Balsam Alkouz

Balsam Alkouz, Osama Amin, Basem Shihada

Emerging on-demand connectivity scenarios increasingly require networking solutions with stringent service-level guarantees. We propose Swarm Network-as-a-Service (SNaaS), a service-oriented framework that leverages fleets of drones to provide on-demand connectivity at scale. SNaaS explicitly models drone-to-device and drone-to-drone interactions as composable services, enabling consumers to request connectivity through Service-Level Agreements (SLAs). We formalize atomic and composite SNaaS services, present an SDN-inspired architecture that integrates the service-oriented triad of provider, consumer, and registry. We introduce a composition framework that orchestrates drones into end-to-end services. Within this framework, we define and analyze three composition strategies, i.e., direct, clustered, and parallel, and propose a queuing-theory-based heuristic for selecting the most suitable strategy under varying load conditions. A dedicated enforcement module continuously monitors queue stability and SLA latency, adaptively reconfiguring the swarm when violations occur. Experiments using real air-to-ground measurements show that the framework consistently outperforms fixed compositions, achieving lower latency, fewer SLA violations, and smoother adaptation as load and swarm size increase.

Xijing Liu, Kevin Lam, Balsam Alkouz et al.

Drone swarms are required for the simultaneous delivery of multiple packages. We demonstrate a multi-stop drone swarm-based delivery in a smart city. We leverage formation flying to conserve energy and increase the flight range of a drone swarm. An adaptive formation is presented in which a swarm adjusts to extrinsic constraints and changes the formation pattern in-flight. We utilize the existing building rooftops in a city and build a line-of-sight skyway network to safely operate the swarms. We use a heuristic-based A* algorithm to route a drone swarm in a skyway network.

Balsam Alkouz, Babar Shahzaad, Athman Bouguettaya

Service delivery is set to experience a major paradigm shift with fast advances in drone technologies coupled with higher expectations from customers and increased competition. We propose a novel service-oriented approach to enable the ubiquitous delivery of packages in a drone-operated skyway network. We discuss the benefits, framework and architecture, contemporary approaches, open challenges and future visioned directions of service-based drone deliveries.

Jermaine Janszen, Babar Shahzaad, Balsam Alkouz et al.

Drones are becoming a novel means for delivery services. We present a demonstration of drone delivery services in a skyway network that uses the service paradigm. A set of experiments is conducted using Crazyflie drones to collect the data on various positions of drones, wind speed, wind direction, and battery consumption. We run the experiments for a range of flight patterns including linear, rectangular, and triangular shapes.

Woojin Lee, Balsam Alkouz, Babar Shahzaad et al.

Current drone delivery systems mostly focus on point-to-point package delivery. We present a multi-stop drone service system to deliver packages anywhere anytime within a specified geographic area. We define a skyway network which takes into account flying regulations, including restricted areas and no-fly zones. The skyway nodes typically represent building rooftops which may act as both recharging stations and delivery destinations. A heuristic-based A* algorithm is used to compute an optimal path from source to destination taking into account a number of constraints, including delivery time, availability of recharging stations, etc. We deploy our drone delivery system in an indoor testbed environment using a 3D model of Sydney CBD. We describe a graphical user interface to monitor the real-time package delivery in the skyway network.

Balsam Alkouz, Athman Bouguettaya

Swarm of drones are increasingly being asked to carry out missions that can't be completed by one drone. Particularly, in delivery, issues arise due to the swarm's limited flight endurance. Hence, we propose a novel formation-guided framework for selecting Swarm-based Drone-as-a-Service (SDaaS) for delivery. A detailed study is carried out to highlight the effect of swarm formations on energy consumption. Two SDaaS selection approaches, i.e. Fixed and Adaptive, are designed considering the different formation decisions a swarm can take. The proposed framework considers extrinsic constraints including wind speed and direction. We propose SDaaS selection algorithms for each approach. Experimental results prove the efficiency of the proposed algorithms.