Fog-Enabled 5G Networks

Background and Challenges

Contributors

NSF NSF NSF

Thrust 1: Bandwidth-Constrained Task Throughput Maximization in IoT-enabled 5G Networks

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 task demands (e.g. heterogeneous tasks with different priority values) under interference constraints in the presence of limited communication and computational resources. In this paper, our goal is to maximize the total number of tasks served by an IoT-enabled 5G network, labeled \emph{task throughput}, in the presence of heterogeneous task demands and limited resources. Since our original problem is intractable, we propose an efficient two-stage solution based on multi-graph-coloring. We analyze the computational complexity of our proposed algorithm, and prove the correctness of our algorithm. Lastly, simulation results are presented to demonstrate the effectiveness of the proposed algorithm, in comparison with state-of-the-art approaches in the literature.

References
  • A. Pratap, R. Gupta, V. S. S. Nadendla, and S. K. Das, “Bandwidth-Constrained Task Throughput Maximization in IoT-enabled 5G Networks,” Pervasive and Mobile Computing, vol. 69, p. 101281, Nov 2020
  • A. Pratap, R. Gupta, V. S. S. Nadendla, and S. K. Das, “On Maximizing Task Throughput in IoT-Enabled 5G Networks Under Latency and Bandwidth Constraints,” in Proc. of the IEEE Intl. Conf. on Smart Computing (SMARTCOMP ’19), pp. 217–224, June 2019.

    (Best Paper Candidate Award)

Thrust 2: Three-dimensional Matching based Resource Provisioning for IoT-enabled 5G Networks

Internet-of-Things (IoT) is a networking architecture where promising, intelligent services are designed via leveraging information from multiple heterogeneous sources of data within the network. However, the availability of such information in a timely manner requires processing and communication of raw data collected from these sources. Therefore, the economic feasibility of IoT-enabled networks relies on the efficient allocation of both computational and communication resources within the network. Since fog computing and 5G cellular networks approach this problem independently, there is a need for joint resource-provisioning of both communication and computational resources in the networks. As the solution to this problem, we propose a novel three-dimensional matching based resource provisioning algorithm that minimizes average service latency in the presence of various resource constraints, task deadlines and non-identical preferences at IoT devices, fog access points (FAPs) and small-cell access points (SAPs) in 5G networks. We prove the stability and termination of the proposed algorithm and also demonstrate that our proposed algorithm outperforms other state-of-the-art algorithms through both, simulation and realworld experiments on the laboratory test-bed.

References
  • A. Pratap, F. Concone, V. S. S. Nadendla, and S. K. Das, “Three-Dimensional Matching Based Resource Provisioning for the Design of Low-Latency Heterogeneous IoT Networks,” in Proc. of the 22nd Intl. ACM Conf. on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM ’19), pp. 79–86, 2019