Power minimization with end-to-end frame error constraints in wireless multi-hop sensor networks

Sheu, Tsang-Ling; Lu, Yi-Jen

doi:10.1145/1143549.1143758

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…Yuan et al [17] and Sheu and Lu [18] consider power management and QoS in wireless environments. Power management is done by considering connection quality of a wireless link and co‐channel interference caused by the excessive power by using same frequency, radiated by nodes.…”

Section: Related Workmentioning

confidence: 99%

Energy‐efficient predictive congestion control for wireless sensor networks

Rajan

Raja

Jeyasekar

et al. 2015

IET wirel. sens. syst.

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In recent years, wireless sensor networks have become an emerging technology in industries, environment monitoring and health care monitoring systems and so on. However, sensor node is a resource-constrained device in terms of memory, bandwidth and energy. These constraints impose congestion in the network, leading to large number of packet drops, low throughput and significant wastage of energy because of retransmission. This study presents a new approach for predicting congestion using probabilistic method, and controlling congestion using new rate control methods. The probabilistic approach used for the prediction of occurrence of congestion in a node is developed using data traffic and buffer occupancy. The rate control method uses rate allocation schemes, namely, rate reduction (RR), rate regulation (RRG) and split protocol (SP) to improve throughput and to reduce packet drops. In addition, an energy-efficient routing which finds the best forwarding node for data transmission is also proposed. Simulation results are compared with decentralised predictive congestion control (DPCC). The results show that the proposed method indeed reduces congestion and energy consumption, and improves the performance.

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Section: Related Workmentioning

confidence: 99%

Energy‐efficient predictive congestion control for wireless sensor networks

Rajan

Raja

Jeyasekar

et al. 2015

IET wirel. sens. syst.

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“…The routing protocols adopting in current wired networks can retrieve one suitable path according to the criterion of minimizing link cost and balancing traffic load, but those protocols may not directly apply to wireless networks due to the effects of power consumption, noise interference, or node's mobility. Related works [5,12,14] consider power management and QoS in wireless environments. Power management is done by considering connection quality of a wireless link and cochannel interference caused by the excessive power by using same frequency, radiated by nodes.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Congestion Control in Wireless Sensor Network

Uthra

Raja

2014

Advances in Intelligent Systems and Computing

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Abstract. Power consumption plays crucial role in wireless sensor network (WSN). WSN is widely used for many applications in industries, military, home monitoring system etc. Data is sensed, manipulated and transmitted to the next hop nodes. Finally it reaches the destination. Certain amount of battery power is consumed by the sensor node for transmitting, receiving, listening and sleeping. In order to utilize the battery power efficiently we developed a technique which finds suitable forwarding node for transmission. The forwarding node is found based on the power level of the transmitter node. The forwarding node is chosen so that the distance to the destination is minimum compared to other neighbor nodes of the transmitter node. Moreover, energy in WSN is wasted due to packet retransmission. Network congestion is one of the primary reasons for packet drop which leads to packet retransmission. Therefore in addition to the energy efficient model, congestion control method is also proposed. Suitable outgoing rate is selected for every node in order to reduce congestion. Simulation results are compared with existing protocols and show improvement.

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“…Here, a QoS is usually required to meet a fixed rate on packet loss, tolerance of packet delay, or traffic throughput. Related works [4][5][6][7][8][9][10]16] consider power management and QoS in wireless environments. Furthermore, connection quality of a wireless link may deteriorate due to co-channel interference caused by the fact that some of the nodes radiate excessive power by using same frequency.…”

Section: Introductionmentioning

confidence: 99%

Power minimization with end-to-end frame error constraints in wireless multi-hop sensor networks

Cited by 3 publications

References 8 publications

Energy‐efficient predictive congestion control for wireless sensor networks

Energy‐efficient predictive congestion control for wireless sensor networks

Energy Efficient Congestion Control in Wireless Sensor Network

An efficient routing scheme with optimal power control in wireless multi-hop sensor networks

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