Resilient Composition of Drone Services for Delivery

Abstract We propose a novel resilient drone service composition framework for delivery in dynamic weather conditions. We use a skyline approach to select an optimal set of candidate drone services at the source node in a skyway network. Drone services are initially composed using a novel constraint-aware deterministic lookahead algorithm using the multi-armed bandit tree exploration. We propose a heuristic-based resilient service composition approach that adapts to runtime changes and periodically updates the composition to meet delivery expectations. Experimental results prove the efficiency of the proposed approach.

[1]  Dario Floreano,et al.  Downside Up:Rethinking Parcel Position for Aerial Delivery , 2020, IEEE Robotics and Automation Letters.

[2]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008, Proceedings of the Python in Science Conference.

[3]  Timos K. Sellis,et al.  Failure-Proof Spatio-temporal Composition of Sensor Cloud Services , 2014, ICSOC.

[4]  Tae-Ho Kim,et al.  CBDN: Cloud-Based Drone Navigation for Efficient Battery Charging in Drone Networks , 2019, IEEE Transactions on Intelligent Transportation Systems.

[5]  Sebastien Celles,et al.  Windrose: A Python Matplotlib, Numpy library to manage wind and pollution data, draw windrose , 2018, J. Open Source Softw..

[6]  Tao Yu,et al.  Adaptive algorithms for finding replacement services in autonomic distributed business processes , 2005, Proceedings Autonomous Decentralized Systems, 2005. ISADS 2005..

[7]  Grzegorz Chmaj,et al.  Distributed Processing Applications for UAV/drones: A Survey , 2014, ICSEng.

[8]  Rémi Munos,et al.  Bandit Algorithms for Tree Search , 2007, UAI.

[9]  Serguei A. Mokhov,et al.  Constraint verification failure recovery in web service composition , 2018, Future Gener. Comput. Syst..

[10]  Chase C. Murray,et al.  The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery , 2015 .

[11]  Athman Bouguettaya,et al.  Computing Service Skylines over Sets of Services , 2010, 2010 IEEE International Conference on Web Services.

[12]  Bernhard Seeger,et al.  An optimal and progressive algorithm for skyline queries , 2003, SIGMOD '03.

[13]  Paul Schonfeld,et al.  Optimization of Multi-package Drone Deliveries Considering Battery Capacity , 2017 .

[14]  Aurora Trinidad Ramirez Pozo,et al.  A Multi-Armed Bandit selection strategy for Hyper-heuristics , 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).

[15]  Athman Bouguettaya,et al.  Composing Drone-as-a-Service (DaaS) for Delivery , 2019, 2019 IEEE International Conference on Web Services (ICWS).

[16]  Deepayan Chakrabarti,et al.  Multi-armed bandit problems with dependent arms , 2007, ICML '07.

[17]  Kyungsu Park,et al.  Persistent UAV delivery logistics: MILP formulation and efficient heuristic , 2018, Comput. Ind. Eng..

[18]  Jung-Fa Tsai,et al.  A Review of Deterministic Optimization Methods in Engineering and Management , 2012 .

[19]  Kaarthik Sundar,et al.  A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption , 2017, Sensors.

[20]  Mario A. R. Dantas,et al.  Resilient composition of Web services through nondeterministic planning , 2016, 2016 IEEE Symposium on Computers and Communication (ISCC).

[21]  Rolf Rysdyk,et al.  Waypoint Guidance for Small UAVs in Wind , 2005 .

[22]  Yanlong Zhai,et al.  SOA Middleware Support for Service Process Reconfiguration with End-to-End QoS Constraints , 2009, 2009 IEEE International Conference on Web Services.

[23]  Pascal Poizat,et al.  Repair vs. Recomposition for Broken Service Compositions , 2010, ICSOC.

[24]  William B. Carlton,et al.  Dynamic Routing of Unmanned Aerial Vehicles Using Reactive Tabu Search , 2001 .

[25]  Andrew Howard,et al.  Design and use paradigms for Gazebo, an open-source multi-robot simulator , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[26]  Timos K. Sellis,et al.  Spatio-temporal Composition of Sensor Cloud Services , 2014, 2014 IEEE International Conference on Web Services.

[27]  Bulent Soykan,et al.  A Hybrid Tabu/Scatter Search Algorithm for Simulation-Based Optimization of Multi-Objective Runway Operations Scheduling , 2016 .

[28]  Mohsen Guizani,et al.  Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges , 2018, IEEE Access.

