Abstract
M.Sc.
Grid computing is a technology concerned with harvesting idle resources of geographically
distributed and interconnected computers. It solves problems regarded as too complex or
large to be solved by a single computer. Furthermore, economic grid computing is becoming
the most dominant form of grid computing. It enables some form of payment to occur
between resource producers and resource consumers in grid computing.
Mobile devices and mobile telecommunication services, a relatively new field of technology,
are rapidly increasing in popularity, size, strength and application. At the end of 2006, there
were approximately 2.7 billion global active mobile users utilising mobile devices and mobile
telecommunication services [Aho07]. At the end of 2007 this number had grown to 3.3
billion mobile users, more than half a billion additional mobile users in a period of one year
[McN07].
With such large numbers, grid computing can benefit from the clustering of mobile devices
forming a mobile grid computing model. However, there are many inherent disadvantages
concerning mobile devices, such as low processing capabilities, unpredictable network
connections and battery utilisation. Such hurdles must be addressed and solved if a mobile
computing infrastructure or architecture is ever to be considered.
This dissertation proposes the implementation of an economic mobile computing solution:
Mobile Agents for Global Mobile Device Grid Infrastructure Enterprises, or MAGGIE.
MAGGIE is concerned with harvesting idle mobile device resources by implementing the
supply and demand economic model, aiming to create a healthy competitive economic
market environment.
MAGGIE implements agent and mobile agent technology to compensate for the hurdles
introduced by mobile devices and mobile device software development platforms. It is
targeted at both Sun Microsystems’s J2ME MIDP 2.0 and Microsoft’s .NET Compact
Framework, enabling lower-end and higher-end mobile devices to contribute mobile
computing services and resources for utilisation by other mobile device users.
The primary goal of MAGGIE is to produce an architecture as generic as possible regarding
the development and implementation of MAGGIE services. MAGGIE allows third-party
application developers to seamlessly implement an array of MAGGIE services, without indepth
prior knowledge of the architecture and technical aspects of MAGGIE.
Finally, MAGGIE’s capabilities are demonstrated by implementing a distributed mobile
chess service known as the MAGGIE Chess Service. The MAGGIE Chess Service enables a
collection of distributed mobile devices in determining the best move originating from a
chessboard position.