Minimizing Delay and Transmission Times with Long Lifetime in Code Dissemination Scheme for High Loss Ratio and Low Duty Cycle Wireless Sensor Networks

Xie

et al. 2019

J Wireless Com Network

Self Cite

Sensor nodes equipped with various sensory devices can sense a wide range of information regarding human or things, thereby providing a foundation for Internet of Thing (IoT). Fast and energy-efficient data collection to the control center (CC) is of significance yet very challenging. To deal with this challenge, a low redundancy data collection (LRDC) scheme is proposed to reduce delay as well as energy consumption for monitoring network by using matrix completion technique. Due to the correlation of the location-dependent sensing data, some data without being collected can still be recovered by the matrix completion technology, thereby reducing the data amount for data collection and transmission, reducing the network energy consumption, and accelerating the process of data acquisition. Based on matrix completion technique, LRDC scheme can select only part of the nodes to sense data and transmit less data to CC. By doing so, the data collected by the network can be greatly reduced, which can effectively improve the network lifetime. In addition, LRDC scheme also proposes a method for quickly compensate sample data in cases of packet loss, whereby part of redundant data is sent in advance to the area closer to CC. If the data required for matrix completion is lost, these redundant data can be quickly obtained by CC, so the LRDC scheme has low delay characteristics. Simulation results demonstrate that LRDC scheme can achieve better performance than the traditional strategy, and it can reduce the maximum energy consumption of the network by 27.6-57.9% and reduce the delay by 0.7-17.9%.

Section: Background and Related Workmentioning

confidence: 99%

A low redundancy data collection scheme to maximize lifetime using matrix completion technique

Tan

Xie

et al. 2019

J Wireless Com Network

Self Cite

“…Delay issue for data transmission. 44,[56][57][58] Obviously, the routing scheme needs to make the delay of the data reaching the sink as small as possible.…”

Section: Related Workmentioning

confidence: 99%

“…There is a much higher loss ratio in wireless communication than in wired communication. 37,40,44 In addition, there may be attacks in WSNs, 51,52 where malicious nodes interfere with data transmission and damage the reliability of data transmission. Therefore, security is also a problem worthy of attention.…”

Section: Related Workmentioning

confidence: 99%

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Adaptive duty cycle control–based opportunistic routing scheme to reduce delay in cyber physical systems

Xiang

International Journal of Distributed Sensor Networks

et al. 2019

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Wireless sensor networks are the foundation of cyber physical systems. In loss and delay sensitive wireless sensor networks, there is much room for improving the performance of opportunistic routing scheme. In this article, an adaptive duty cycle control-based opportunistic routing scheme was put forward to improve the performance of the opportunistic routing scheme. Our main work is as follows: (a) the proposed duty cycle control-based opportunistic routing scheme implements the opportunistic routing in the duty cycle-based wireless sensor networks. Compared with the opportunistic routing scheme in the non-duty cycle mode, the duty cycle control-based opportunistic routing scheme can effectively reduce the energy consumption by 55.64%, although the performance in the delay is degraded. (b) Next, adaptive duty cycle control-based opportunistic routing scheme is proposed to reduce the delay of nodes in duty cycle control-based opportunistic routing. In adaptive duty cycle control-based opportunistic routing scheme, the node's duty cycle is increased in the area where the energy has remaining, so that the network delay can be reduced without reducing the network lifetime. Compared with duty cycle control-based opportunistic routing scheme, the maximum end-toend delay of the node in the network can be reduced by 69.83%.

“…Sensor nodes are responsible for monitoring events within the perceived range, sensing surrounding data. Then send them to the sink node via multi-hop routing [41][42][43][44][45]. To realize the enormous potential of wireless sensor networks (WSNs), it is important for sink to integrate the sensed data by many sensor nodes, and distill the high value information for each application needs [46][47][48].…”

Section: Introductionmentioning

confidence: 99%

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

Xiang

Wang

et al. 2019

J Wireless Com Network

Self Cite

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%.