Delay and energy-efficient data collection scheme-based matrix filling theory for dynamic traffic IoT

EURASIP Journal on Wireless Communications and Networking

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[1] 0000 0000 8895 903X, grid.411404.4, Department of Computer Science and Technology, Huaqiao University, 361021, Xiamen, China;0000 0001 0379 7164, grid.216417.7, School of Computer Science, Central South University, 410083, Changsha, China;0000 0001 0561 4552, grid.255501.6, Department of Electrical, Computer, Software, and Systems Engineering, Embry-Riddle Aeronautical University, 32114, Daytona Beach, FL, USA;0000 0001 0574 8737, grid.413273.0, Faculty of Informatics & Electronics, Zhejiang SCI-Tech University, 310018, Hangzhou, China;0000 0001 2229 7034, grid.413072.3, School of Computer Science and Information Engineering, Zhejiang Gongshang University, 310018, Hangzhou, China;0000 0004 1760 6172, grid.411429.b, School of Computer Science and Engineering, Hunan University of Science and Technology, 411201, Xiangtan, China;0000 0004 1765 5169, grid.488482.a, School of Informatics, Hunan University of Chinese Medicine, 410208, Changsha, China;

关键词: Multi-modal;    Clustered routing;    Matrix filling;    Low latency;    Energy efficient;   

DOI  :  10.1186/s13638-019-1490-5

来源: publisher

【 摘 要 】

Data collection is the basic functions of the Internet of Things (IoT), in which the sensed data are concentrations from sensor nodes to the sink, with a timely style, so the smart response can be done for emergency. The goal of multi-modal sensor data fusion is to obtain simple and accurate data to enhance system reliability and fault tolerance. Energy efficiency and small delay are the most important indicators which govern the performance of IoT. Convergecast is a low-latency data collection strategy based on effective time division multiple access (TDMA), in which each sensor node generates a packet, and m packets can aggregate to a packet. However, in most practical networks, sensor nodes do not necessarily generate packets during each data collection cycle, but instead generate packets from time to time. In the previous convergecast strategy, each node was fixedly allocated a slot, which increased the delay and wasted energy. A delay and energy-efficient data collection (DEEDC) scheme-based matrix filling theory is proposed to collect data in a randomly generated WSNs with minimum delay and energy consumption. The DEEDC scheme uses a clustering approach. For each cluster, the number of slots required for transmission is calculated by matrix filling theory, not the number of nodes that actually generate data. This ensures that data can be collected in a network with randomly generated data (number of slots ≤ number of nodes), thereby avoiding the allocation of slots for each node and the acquisition of redundant data to lead to the wastage of time and energy. Based on the above, a mixed slot scheduling strategy is proposed to construct energy and delay-efficient, collision-free schedule scheme. After extensive theoretical analysis, by using the DEEDC scheme, the delay is reduced by about 50~80%, and the energy consumed is reduced by about 40~57%.

【 授权许可】

CC BY