Robust orchestration of concurrent application workflows in mobile device clouds

A hybrid mobile/fixed device cloud that harnesses sensing, computing, communication, and storage capabilities of mobile and fixed devices in the field as well as those of computing and storage servers in remote datacenters is envisioned. Mobile device clouds can be harnessed to enable innovative per...

Full description

Saved in:
Bibliographic Details
Published in:Journal of parallel and distributed computing Vol. 120; pp. 101 - 114
Main Authors: Pandey, Parul, Viswanathan, Hariharasudhan, Pompili, Dario
Format: Journal Article
Language:English
Published: Elsevier Inc 01.10.2018
Subjects:
Application workflows
Controlled replication
Distributed computing
Mobile device clouds
Testbed
Testbed
Controlled replication
Application workflows
Mobile device clouds
Distributed computing
ISSN:0743-7315, 1096-0848
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A hybrid mobile/fixed device cloud that harnesses sensing, computing, communication, and storage capabilities of mobile and fixed devices in the field as well as those of computing and storage servers in remote datacenters is envisioned. Mobile device clouds can be harnessed to enable innovative pervasive applications that rely on real-time, in-situ processing of sensor data collected in the field. To support concurrent mobile applications on the device cloud, a robust distributed computing framework, called Maestro, is proposed. The key components of Maestro are (i) a task scheduling mechanism that employs controlled task replication in addition to task reallocation for robustness and (ii) Dedup for task deduplication among concurrent pervasive workflows. An architecture-based solution that relies on task categorization and authorized access to the categories of tasks is proposed for different levels of trust. Experimental evaluation through prototype testbed of Android- and Linux-based mobile devices as well as simulations is performed to demonstrate Maestro’s capabilities. •A mobile device cloud to harnesses local and remote compute resources is proposed.•A task scheduling mechanism that employs controlled task replication is proposed.•A task deduplication mechanism to handle similar tasks across workflows is proposed.•A solution is designed to categorize tasks according to sensitivity of input data.•Experiments and simulations demonstrate capabilities of proposed work.
ISSN:0743-7315
1096-0848
DOI:10.1016/j.jpdc.2018.05.004