Wireless sensor networks promise a new paradigm for gathering data via collaboration among sensors spreading over a large geometrical region. Many applications impose delay requirements for data gathering and ask for time-efficient schedules for aggregating sensed data and sending to the data sink. In this paper, the authors study the minimum data aggregation time problem under collision-free transmission model. In each time round, data sent by a sensor reaches all sensors within its transmission range, but a sensor can receive data only when it is the only data that reaches the sensor. The goal is to find the method that schedules data transmission and aggregation at sensors so that the time for all requested data to be sent to the data sink is minimal. The authors propose a new approximation algorithm for this NP-hard problem with guaranteed performance ratio $\frac{7\mathrm{\Delta }}{{\log }_2|\mathsf{S}|}+c$, which significantly reduces the current best ratio of $\mathrm{\Delta }-1$, where $\mathsf{S}$ is the set of sensors containing source data, $\mathrm{\Delta }$ is the maximal number of sensors within the transmission range of any sensor, and $c$ is a constant. The authors also conduct extensive simulation, the obtained results justify the improvement of proposed algorithm over the existing one.

Wireless sensor networks promise a new paradigm for gathering data via collaboration among sensors spreading over a large geometrical region. Many applications impose delay requirements for data gathering and ask for time-efficient schedules for aggregating sensed data and sending to the data sink. In this paper, the authors study the minimum data aggregation time problem under collision-free transmission model. In each time round, data sent by a sensor reaches all sensors within its transmission range, but a sensor can receive data only when it is the only data that reaches the sensor. The goal is to find the method that schedules data transmission and aggregation at sensors so that the time for all requested data to be sent to the data sink is minimal. The authors propose a new approximation algorithm for this NP-hard problem with guaranteed performance ratio $\frac{7\mathrm{\Delta }}{{\log }_2|\mathsf{S}|}+c$, which significantly reduces the current best ratio of $\mathrm{\Delta }-1$, where $\mathsf{S}$ is the set of sensors containing source data, $\mathrm{\Delta }$ is the maximal number of sensors within the transmission range of any sensor, and $c$ is a constant. The authors also conduct extensive simulation, the obtained results justify the improvement of proposed algorithm over the existing one.