Improved iterative adaptive thresholding algorithm with sleep scheduling for lifetime maximization in wireless sensor Network

Bhattad, J.M.; Chede, Santosh D.

doi:10.1109/wiecon-ece.2016.8009134

Cited by 1 publication

(2 citation statements)

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“…Then we make simulation and comparisons the performance of various wireless network system approaches including three network designs (NDN platform stands for conventional ICN design, sleep scheduling ICN [ 22 ] and the proposed ICN model) under the same network condition and parameters as described. We use the proposed chunk-based aggregated packets as the forwarding scheme and sensor power-based cache management policy for the proposed ICN system.…”

Section: Performance Evaluations and Discussionmentioning

confidence: 99%

“…For green networking, a combination of rate-adaptivity and power-aware routing for greening approaches was stated in [ 21 ] to save network power consumption by giving a simple model of power based on two kinds of link states (on and off), with a comparison on the benefit of each one. As the power consumption of the network system can be taken as a function of network devices status, sleep scheduling algorithm was proposed in [ 22 ] as an efficient method to save device energy. Recently, the authors in [ 23 ] studied an overview of green IoT and its challenges due to the energy usage of IoT devices.…”

Section: Related Workmentioning

confidence: 99%

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A Smart Congestion Control Mechanism for the Green IoT Sensor-Enabled Information-Centric Networking

Sukjaimuk

Nguyễn

Sato

2018

Sensors

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Information-Centric Networking (ICN) is a new Internet architecture design, which is considered as the global-scale Future Internet (FI) paradigm. Though ICN offers considerable benefits over the existing IP-based Internet architecture, its practical deployment in real life still has many challenges, especially in the case of high congestion and limited power in a sensor enabled-network for the Internet of Things (IoT) era. In this paper, we propose a smart congestion control mechanism to diminish the network congestion rate, reduce sensor power consumptions, and enhance the network performance of ICN at the same time to realize a complete green and efficient ICN-based sensor networking model. The proposed network system uses the chunk-by-chunk aggregated packets according to the content popularity to diminish the number of exchanged packets needed for data transmission. We also design the sensor power-based cache management strategy, and an adaptive Markov-based sensor scheduling policy with selective sensing algorithm to further maximize power savings for the sensors. The evaluation results using ndnSIM (a widely-used ICN simulator) show that the proposed model can provide higher network performance efficiency with lower energy consumption for the future Internet by achieving higher throughput with higher cache hit rate and lower Interest packet drop rate as we increase the number of IoT sensors in ICN.

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Section: Performance Evaluations and Discussionmentioning

confidence: 99%