27-11-2012, 03:23 PM
SCHEDULABILITY ANALYSIS FOR HARD NETWORK LIFETIME WIRELESS SENSOR NETWORKS WITH HIGH ENERGY FIRST CLUSTERING
ABSTRACT
Network lifetime predictability is an essential system requirement for the type of wireless sensor network (WSN) used in safety-critical and highly-reliable applications.
All sensor nodes in these time-critical WSNs should meet the lifetime constraint at any time instance, else it may cause severe consequences that involve economic losses, or even fatalities. In the literature, clustering sensors into groups is a popular strategy to maximize the network lifetime, but none of the clustering algorithms address the predictability issue for time-critical WSNs.
In this paper, the High Energy First (HEF) clustering algorithm is chosen as a design reference model, which is proved in this paper to be an optimal clustering policy under certain ideal conditions. To address network lifetime predictability in practice, the network lifetime bounds and feasibility test for the HEF are developed via the worst case energy consumption analysis.
The network simulator 2 (NS2) is used to verify the proposed network lifetime predictability model, and the results show that the derived bounds of the predictability provide accurate estimations of the system lifetime.
ABSTRACT
Network lifetime predictability is an essential system requirement for the type of wireless sensor network (WSN) used in safety-critical and highly-reliable applications.
All sensor nodes in these time-critical WSNs should meet the lifetime constraint at any time instance, else it may cause severe consequences that involve economic losses, or even fatalities. In the literature, clustering sensors into groups is a popular strategy to maximize the network lifetime, but none of the clustering algorithms address the predictability issue for time-critical WSNs.
In this paper, the High Energy First (HEF) clustering algorithm is chosen as a design reference model, which is proved in this paper to be an optimal clustering policy under certain ideal conditions. To address network lifetime predictability in practice, the network lifetime bounds and feasibility test for the HEF are developed via the worst case energy consumption analysis.
The network simulator 2 (NS2) is used to verify the proposed network lifetime predictability model, and the results show that the derived bounds of the predictability provide accurate estimations of the system lifetime.