Issue No. 04 - April (2013 vol. 24)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2012.163
Wenbo Zhao , Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
Xueyan Tang , Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
The network traffic pattern of continuous sensor data collection often changes constantly over time due to the exploitation of temporal and spatial data correlations as well as the nature of condition-based monitoring applications. In contrast to most existing TDMA schedules designed for a static network traffic pattern, this paper proposes a novel TDMA schedule that is capable of efficiently collecting sensor data for any network traffic pattern and is thus well suited to continuous data collection with dynamic traffic patterns. In the proposed schedule, the energy consumed by sensor nodes for any traffic pattern is very close to the minimum required by their workloads given in the traffic pattern. The schedule also allows the base station to conclude data collection as early as possible according to the traffic load, thereby reducing the latency of data collection. We present a distributed algorithm for constructing the proposed schedule. We develop a mathematical model to analyze the performance of the proposed schedule. We also conduct simulation experiments to evaluate the performance of different schedules using real-world data traces. Both the analytical and simulation results show that, compared with existing schedules that are targeted on a fixed traffic pattern, our proposed schedule significantly improves the energy efficiency and time efficiency of sensor data collection with dynamic traffic patterns.
time division multiple access, scheduling, telecommunication traffic, TDMA schedules, sensor data collection scheduling, dynamic traffic patterns, network traffic pattern, continuous sensor data collection, temporal data correlations, spatial data correlations, Schedules, Base stations, Time division multiple access, Dynamic scheduling, Monitoring, Distributed databases, Routing, wireless sensor networks, Data collection, TDMA, scheduling, energy efficiency, latency
Wenbo Zhao and Xueyan Tang, "Scheduling Sensor Data Collection with Dynamic Traffic Patterns," in IEEE Transactions on Parallel & Distributed Systems, vol. 24, no. , pp. 789-802, 2013.