FOCUS: Fog Computing in UAS Software-Defined Mesh Networks

Gokhan Secinti*, Angelo Trotta, Subhramoy Mohanti, Marco Di Felice, Kaushik R. Chowdhury

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Unmanned aerial systems (UASs) allow easy deployment, three-dimensional maneuverability and high reconfigurability, as they sustain communication network in the absence of pre-installed infrastructure. The proposed FOg Computing in UAS Software-defined mesh network (FOCUS) paradigm aims to realize an implementable network design that considers practical issues of aerial connectivity and computation. It allocates UASs to the tasks of data forwarding and in-network fog computing while maximizing number of ground-users in UAS coverage. FOCUS improves efficient utilization of network resources by introducing on-board computation and innovates on top of software-defined networking stack by integrating the capabilities of network and ground controllers to enable simultaneous orchestration of both UASs and communication flows. There are three main contributions of the paper: First, a SDN-based architecture is designed enabling autonomous configuration of computation and communication as well as managing multi-hop aerial links. Second, a global optimization problem to achieve optimal forwarding and computational allocation is formulated using Open Jackson Network model and solved via a heuristic approach with well defined complexity. Third, FOCUS framework is implemented on a small-scale testbed of Intel® Aero UASs performing image analysis with a full software stack. Experiments reveal at least 32% latency improvement in computation service time compared to traditional centralized computation at the end-server or greedy task allocation schemes within the network.

Original languageEnglish
Article number8944002
Pages (from-to)2664-2674
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Volume21
Issue number6
DOIs
Publication statusPublished - Jun 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2000-2011 IEEE.

Funding

Manuscript received January 4, 2019; revised August 29, 2019; accepted November 18, 2019. Date of publication December 27, 2019; date of current version May 29, 2020. This work was supported by the Office of Naval Research (ONR) Code 30 Other Transaction Agreement (OTA) #N00014-18-9-0001. The Associate Editor for this article was S. Olariu. (Corresponding author: Gokhan Secinti.) G. Secinti, S. Mohanti, and K. R. Chowdhury are with the Electrical and Computer Engineering Department, Northeastern University, Boston, MA 02115 USA (e-mail: [email protected]; [email protected]; [email protected]).

FundersFunder number
Office of Naval Research00014-18-9-0001

    Keywords

    • Unmanned aerial vehicles
    • edge computing
    • heuristic algorithms
    • mobile ad hoc networks
    • software defined networking

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