Energy efficient mobile edge computing framework based on secure host level management for resource allocation

• A MEC framework is proposed for secure and energy aware resource allocation. • A MEC framework is made up of user equipment, third parties and management system. • This work is carried out by considering the energy and security as a major factor. • The host evaluates energy and security cost to rectify the resource constraints. • The effectiveness is computed in terms of delay, make span time and consumption. In Mobile Edge Computing (MEC), task scheduling is used to overcome the problems related to resource constraints in mobile devices. However, the conventional task allocation approaches failed to consider both the energy consumption and security requirements, that leads to higher energy consumption, increased latency and potential vulnerabilities. To overcome these issues, this research proposes a secure and energy-aware task scheduling technique by considering energy and security needs at host level while allocating tasks to Virtual Machines (VMs). The evaluation of energy cost at task allocation helps to enhance the energy efficiency. On the contrary, security is improved via the combination of authentication, confidentiality, and integrity mechanism that ensures secure task execution while maintaining low energy consumption. Thus, the proposed model i.e., multi-tier MEC architecture performs secure resource allocation and reduced energy utilization through effective VM selection and optimized scheduling. The results are evaluated based on energy consumption, average delay, and make span time. For instance, when the result is evaluated by considering energy consumption, the proposed approach consumed 7.3 J of energy when time slot is assigned as 10, while the existing Improved NSGA-II consumed higher energy of 8.2 J in the similar time slot.

Authors

Institutions

Publication Details

Journal
International Journal of Cognitive Computing in Engineering
Published
2025-11-21
DOI
https://doi.org/10.1016/j.ijcce.2025.11.004
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Energy efficient mobile edge computing framework based on secure host level management for resource allocation

S Suhas, Ahmed Alkhayyat, S. P. Paramesh, Abdul Lateef Haroon P S et al.
International Journal of Cognitive Computing in Engineering
IoT and Edge/Fog Computing
article

Energy efficient mobile edge computing framework based on secure host level management for resource allocation

S Suhas, Ahmed Alkhayyat, S. P. Paramesh, Abdul Lateef Haroon P S, Ananda Babu Jayachandra
article en

Abstract

• A MEC framework is proposed for secure and energy aware resource allocation. • A MEC framework is made up of user equipment, third parties and management system. • This work is carried out by considering the energy and security as a major factor. • The host evaluates energy and security cost to rectify the resource constraints. • The effectiveness is computed in terms of delay, make span time and consumption. In Mobile Edge Computing (MEC), task scheduling is used to overcome the problems related to resource constraints in mobile devices. However, the conventional task allocation approaches failed to consider both the energy consumption and security requirements, that leads to higher energy consumption, increased latency and potential vulnerabilities. To overcome these issues, this research proposes a secure and energy-aware task scheduling technique by considering energy and security needs at host level while allocating tasks to Virtual Machines (VMs). The evaluation of energy cost at task allocation helps to enhance the energy efficiency. On the contrary, security is improved via the combination of authentication, confidentiality, and integrity mechanism that ensures secure task execution while maintaining low energy consumption. Thus, the proposed model i.e., multi-tier MEC architecture performs secure resource allocation and reduced energy utilization through effective VM selection and optimized scheduling. The results are evaluated based on energy consumption, average delay, and make span time. For instance, when the result is evaluated by considering energy consumption, the proposed approach consumed 7.3 J of energy when time slot is assigned as 10, while the existing Improved NSGA-II consumed higher energy of 8.2 J in the similar time slot.

International Journal of Cognitive Computing in EngineeringVol. 7
Central University of Karnataka (IN), Iraqi University (IQ)
Openalex Percentile: Top 59%
IoT and Edge/Fog Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.