An analysis on the delay-aware data collection network structure using pareto optimality

Clustering techniques are effective techniques in reducing energy consumption in wireless sensor networks (WSNs). A data collection process (DCP) is an operation for a base station (BS) to collect a complete set of data from a WSN. Clustering techniques may, however, introduce bottlenecks to a DCP and cause extra delays. For time-sensitive applications, a delay-aware network structure is necessary. A delay-aware network structure should not only minimize the duration of a single DCP, but also shorten the duration of consecutive DCPs. Furthermore, for better sensing quality, a delay-aware network structure should try to accommodate as many wireless sensor nodes as possible. This paper investigates the trade-offs among the above objective functions in a delay-aware data collection network structure using the concepts of Pareto optimality. The analyses provide an insight into selecting the most suitable network parameters.