Hybrid Genetic Algorithm Combining Simulated Annealing for Task Allocation with Data Security

Wanli Yu*, Yanqiu Huang, Yuan Yang, Alberto Garcia-Ortiz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Task allocation and scheduling schemes have been widely used for the emerging computation-intensive Internet of Things applications to achieve energy efficiency and meet the latency requirement. However, collaborative task execution brings a high risk of security threats, e.g., malicious attacks or eavesdropping, because communication over wireless channel is naturally vulnerable. This work addresses the task allocation problem considering security threats. Firstly, it develops a general framework for the problem of task allocation with data security termed TADS. Besides the energy and latency requirements, TADS also considers the data confidentiality required by both the surrounding environment and the application tasks' criticality. Then, this work proposes a security-aware task allocation algorithm, GASA, by combining the genetic algorithm and the simulated annealing approach to distribute the application tasks across the network efficiently. Extensive simulations have been performed in various testing environments to validate the proposed GASA algorithm. The results illustrate the considerable performance improvements compared with the existing approaches in terms of algorithm convergence rate, network lifetime extension, etc.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publication19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
PublisherIEEE
Pages134-141
Number of pages8
ISBN (Electronic)979-8-3503-4649-7
ISBN (Print)979-8-3503-4650-3
DOIs
Publication statusPublished - 27 Sept 2023
Event19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023 - Paphos, Cyprus
Duration: 19 Jun 202321 Jun 2023
Conference number: 19
https://dcoss.org/dcoss23/

Publication series

NameProceedings - 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
PublisherIEEE
ISSN (Print)2325-2936
ISSN (Electronic)2325-2944

Conference

Conference19th International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023
Abbreviated titleDCOSS-IoT 2023
Country/TerritoryCyprus
CityPaphos
Period19/06/2321/06/23
Internet address

Keywords

  • Data confidentiality
  • hybrid genetic algorithm
  • multihop wireless networks
  • simulated annealing
  • task allocation and scheduling
  • 2023 OA procedure

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