Critical analysis of resource sharing and optimization in fog clustering

HEZEKIAH SAMWINI; MOHSIN RAZA; ELLA PEREIRA; UMAR KHAN; MUHAMMAD AWAIS

Critical analysis of resource sharing and optimization in fog clustering

HEZEKIAH SAMWINI, MOHSIN RAZA, ELLA PEREIRA, UMAR KHAN, MUHAMMAD AWAIS

University of East Anglia

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding (ISBN) › peer-review

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Abstract

Fog computing aims to process data closer to its source to reduce latency and enhance application performance. However, the integration of an additional fog layer introduces complexities in resource management and service guarantees.
This paper critically analyzes resource sharing and optimization in fog clustering, focusing on adaptive middleware designed to manage resources within and across fog clusters. We present a novel middleware architecture that facilitates efficient load balancing, task scheduling, and inter-cluster communication. The middleware’s performance is evaluated through simulations using OMNeT++, highlighting improvements in response time and resource utilization compared to traditional cloud processing.

Original language	English
Title of host publication	3rd International Conference on Emerging Trends in Smart Technologies
Publisher	Institute of Electrical and Electronics Engineers
Publication status	Accepted/In press - 5 Sept 2024

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IEEE_Conference_Fog_Middleware_ClusteringAccepted author manuscript, 622 KBLicence: CC BY

1 Conference proceeding (ISBN)

Middleware for resource sharing in fog computing with IoT applications
SAMWINI, H., AWAIS, M. & PEREIRA, E., 22 Mar 2023, (Accepted/In press) IEEE EUROCON 2023 - 20th IEEE Conference on Smart Technologies. IEEE, 6 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding (ISBN) › peer-review

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title = "Critical analysis of resource sharing and optimization in fog clustering",

abstract = "Fog computing aims to process data closer to its source to reduce latency and enhance application performance. However, the integration of an additional fog layer introduces complexities in resource management and service guarantees.This paper critically analyzes resource sharing and optimization in fog clustering, focusing on adaptive middleware designed to manage resources within and across fog clusters. We present a novel middleware architecture that facilitates efficient load balancing, task scheduling, and inter-cluster communication. The middleware{\textquoteright}s performance is evaluated through simulations using OMNeT++, highlighting improvements in response time and resource utilization compared to traditional cloud processing.",

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N2 - Fog computing aims to process data closer to its source to reduce latency and enhance application performance. However, the integration of an additional fog layer introduces complexities in resource management and service guarantees.This paper critically analyzes resource sharing and optimization in fog clustering, focusing on adaptive middleware designed to manage resources within and across fog clusters. We present a novel middleware architecture that facilitates efficient load balancing, task scheduling, and inter-cluster communication. The middleware’s performance is evaluated through simulations using OMNeT++, highlighting improvements in response time and resource utilization compared to traditional cloud processing.

AB - Fog computing aims to process data closer to its source to reduce latency and enhance application performance. However, the integration of an additional fog layer introduces complexities in resource management and service guarantees.This paper critically analyzes resource sharing and optimization in fog clustering, focusing on adaptive middleware designed to manage resources within and across fog clusters. We present a novel middleware architecture that facilitates efficient load balancing, task scheduling, and inter-cluster communication. The middleware’s performance is evaluated through simulations using OMNeT++, highlighting improvements in response time and resource utilization compared to traditional cloud processing.

M3 - Conference proceeding (ISBN)

BT - 3rd International Conference on Emerging Trends in Smart Technologies

PB - Institute of Electrical and Electronics Engineers

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Critical analysis of resource sharing and optimization in fog clustering

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Research output

Middleware for resource sharing in fog computing with IoT applications

Cite this