Towards green computing for Internet of Things: energy oriented path and message scheduling approach

Farhan, L., Kharel, R., Kaiwartya, O. ORCID: 0000-0001-9669-8244, Hammoudeh, M. and Adebisi, B., 2018. Towards green computing for Internet of Things: energy oriented path and message scheduling approach. Sustainable Cities and Society, 38, pp. 195-204. ISSN 2210-6707

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Abstract

Recently, energy efficiency in sensor enabled wire-less network domain has witnessed significant attention from both academia and industries. It is an enabling technological advancement towards green computing in Internet of Things (IoT) eventually supporting sensor generated big data processing for smart cities. Related literature on energy efficiency in sensor enabled wireless network environments focuses on one aspects either energy oriented path selection or energy oriented message scheduling. The definition of path also varies in literature without considering links towards energy efficiency. In this context, this paper proposes an energy oriented path selection and message scheduling framework for sensor enabled wireless network environments. The technical novelty focuses on effective cooperation between path selection and message scheduling considering links on path, location of message sender, and number of processor in sensor towards energy efficiency. Specifically, a path selection strategy is developed based on shortest path and less number of links on path (SPLL). The location of message sender, and number of processor in specific sensor are utilized for developing a longer hops (LH) message scheduling approach. A system model is presented based on M/M/1 queuing analysis to showcase the effective cooperation of SPLL and LH towards energy efficiency. Simulation oriented comparative performance evaluation attest the energy efficiency of the proposed framework as compared to the state-of-the-art techniques considering number of energy oriented metrics.

Item Type: Journal article
Publication Title: Sustainable Cities and Society
Creators: Farhan, L., Kharel, R., Kaiwartya, O., Hammoudeh, M. and Adebisi, B.
Publisher: Elsevier
Date: April 2018
Volume: 38
ISSN: 2210-6707
Identifiers:
NumberType
10.1016/j.scs.2017.12.018DOI
S2210670717309678Publisher Item Identifier
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 14 Aug 2018 08:32
Last Modified: 14 Aug 2018 11:10
URI: https://irep.ntu.ac.uk/id/eprint/34328

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