OsCoMIT: Osmotic computing-based service management for intelligent transportation systems in 5G network

Intelligent Transportation System (ITS) is becoming essential to modern transportation. Due to rise in the number of intelligent vehicles, memory and computation resource allocation closer to the user is becoming increasingly important. With the advent of Mobile Edge Computing, a new processing site is available that can provide memory and computational resource to lower the burden on the core network. However, handling multiple intelligent vehicles near-site requires fast handling of service requests. This paper proposes OsCoMIT, an Osmotic Computing based task segregation and resource allocation framework to handle services decomposed into macroservices and microservices at the edge network. For resource allocation the Proportional Fairness algorithm considers the requirements of the vehicles and maps them to the resources that result in less internal fragmentation. The effectiveness of the proposed framework is demonstrated on Intelligent Transportation System in 5G network using simulation and numerical analysis. It is found that the Proportional Fairness (PF) algorithm is better than the First Come First Serve (FCFS) and Priority Scheduling (PS) Algorithm in terms for memory and computation resource. It maximizes the system’s utility while ensuring fairness and QoS requirements. The performance of OsCoMIT framework is validated statistically using one-way analysis of variance (ANOVA) with 95% confidence interval and the proposed framework shows that the value of F is much greater than \(F_{critical}\) $F_{\mathit{critical}}$ in case of memory and computation resources, which shows the significant improvement.