On Maximizing Task throughput in IoT-Enabled 5g Networks under Latency and Bandwidth Constraints
Fog computing in 5G networks has played a significant role in increasing the number of users in a given network. However, Internet-of-Things (IoT) has driven system designers towards designing heterogeneous networks to support diverse demands (tasks with different priority values) with different latency and data rate constraints. In this paper, our goal is to maximize the total number of tasks served by a heterogeneous network, labeled task throughput, in the presence of data rate and latency constraints and device preferences regarding computational needs. Since our original problem is intractable, we propose an efficient solution based on graph-coloring techniques. We demonstrate the effectiveness of our proposed algorithm using numerical results, real-world experiments on a laboratory test-bed and comparing with the state-of-the-art algorithm.
A. Pratap et al., "On Maximizing Task throughput in IoT-Enabled 5g Networks under Latency and Bandwidth Constraints," Proceedings of the 5th IEEE International Conference on Smart Computing (2019, Washington, DC), pp. 217-224, Institute of Electrical and Electronics Engineers (IEEE), Jun 2019.
The definitive version is available at https://doi.org/10.1109/SMARTCOMP.2019.00056
5th IEEE International Conference on Smart Computing, SMARTCOMP 2019 (2019: Jun. 12-14, Washington, DC)
Center for High Performance Computing Research
Keywords and Phrases
Fog; IoT; PRB; Resource Allocation
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jun 2019