Use this URL to cite or link to this record in EThOS:
Title: An integrated modelling framework for the design and construction of distributed messaging systems
Author: Makoond, Bippin Lall
ISNI:       0000 0004 2719 7333
Awarding Body: Kingston University
Current Institution: Kingston University
Date of Award: 2008
Availability of Full Text:
Access from EThOS:
Access from Institution:
Having evolved to gain the capabilities of a computer and the inherent characteristic of mobility, mobile phones have transcended into the realm of the Internet, forcing mobile telecommunication to experience the phenomenon of IP Convergence. Within the wide spectrum of mobile services, the messaging business has shown the most promising candidate to exploiting the Internet due to its adaptability and growing popularity. However, mobile operators have to change the way they traditionally handle the message logistics, transforming their technologies while adhering to aspects of quality of service. To keep up with the growth in messaging, in the UK alone reaching to 52 billion in 2007, and with the increased complexity of the messages, there is an urgent need to move away from traditional monolithic architectures and to adopt distributed and autonomous systems. The aim of this thesis is to propose and validate the implementation of a new distributed messaging infrastructure that will sustain the dynamics of the mobile market by providing innovative technological resolutions to the common problem of quality modelling, communication, evolution and resource management, within mobile Telecoms. To design such systems, requires techniques, not only found in classical software engineering, but also in the scientific methods, statistics and economics, thus the emergence of an apparent problem of combining these tools in a logical and meaningful manner. To address this problem, we propose a new blended modelling approach which is at the heart of the research process model. We formulate a Class of problems that categorises problem attributes into an information system and assess each requirement against a quality model. To ensure that quality is imprinted in the design of the distributed messaging system, we formulate dynamic models and simulation methods to measure the QoS capabilities of the system, particular in terms of communication and distributed resource management. The outcomes of extensive simulation enabled the design of predictive models to build a system for capacity. A major contribution of this work relates to the problem of integrating the aspect of evolution within the communication model. We propose a new multi-criteria decision making mechanism called the BipRyt algorithm, which essentially preserve the quality model of the system as it tends to grow in size and evolve in complexity. The decision making I process is based on the availability of computational resources, associated rules of usage and defined rules for a group of users or the system as a whole. The algorithm allows for local and global optimisation of resources during the system life cycle while managing conflicts among the rules, such as racing condition and resource starvation. Another important contribution relates to the process of organizing and managing nodes over distributed shared memory. We design the communication model in the shape of a grid architecture, which empowers the concept of single point management of the system (without being a single point of failure), using the same discipline of managing an information system. The distributed shared memory is implemented over the concept of RDMA, where the system runs at very high performance and low latency, while preserving requirements such as high availability and horizontal scalability. A working prototype of the grid architecture is presented, which compares different network technologies against a set of quality metrics for validation purposes.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computer science and informatics