TY - JOUR
T1 - Broadcasting info-pages to sensors
T2 - Efficiency versus energy conservation
AU - Alayev, Yosef
AU - Bar-Noy, Amotz
AU - Porta, Tom F.La
N1 - Funding Information:
Acknowledgments This research was sponsored by US Army Research laboratory and the UK Ministry of Defence and was accomplished under Agreement Number W911NF-06-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the US Army Research Laboratory, the US Government, the UK Ministry of Defence, or the UK Government. The US and UK Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.
PY - 2011/8
Y1 - 2011/8
N2 - In sensor networks applied to monitoring applications, individual sensors may perform preassigned or on-demand tasks, or missions. Data updates (info-pages) may be sent to sensors from a command center, via a timedivision broadcast channel. Sensors are normally put in sleep mode when not actively listening, in order to conserve energy in their batteries. Hence, a schedule is required that specifies when sensors should listen for updates and when they should sleep. The performance of such a schedule is evaluated based on data-related costs and sensor-related costs. Data-related costs reflect the obsoleteness of current sensor data, or the delay while sensors wait for updated instructions. Sensor-related costs reflect the energy that sensors consume while accessing the broadcast channel and while switching between the active and sleeping modes (rebooting). Our goal is a schedule with the minimum total cost. Previous related work has explored data-related costs, but listening cost has been addressed only under the assumption that the rebooting operation is free. This paper formulates a new cost model, which recognizes the cost of sensor rebooting. We derive an optimal schedule for the single-sensor setting. We proceed to consider schedules of multiple sensors; we formulate a mathematical program to find an optimal fractional schedule for this setting and provide a solution to the lower bound. Several heuristics for scheduling multiple sensors are introduced and analyzed, and various tradeoffs among the cost factors are demonstrated.
AB - In sensor networks applied to monitoring applications, individual sensors may perform preassigned or on-demand tasks, or missions. Data updates (info-pages) may be sent to sensors from a command center, via a timedivision broadcast channel. Sensors are normally put in sleep mode when not actively listening, in order to conserve energy in their batteries. Hence, a schedule is required that specifies when sensors should listen for updates and when they should sleep. The performance of such a schedule is evaluated based on data-related costs and sensor-related costs. Data-related costs reflect the obsoleteness of current sensor data, or the delay while sensors wait for updated instructions. Sensor-related costs reflect the energy that sensors consume while accessing the broadcast channel and while switching between the active and sleeping modes (rebooting). Our goal is a schedule with the minimum total cost. Previous related work has explored data-related costs, but listening cost has been addressed only under the assumption that the rebooting operation is free. This paper formulates a new cost model, which recognizes the cost of sensor rebooting. We derive an optimal schedule for the single-sensor setting. We proceed to consider schedules of multiple sensors; we formulate a mathematical program to find an optimal fractional schedule for this setting and provide a solution to the lower bound. Several heuristics for scheduling multiple sensors are introduced and analyzed, and various tradeoffs among the cost factors are demonstrated.
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U2 - 10.1007/s11276-011-0362-7
DO - 10.1007/s11276-011-0362-7
M3 - Article
AN - SCOPUS:80053610860
SN - 1022-0038
VL - 17
SP - 1529
EP - 1542
JO - Wireless Networks
JF - Wireless Networks
IS - 6
ER -