Towards a socionomic framework for collaborative data routing in wireless sensor network
- Publication Type:
- Thesis
- Issue Date:
- 2011
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
 | 01Front.pdf | contents and abstract | 8.77 MB | ||
 | 02Whole.pdf | thesis | 159.17 MB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
NO FULL TEXT AVAILABLE. This thesis contains 3rd party copyright material. ----- A Darwinian perspective on the existence of a relationship between change and evolution in nature has
long been argued. Over the last 35,000 years human culture has witnessed an enormous change that is
in sharp contrast to our biological evolution. Our cultural change has been governed by the attributes of
human behaviour -to react, learn and adapt, leading to the formulation of complex social and economic
phenomenon . Such traits have allowed human beings to live in groups, experience, contribute, and
share knowledge, leading to the formation and association to our respective societies. However, the
autonomous traits in humans also create differences in opinion which in turn moulds our perception,
experience and action. As a result of the individual differences, no two societies can be exactly alike and
a means of assessing the underlying dynamics is through understanding the economic constraints. After
all, a society is driven by its resource constraints that is best gauged by realizing the cost of mining and
using those resources. Although, such a socionomic model cannot necessarily be formalized, yet, in
software intensive systems it establishes a new paradigm for resource management.
This thesis establishes the potential for the application of such a socionomic model in optimizing
resource usage and collaboration among sensor nodes in a typical Wireless Sensor Network. The synergy
of new technological innovations in the realm of Wireless Sensor Networks has paved the way for their
application in many different domains. In dyna mic but sometimes hostile environments, such as,
battlefields, roads, tunnels, and hospitals, sensor nodes need to be autonomous to be able to maximize
their chances of survival without the need for any external aid . However, spatial differences and
environmental factors may sometimes make it impossible for sensor nodes to successfully collaborate
and exchange information. The application of a socionomic model in such scenarios allows sensor nodes
to be programmed with the intelligence to attempt different avenues of communication, cluster
formation and data routing. The goal of this research is to optimize resources usage and thereby
maximize the lifetime of the network.
Finally, the socionomic framework has been validated against more traditional techniques of clustering
and data routing, through several experiments and case studies. Some of the novel concepts of selflearning,
knowledge acquisition and collaboration methodologies have also been detailed and evaluated
against relevant practices and guidelines.
Please use this identifier to cite or link to this item: