TETES: Trust Based Efficient Task Execution Scheme for Fog Enabled Smart Cities

Author:

Alvi Ahmad Naseem1ORCID,Ali Bakhtiar1ORCID,Saleh Mohamed Saad2,Alkhathami Mohammed2ORCID,Alsadie Deafallah3,Alghamdi Bushra2

Affiliation:

1. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan

2. Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia

3. Information Systems Department, Umm Al-Qura University, Makkah 21955, Saudi Arabia

Abstract

Quality lifestyle leads to increasing trends in smart cities by offering modern communication and information technologies. Smart cities offer multiple applications with smart management of resources such as smart agriculture, Intelligent transportation systems, waste management and energy management. These applications are based on IoTs that are composed of sensor networks with limited processing and computing capabilities and are connected with different types of networks. Due to limited computational capability, IoT sensor nodes require more time to compute different tasks and are required to offload some tasks to remotely placed cloud servers for task execution. Fog nodes are preferred over the cloud as they are placed in close access to IoT nodes distributed in different networks. Different types of networks make it more vulnerable to malicious attacks. Malicious nodes offload complex and high computing tasks to fog nodes to compromise their performance and create delays in the computing tasks of legitimate nodes. In addition, fog nodes even after removing the malicious nodes are unable to process all the legitimate tasks within a specific time frame. In this work, a Trust-based Efficient Task Execution Scheme (TETES) is proposed for fog node that scrutinizes the offloaded tasks sent by the malicious nodes and efficiently execute most of the trusted tasks within a stipulated time cycle. The simulated results show that TETES execute more offloaded tasks as compared to well-known First Come First Serve (FCFS), Longest Task First (LTF), and Shortest Task First (STF) algorithms.

Funder

Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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