Queue management plays an important role in the performance of IP based networks and cellular networks in particular where large buffers are often deployed in order to absorb bursts resulting from the dynamic nature of the radio channel. Long standing queues building up in large buffers leads to "Bufferbloat", degrading the performance especially for delay-sensitive applications while small buffers may lower the link utilization. This paper proposes a novel AQM algorithm tailored to cellular networks, mainly by utilizing the Channel Quality Indicator (CQI) periodically reported by user equipment, in order to mitigate Bufferbloat and maintain acceptable levels of performance. Simulation results show that the proposed algorithm reduces the average queuing delay of packets for each user by 40% on average with TCP traffic compared with the CoDel algorithm which has recently become popular.
Internet router buffers are commonly made very large with the aim of minimising losses and maximising link utilisation, supported by the ever-decreasing cost of memory. However, large packet queues not only increase the energy consumption, but can also adversely affect network performance which has recently been attracting attention under 'bufferbloat'. This study compares the buffer-related energy consumption of two models, that is, 'large-buffer with on-off server' and 'small-buffer with always-on server' in the presence of multiplexed on-off traffic and FTP traffic; and demonstrates that the latter model is more energy efficient. Further analysis is then carried out on the 'small-buffer model with always-on server' for the evaluation of its performance against different levels of energy consumption. Relationships among energy, delay, throughput and loss are studied in a range of scenarios, quantifying the variations in performance metrics in relation to energy consumption. In general, lower buffer sizes which reduce the energy consumption were found to improve delay, but sacrifice throughput by 5-8% at high load. Based on a broad set of results, this study provides guidelines for sizing router buffers in realistic networks which would lead to optimal trade-offs between energy consumption and quality of service.
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