International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 180 - Issue 10 |
Published: Jan 2018 |
Authors: Ma'en Saleh |
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Ma'en Saleh . Security Aware Routing Protocol for Intelligent Transportation Distributed Multi-Agent System. International Journal of Computer Applications. 180, 10 (Jan 2018), 5-13. DOI=10.5120/ijca2018916153
@article{ 10.5120/ijca2018916153, author = { Ma'en Saleh }, title = { Security Aware Routing Protocol for Intelligent Transportation Distributed Multi-Agent System }, journal = { International Journal of Computer Applications }, year = { 2018 }, volume = { 180 }, number = { 10 }, pages = { 5-13 }, doi = { 10.5120/ijca2018916153 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2018 %A Ma'en Saleh %T Security Aware Routing Protocol for Intelligent Transportation Distributed Multi-Agent System%T %J International Journal of Computer Applications %V 180 %N 10 %P 5-13 %R 10.5120/ijca2018916153 %I Foundation of Computer Science (FCS), NY, USA
Most recent VANETs routing protocols have neither taken into consideration security aspects nor the available resources at the mobile node. In this research, a security-aware road-side routing protocol with resource estimation methodology (SRSR_RE) for VANETs in a segmented road topology was proposed. The proposed algorithm was modelled by a distributed multi-agent system and to be installed at each road-side base-unit (RSU). The algorithm combines a congestion control unit that adopts a resource estimation mechanism with a secure-route discovery scheme. By such combination, both security and quality-of-service (QoS) requirements are guaranteed, and thus making our VANET robust against security threats besides protecting it from being congested. Compared to the insecure road-side (IRSR) and secure road-side (SRSR) protocols, extensive simulation results show the highest capability of the proposed protocol (SRSR_RE) in maximizing the secure delivery of the data packets and minimizing the end-to-end delays for VANETs with different network’s factors such as nodes density, number of malicious nodes and node’s buffer size.