In the first phase of this research, we will study and implement several existing schedule driven MAC protocols to analyze and evaluate their performances under conditions where signal disintegration is present. Specifically, we will evaluate all performance metrics of the existing MAC protocols to identify the components that contribute to performance degradation.
We will then devise a new schedule driven MAC protocol using a generic routing scheme that improves upon the weaker areas of the existing MAC protocols in the presence of signal disintegration. Ideally, the proposed protocol will be able to predict the periods when the medium is strident and avoid transmitting data during these periods. By doing so, sensor nodes are able to turn their radio transceivers off during these periods and lower their duty cycle to conserve energy and avoid data transmission. The main challenge in this part of the project is to devise a simple prediction model that does not require extensive computation and is not excessively memory dependent.
In the second phase of this research, we will integrate the existing reactive/hybrid cluster routing protocols into our implementation of the first phase. We will observe and analyze the performances of the existing routing protocols in presence of signal disintegration and extract the problem areas that degrade the overall protocol performance.
Having identified the problem areas, we will design a new routing protocol specific to harsh working conditions to work hand-in-hand with our MAC protocol from phase one. To overcome the problem of temporary network partition due to schedule driven MAC scheme used, we will explore the possibility of adopting an opportunistic routing scheme [26] that uses neighbouring sensor nodes which are available for routing at any particular time when some data needs to be transmitted.
Given the completion of phase one and two of this research, the third phase involves designing a network management protocol as an attachment to the previous two phases that is specific to monitoring and maintaining network activities in manufacturing environments. As network monitoring activities require extensive log data reporting, we will explore the possibilities of employing an efficient technique, other than those mentioned previously, to maximize the quality of log data that is to be reported, at a minimal cost.
In the last phase of this research, we will implement our framework in an actual experiment involving the deployment of physical sensor nodes in a manufacturing plant. In this field-test, the behaviour of the system will be observed and analyzed, with any anomalies reported and corrected.