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Computation Offloading and Scheduling in Edge-Fog Cloud Computing DOI:  https://doi.org/10.30564/jeisr.v1i1.1135 Abstract Resource allocation and task scheduling in the Cloud environment faces many challenges, such as time delay, energy consumption, and security. Also, executing computation tasks of mobile applications on mobile devices (MDs) requires a lot of resources, so they can offload to the Cloud. But Cloud is far from MDs and has challenges as high delay and power consumption. Edge computing with processing near the Internet of Things (IoT) devices have been able to reduce the delay to some extent, but the problem is distancing itself from the Cloud. The fog computing (FC), with the placement of sensors and Cloud, increase the speed and reduce the energy consumption. Thus, FC is suitable for IoT applications. In this article, we review the resource allocation and task scheduling methods in Cloud, Edge and Fog environments, such as traditional, heuristic, and meta-heuristics...

Assessing the Impact of the Lead/Lag Times on the Project Duration Estimates in Highway Construction DOI:  https://doi.org/10.30564/jaeser.v4i3.3383 Abstract The literature mentions multiple factors that can affect the accuracy of estimating the project duration in highway construction, such as weather, location, and soil conditions. However, there are other factors that have not been explored, yet they can have significant impact on the accuracy of the project time estimate. Recently, TxDOT raised a concern regarding the importance of the proper estimating of the lead/lag times in project schedules. These lead/lag times are often determined based on the engineer’s experience. However, inaccurate estimates of the lead/lag time can result in unrealistic project durations. In order to investigate this claim, the study utilizes four time sensitivity measures (TSM), namely the Criticality Index (CI), Significance Index (SI), Cruciality Index (CRI), and the Schedule Sensitivity Index (S...

Comparative Analysis of Scheduling Algorithms Performance in a Long Term Evolution Network Abstract The advancement in cellular communications has enhanced the special attention given to the study of resource allocation schemes. This study is to enhance communications to attain efficiency and thereby offers fairness to all users in the face of congestion experienced anytime a new product is rolled out. The comparative analysis was done on the performance of Enhanced Proportional Fair, Qos-Aware Proportional Fair and Logarithmic rule scheduling algorithms in Long Term Evolution in this work. These algorithms were simulated using LTE system toolbox in MATLAB and their performances were compared using Throughput, Packet delay and Packet Loss Ratio. The results showed Qos-Aware Proportional Fair has a better performance in all the metrics used for the evaluation. Keywords Algorithms; LTE; Scheduling; Network; Performance Full Text: PDF DOI :  https://doi.org/10.30564/jcsr.v3i4.3555