Back close

Motion and Connectivity Aware Offloading in Cloud Robotics via Genetic Algorithm

Publication Type : Conference Proceedings

Publisher : GLOBECOM 2017 - 2017 IEEE Global Communications Conference

Source : GLOBECOM 2017 - 2017 IEEE Global Communications Conference (2017)

Url :

Keywords : Bandwidth, Cloud computing, cloud robotics, control engineering computing, decision making, direct acyclic graph, directed graphs, Genetic algorithm, Genetic algorithms, Mobile robots, Network connectivity, Path Planning, Quality of service, robot mobility, Robot sensing systems, Smart cities

Campus : Bengaluru

School : School of Engineering

Center : Electronics Communication and Instrumentation Forum (ECIF)

Department : Electronics and Communication

Verified : Yes

Year : 2017

Abstract : Task offloading opens a gateway for robotic applications to leverage computation support from the cloud infrastructure. It exploits a trade-off between the robot's and cloud's processing capabilities, and the communication between the two entities plays a critical role in making these decisions. Two major factors that significantly influence communication are network connectivity (bandwidth) and mobility of the robot. We integrate these two factors with the offloading decisions to formulate an optimization problem. Our objective in this paper is to improve the quality of service (QoS) for a 25 node application taskflow, known as direct acyclic graph. We propose a genetic algorithm based approach to solve the optimization problem which performs a novel three-layer decision making: (i) whether to offload a task or not, (ii) path planning to reach a desired location for offloading/local execution, (iii) select access point to associate with for offloading. We simulate for a smart city scenario consisting of 36-cell workspace with obstacles and compare the offloading results with a well- established fixed movement offloading method. The outcomes of our study suggest that motion and connectivity aware offloading leads to more efficient performance in terms of improved QoS and minimum consumption of resources, i.e., energy, time or distance.

Cite this Research Publication : A. Rahman, Jin, J., Cricenti, A., Rahman, A., and Manoj Kumar Panda, “Motion and Connectivity Aware Offloading in Cloud Robotics via Genetic Algorithm”, GLOBECOM 2017 - 2017 IEEE Global Communications Conference. 2017.

Admissions Apply Now