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.

Meeting Name

5th IEEE International Conference on Smart Computing, SMARTCOMP 2019 (2019: Jun. 12-14, Washington, DC)


Computer Science

Research Center/Lab(s)

Center for High Performance Computing Research


This work is partially supported by NSF grants under award numbers CNS-1818942, CCF-1725755, CNS-1545037, and CNS-1545050.

Keywords and Phrases

Fog; IoT; PRB; Resource Allocation

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


File Type





© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jun 2019