Provider-centric Allocation of Drone Swarm Services
Balsam Alkouz, Athman Bouguettaya

TL;DR
This paper introduces a framework for efficiently allocating drone swarms for delivery services, optimizing provider profit while satisfying consumer time constraints and environmental limitations.
Contribution
It presents a novel allocation framework and three algorithms for drone swarm assignment considering cost, feasibility, and environmental constraints.
Findings
The algorithms improve provider profit and request fulfillment.
The framework accounts for environmental constraints like recharging pads.
Experimental results compare algorithm efficiency in various scenarios.
Abstract
We propose a novel framework for the allocation of drone swarms for delivery services known as Swarm-based Drone-as-a-Service (SDaaS). The allocation framework ensures minimum cost (aka maximum profit) to drone swarm providers while meeting the time requirement of service consumers. The constraints in the delivery environment (e.g., limited recharging pads) are taken into consideration. We propose three algorithms to select the best allocation of drone swarms given a set of requests from multiple consumers. We conduct a set of experiments to evaluate and compare the efficiency of these algorithms considering the provider's profit, feasibility, requests fulfilment, and drones utilization level.
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