International Journal of Cloud Applications and Computing (IJCAC)

The high levels of energy use for cloud computing affect carbon emissions and climate change. This research thoroughly compares the energy utilisation of conventional and high-speed three-tier data... Show More

The high levels of energy use for cloud computing affect carbon emissions and climate change. This research thoroughly compares the energy utilisation of conventional and high-speed three-tier data centres (DCs). The green cloud simulator (GCS) was used to compare network configurations and energy-saving algorithms for each cloud's energy consumption in 10 trials. The power saver schedule algorithm used the least server energy, while the green and RR schedule algorithms used more. Despite the testing of several energy conservation approaches, core switch and aggregate switch energy usage remained unchanged. Although the high-speed three-tier DC architecture used more energy than the standard design, this is a key difference between the two network topologies. The authors discuss the power saver schedule algorithm's benefits for server energy utilisation. This study shows how three-tier DC architecture can save money by reducing core switch and aggregation switch energy use. These evaluations should include the make span coefficient, and future research should focus on DC transform energy-saving techniques.

A liquefied petroleum gas plant facility (LPGPF) is a series of binary distillation columns used to separate natural gas into four alkanes: ethane, propane, butane, and pentane. The conventional... Show More

A liquefied petroleum gas plant facility (LPGPF) is a series of binary distillation columns used to separate natural gas into four alkanes: ethane, propane, butane, and pentane. The conventional distillation column design consists of three binary distillation columns and six heat exchangers to perform the process. Each heat exchanger consumes immense energy to heat up the reboiler and condense the distillate. There are several process technologies that can minimize distillation column energy consumption. In this research, a fully thermally coupled distillation column (FTCDC) was proposed to minimize energy consumption by reducing the number of heat exchangers and tray columns. An FTCDC has the capability to reduce capital expenditure, operational expenditure, and total annual cost (TAC). The complexity of the FTCDC arises from its process integration. In each column, the intersection composition depends on complex mass and energy balances at the column inlet and outlet and each tray. Process integration, including material recycling and heat recovery, increases the complexity significantly. Moreover, the decision variables are multi-intersection composition for each column to achieve optimum objective function, increasing the number and complexity of the computational load such that effective stochastic optimization algorithms are required. The proposed method was designed using a rigorous vapor liquid equilibrium (VLE) FTCDC model and incorporated with recent stochastic optimization algorithms, such as a genetic algorithm, particle swarm optimization (PSO), an imperialist competitive algorithm, and a duelist algorithm, to determine hydrocarbon composition in the FTCDC intersection. To increase the efficiency and effectiveness of the FTCDC optimization design, cloud computing was utilized. The result was compared with conventional methods such as Fenske-Underwood-Gilliland, a Fenske-Underwood-Gilliland modification, and VLE. The optimization objective function is to minimize TAC with hydrocarbon composition in the FTCDC intersection as decision variables. The optimization using the VLE-PSO method reduces TAC up to 26.28%. All designs were validated using a rigorous model with Aspen HYSYS commercial software. This study's primary goal is to improve the performance of FTCDCs using stochastic algorithms and cloud-based computing capacity. The large amount of computation is handled by cloud-based computing resources, enabling reliability and durability.

The impending exhaustion of internet protocol (IP) version four (IPv4) addresses necessitates a transition to the more expansive IP version six (IPv6) protocol. However, this shift faces challenges... Show More

The impending exhaustion of internet protocol (IP) version four (IPv4) addresses necessitates a transition to the more expansive IP version six (IPv6) protocol. However, this shift faces challenges due to the widespread legacy of IPv4 infrastructure and resistance among organizations to overhaul networks. Host-based translators offer a critical bridging solution by enabling IPv6-only devices to communicate with IPv4-only devices through software-level protocol translation. This paper comprehensively evaluates four pivotal host-based translator mechanisms—bump-in-the-stack (BIS), bump-in-the-application programming interface (API) (BIA), BIA version 2 (BIAv2), and bump-in-the-host (BIH). Using simulated networks with diverse configurations of IPv4/IPv6 applications, hosts, and routing protocols, the authors assessed performance through metrics including packet loss, convergence time, traffic throughput, and overhead. The results reveal variability in effectiveness across both translators and scenarios. BIAv2 demonstrated advantages in throughput and overhead due to stateless mapping. The research underscores the importance of selecting the optimal translation approach for specific network environments and goals. It guides smoother IPv6 adoption by demonstrating how host-based translators can facilitate coexistence during transition. Further exploration of performance tradeoffs can continue guiding effective deployment strategies.