Energy-aware adaptive offloading of soft real-time jobs in mobile edge clouds

• Type: Article in International Scientific Journal
• Date: 2021

Authors

Silva, J (Author) Other; Eduardo Marques (Author) FCUP; Lopes, L (Author) FCUP; Silva, F (Author) FCUP

Journal

The Journal is awaiting validation by the Administrative Services.

Title: JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS

Vol. 10

Final page: 38

ISSN: 2192-113X

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Scientific classification

CORDIS: Technological sciences

FOS: Engineering and technology

Other information

Authenticus ID: P-00T-J76

DOI: 10.1186/s13677-021-00251-9

Abstract (EN): We present a model for measuring the impact of offloading soft real-time jobs over multi-tier cloud infrastructures. The jobs originate in mobile devices and offloading strategies may choose to execute them locally, in neighbouring devices, in cloudlets or in infrastructure cloud servers. Within this specification, we put forward several such offloading strategies characterised by their differential use of the cloud tiers with the goal of optimizing execution time and/or energy consumption. We implement an instance of the model using Jay, a software framework for adaptive computation offloading in hybrid edge clouds. The framework is modular and allows the model and the offloading strategies to be seamlessly implemented while providing the tools to make informed runtime offloading decisions based on system feedback, namely through a built-in system profiler that gathers runtime information such as workload, energy consumption and available bandwidth for every participating device or server. The results show that offloading strategies sensitive to runtime conditions can effectively and dynamically adjust their offloading decisions to produce significant gains in terms of their target optimization functions, namely, execution time, energy consumption and fulfilment of job deadlines.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 21