High Reliability Through Cache Failure Minimization Technique for Workload Execution Under Multi-Core Edge-Cloud Platforms

Abstract

The Internet of Things (IoT) has become an infrastructure for various domain applications such as smart homes, smart cities, wearables, smart grids, etc. Due to these applications, the internet of things search engines has attained some attention from various researchers, industry, and users. The search throughput of IoT search engines is crucial because they must execute hundreds of spatial-time-keyword inquiries in a second. Moreover, IoT search engines use cloud resources to execute tasks. Some of the tasks might have a small workflow but some of the tasks might have a larger workflow and require more virtual machines. Instead of using the virtual machine the best option is to utilize a caching mechanism. In recent years, there are only a few methods that use the caching mechanism for the execution of the task. Furthermore, these methods are not reliable, and efficient and have not considered multicore edge-cloud computing. To overcome this issue, this paper proposes a high-reliability method using the cachefailure mechanism for the multi-core edge-cloud computing architecture. The proposed High Reliability through cache-failure minimization (HRCFM) technique's main aim was to provide better tradeoffs during the execution of the task using the caching mechanism and reduce energy consumption. The results have been compared with the existing energy minimizing scheduling (EMS) and reliability (REL) technique in terms of execution time, power sum, power average, and energy consumption. The results have been compared and it shows that the proposed HRCFM technique reduces the time, energy consumption, power sum, and average by 83.3%, 90.92%, 38.44%, and 91.59% for EMS technique and 81.91%, 91.4%, 41.24% and 91.85% for REL technique respectively.