Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 3, Issue 6, Pages 1437-1447Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2016.2613111
Keywords
Energy consumption function; energy efficiency; multi-constraint optimization network criticality; rerouting
Categories
Funding
- National Natural Science Foundation of China [61571104, 61071124, 61572231]
- General Project of Scientific Research of the Education Department of Liaoning Province [L20150174]
- Program for New Century Excellent Talents in University [NCET-11-0075]
- Fundamental Research Funds for the Central Universities [N150402003, N120804004, N130504003]
- State Scholarship Fund [201208210013]
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Many researches show that the power consumption of network devices of ICT is nearly 10% of total global consumption. While the redundant deployment of network equipment makes the network utilization is relatively low, which leads to a very low energy efficiency of networks. With the dynamic and high quality demands of users, how to improve network energy efficiency becomes a focus under the premise of ensuring network performance and customer service quality. For this reason, we propose an energy consumption model based on link loads, and use the network's bit energy consumption parameter to measure the network energy efficiency. This paper is to minimize the network's bit energy consumption parameter, and then we propose the energy-efficient minimum criticality routing algorithm, which includes energy efficiency routing and load balancing. To further improve network energy efficiency, this paper proposes an energy-efficient multi-constraint rerouting (E2MR2) algorithm. E2MR2 uses the energy consumption model to set up the link weight for maximum energy efficiency and exploits rerouting strategy to ensure network QoS and maximum delay constraints. The simulation uses synthetic traffic data in the real network topology to analyze the performance of our method. Simulation results that our approach is feasible and promising.
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