[29]  Sameem Abdul Kareem,et al.  Failure recovery of world-altering composite semantic services - a two phase approach , 2012, IIWAS '12.

[30]  Athman Bouguettaya,et al.  Constraint-Aware Drone-as-a-Service Composition , 2019, ICSOC.

[31]  Raffaello D'Andrea,et al.  Guest Editorial Can Drones Deliver? , 2014, IEEE Trans Autom. Sci. Eng..

[32]  Abdelkarim Erradi,et al.  A service computing manifesto: the next 10 years , 2017, Commun. ACM.

[33]  Grzegorz Bocewicz,et al.  Energy Consumption in Unmanned Aerial Vehicles: A Review of Energy Consumption Models and Their Relation to the UAV Routing , 2018, Advances in Intelligent Systems and Computing.

[34]  Sungwoo Kim,et al.  Traveling Salesman Problem With a Drone Station , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[35]  Antonio Franco,et al.  Stochastic analysis of fuel consumption in aircraft cruise subject to along-track wind uncertainty , 2017 .

[36]  Qiang Zhou,et al.  Minimizing the total completion time of an urban delivery problem with uncertain assembly time , 2019 .

[37]  Karen Willcox,et al.  Lookahead Bayesian Optimization with Inequality Constraints , 2017, NIPS.

[38]  Hadi Saboohi An automatic failure recovery method for world-altering composite semantic web services / Hadi Saboohi , 2013 .

[39]  Dane Bamburry,et al.  Drones: Designed for Product Delivery , 2015, Design Management Review.

[40]  Milan Rollo,et al.  Wind Corrections in Flight Path Planning , 2013 .

[41]  Maria Luisa Villani,et al.  QoS-aware replanning of composite Web services , 2005, IEEE International Conference on Web Services (ICWS'05).

[42]  Patrick M. Reed,et al.  Rhodium: Python Library for Many-Objective Robust Decision Making and Exploratory Modeling , 2020 .

[43]  Valérie Issarny,et al.  QoS-Aware Service Composition in Dynamic Service Oriented Environments , 2009, Middleware.

[44]  Aleksandra Faust,et al.  Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots , 2019, ArXiv.

[45]  Athman Bouguettaya,et al.  Multi-attribute optimization in service selection , 2011, World Wide Web.

[46]  Kaarthik Sundar,et al.  Algorithms for Routing an Unmanned Aerial Vehicle in the Presence of Refueling Depots , 2013, IEEE Transactions on Automation Science and Engineering.

[47]  David M Levinson,et al.  Evolution of the Second-Story City: The Minneapolis Skyway System , 2009 .

[48]  Ittetsu Taniguchi,et al.  Low-Energy Routing for Deadline-Constrained Delivery Drones under Windy Conditions , 2019 .

[49]  Athman Bouguettaya,et al.  Crowdsourced Coverage as a Service: Two-Level Composition of Sensor Cloud Services , 2017, IEEE Transactions on Knowledge and Data Engineering.

[50]  Matt J. Kusner,et al.  Bayesian Optimization with Inequality Constraints , 2014, ICML.

[51]  Mohammadreza Radmanesh,et al.  Flight formation of UAVs in presence of moving obstacles using fast-dynamic mixed integer linear programming , 2016 .

[52]  Jack Bowden,et al.  Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges. , 2015, Statistical science : a review journal of the Institute of Mathematical Statistics.

[53]  Sebastian Magierowski,et al.  Vehicle Routing Problems for Drone Delivery , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[54]  Sangyoung Park,et al.  Design space exploration of drone infrastructure for large-scale delivery services , 2016, 2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

[55]  Donald Kossmann,et al.  The Skyline operator , 2001, Proceedings 17th International Conference on Data Engineering.

[56]  Michael Luck,et al.  Adaptive composition in dynamic service environments , 2018, Future Gener. Comput. Syst..

[57]  Liang Chen,et al.  A service computing manifesto , 2017, Commun. ACM.

[58]  H. Abolhassani,et al.  Failure recovery of composite semantic web services using subgraph replacement , 2008, 2008 International Conference on Computer and Communication Engineering.

[59]  Alain Berro,et al.  Genetic algorithms and particle swarm optimization for exploratory projection pursuit , 2010, Annals of Mathematics and Artificial Intelligence.

[60]  Wouter M. Koolen,et al.  Non-Asymptotic Pure Exploration by Solving Games , 2019, NeurIPS.

[61]  Ashish Kapoor,et al.  AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles , 2017, FSR.