CELL

CLUSTER3

MSS

Mobile Support station

MH − Mobile Host

Cluster Head

Static Host

CLUSTER 2

MSS

CELL

Peer−to−Peer Overlay

Fig.2. Mobile Grid Architecture Clustered as p2p overlay

When client request the cluster head for a service, the cluster head checks for the

availability of the service within the cluster. When the cluster head ﬁnds that services is

not available within the cluster, the cluster head starts to search other neighbouring clus-

ter through the peer-to-peer overlay. In order to optimize on the searching the cluster

head stores the historical data related to the earlier requests. Thus the cluster head can

take an intelligent decision based on the past request. Each cluster head maintains such

information about each of its neighbour cluster heads. When a request for a composite

service is initiated from a mobile device, the middleware should provide the service

which is available in the near vicinity of the mobile device. The success of the compo-

sition depends on the number of hops that are taken to reach the desired service from

the cluster head.

6 Conclusions

Service Composition architectures will become very important with the increasing grow-

th of e-services. The proliferation of mobile devices during these years have started see-

ing the availability of services on different mobile devices. However the conventional

approach is that mobile devices will be merely web browsers without signiﬁcant com-

putational capabilities unto themselves. This paper is proposed with an envision that

mobile devices (embedded devices) can be capable to deliver much greater capabili-

ties for grid computing. This has seen to the integration of mobile devices into the grid

to form a new paradigm namely the mobile grid. Thus this paper proposes a new ser-

vice composition middleware architecture for mobile grid. The paper also provides the

design issues and principles that have been considered to build the layered architecture.

We are currently working on implementing the proposed model and experimentally

validate the model. We are also looking at building a new model that could to some

extent provide solution for the availability of the mobile device, which is due to the

mobility.

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