Enhancing the reliability on data delivery and energy efficiency by combining swarm intelligence and community detection in large-scale WSNs

Author(s)

Rosset, Valerio ; Paulo, Matheus A. ; Cespedes, Juliana G. ; Nascimento, Maria C. V.

• Document type: Journal article
• Source: EXPERT SYSTEMS WITH APPLICATIONS; v. 78, p. 89-102, JUL 15 2017.
• Web of Science Citations: 14

Abstract

In Wireless Sensor Networks (WSNs) to address the duality between the cost-effective energy efficiency and the reliable data delivery is a relevant issue. This paper presents a novel bio-inspired routing protocol, named CB-RACO, that combines the Ant Colony Optimization (ACO) meta-heuristic with the computationally cheap and distributed community detection technique Label Propagation (LP). CB-RACO creates communities in the WSNs and meets the balance of energy consumption by routing data inside-communities through swarm intelligence. As a consequence, CB-RACO demands low memory and overhead in construction and maintenance of routing paths. Additionally, CB-RACO achieves high data delivery reliability through a data retransmission strategy based on acknowledgments between communities. We simulated CB-RACO in large-scale scenarios according to the goodput, delivery delay and energy consumption metrics. The results have shown that the proposed approach may provide significant improvement in comparison to ant-based strategies that do not rely on community structures. (C) 2017 Elsevier Ltd. All rights reserved. (AU)

• FAPESP's process: 15/18580-9 - Meta-heuristics for reliable communication in large scale wireless sensor and actuator networks
• Grantee: Valerio Rosset
• Support Opportunities: Regular Research Grants
• FAPESP's process: 15/21660-4 - Hibridizing heuristic and exact methods to approach combinatorial optimization problems
• Grantee: Mariá Cristina Vasconcelos Nascimento Rosset
• Support Opportunities: Regular Research Grants