Modeling and Performance Analysis for Pipelined-Forwarding MAC Protocols for Linear Wireless Sensor Networks

Singh, Ripudaman; Kumar, Brijesh; Bose, Sanjay K.

doi:10.1109/jsen.2019.2910209

Cited by 14 publications

(12 citation statements)

References 31 publications

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“…The signal nodes are arranged in at least a plurality of orders according to the total amount of data, thereby reducing the waiting time required in the optimization process. 28,29 First, the node with the largest total number of signals is sent, and the sort order N v of each node in the optimization process is obtained, v = 1 , 2 ,… , n send , as shown in Figure 2.…”

Section: Methodsmentioning

confidence: 99%

High-density data transmission and scheduling method in wireless sensor networks based on Wi-Fi

Zhang

Qiu

et al. 2020

International Journal of Distributed Sensor Networks

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In wireless sensor network, the storage amount of information is high, and the transmission and scheduling of control information is reasonable. The node communication model, network structure model, and energy consumption model are constructed. On this basis, the high-density data in wireless sensor network are scheduled to optimize the time for nodes to perform tasks. The nodes in the network are fully scheduled to control the generation time of packets in the network and the generation time of packets in the network. Experimental results show that in different iterations, the proposed method has lower node delay and node energy consumption, with values less than 0.2 and 2, respectively, and the maximum data fusion quality can reach 98, with high fusion benefits, so as to improve the transmission and scheduling efficiency and quality of high-density data in wireless sensor network.

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Section: Methodsmentioning

confidence: 99%

High-density data transmission and scheduling method in wireless sensor networks based on Wi-Fi

Zhang

Qiu

et al. 2020

International Journal of Distributed Sensor Networks

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“…means that s j can detect only one type of event. Moreover, each type of event has at least one sink as shown in (3).…”

Section: A Network Settings/environmentmentioning

confidence: 99%

“…different sensors to detect different events. But sometimes, several WSNs co-exist in a geographical area [2], [3]. For example, a smart-building WSN [4] prepares sensors to detect human movement or body temperature for turning on/off corridor lights.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks

et al. 2020

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Generally, routing techniques are essential for Wireless Sensor Networks (WSNs) to deliver data packets to their destinations (also known as sinks). For a practical application, sensors are deployed to monitor environmental changes and events. Most WSNs detect specific events in their specific environments. But, different WSNs may monitor different events with different sensors in the same area. For example, a smart-home WSN deploys thermal sensors/meters to measure indoor and outdoor temperatures, bodytemperature sensors to detect thief intrusion, etc. Also, in the underlying house, there is a health WSN which utilizes physiological sensors to monitor patients' health condition. In other words, several WSNs of different purposes co-exist in the same geographical area. Currently, each WSN's data delivery is independent from others'. Basically, if all sensors in such a multi-WSNs environment can share their routing paths/nodes and relay event packets for other WSNs, the delivery efficiency can be enhanced since many more sensors can be found there for packet relay. Consequently, the transmission energy can be reduced since energy consumed for wireless transmission is proportional to d 2 where d is the transmission distance between sender and receiver. Therefore, in this study, we propose an energy saving routing mechanism, named Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks (EERH for short), in which several WSNs deployed in the same geographical environment form a heterogeneous sensor network and sensors relay packets for its own WSN and also for other WSNs. Routing paths are dynamically established according to the transmission directions of event packets and the residual energy of the underlying sensors and their neighbors. In addition, the packets routed to the same direction by the same sensors are aggregated to save delivering energy. Moreover, the network parameters of the EERH, like propagation delay of an event packet and the transmission distance of a sensor, are adjustable so as to satisfy the practical environment needs. Simulation results show that the EERH efficiently extends the lifetime of a heterogeneous WSN. INDEX TERMS Wireless sensor networks, heterogeneous wireless sensor networks, energy efficient, cooperative routing.

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“…In this section, the performance of D3 is evaluated by extensive OPNET simulations. The performance of D3 is compared with a basic duty-cycling and pipelined-forwarding protocol as the benchmark [ 37 , 38 ]. The comparison is based on two chain networks, namely, single-chain ( Figure 6 a) and double-chain ( Figure 6 b).…”

Section: Performance Evaluationmentioning

confidence: 99%

A Data-Gathering, Dynamic Duty-Cycling MAC Protocol for Large-Scale Wireless Sensor Networks

Tong

Peng

2020

Sensors

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This paper presents a Data-gathering, Dynamic Duty-cycling (D3) protocol for wireless sensor networks. With a proposed duty-cycling MAC of high energy efficiency in D3, a routing scheme is naturally embedded to reduce protocol overhead. A packet can be forwarded in a pipelined fashion by staggering the sleep-wakeup schedules between two communicating nodes, which can significantly reduce end-to-end delay to meet real-time transmission requirements. To construct and maintain schedules, a grade and schedule establishment mechanism with a lightweight schedule error correction scheme is designed. In addition, based on the intrinsic characteristics of the network, an adaptive schedule maintenance scheme is proposed to dynamically adjust the node duty cycle to the network traffic load. The results based on the extensive OPNET simulations show that D3 can largely improve packet delivery ratio, energy efficiency and throughput, and reduce packet delivery latency.

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Modeling and Performance Analysis for Pipelined-Forwarding MAC Protocols for Linear Wireless Sensor Networks

Cited by 14 publications

References 31 publications

High-density data transmission and scheduling method in wireless sensor networks based on Wi-Fi

High-density data transmission and scheduling method in wireless sensor networks based on Wi-Fi

Energy-Efficient Cooperative Routing Scheme for Heterogeneous Wireless Sensor Networks

A Data-Gathering, Dynamic Duty-Cycling MAC Protocol for Large-Scale Wireless Sensor Networks

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