Introduction
Cloud networking became a valuable tool for organizations to outsource computing tasks and reduce the number of people involved in these activities. Indeed, many companies have already moved to cloud computing which allowed them to increase the cost-efficiency of their businesses (Pourvali, 2017). Cloud networking comprises five essential elements: server virtualization, network virtualization, distributed file processing, file service platforms, and proper management (Kim et al., 2019). cc network’s performance and create access to service resources for users at any time (Nedyalkov et al., 2018). Cloud computing platforms allow users to build a cloud infrastructure without a deep understanding of software and hardware (Nedyalkov et al., 2018). It enables reducing operation costs and people involvement, which removes the need for additional human resources. There are many other advantages to cloud networking, but some issues still need to be solved. Specifically, maintenance, data integration, and response time should be further improved (Kim et al., 2019). Upgrading cloud centers with more nodes and decentralization is essential for boosting cloud-based models and increasing work efficiency in organizations that employ cloud networking.
Challenges in Cloud Networking
Since cloud computing is constantly evolving, some issues will always appear and require fixing and improvement. The first problem is that research in this field is costly because development and testing involve the utilization of many resources (Nedyalkov et al., 2018). Specifically, cloud data centers’ energy consumption and occupied area are high (Varghese & Buyya, 2018). Although cloud computing is cheaper for companies due to outsourcing, doing research and maintaining these centers is still quite expensive. Second, cloud modeling experiments cannot be iterated, posing an additional burden on research in this field (Nedyalkov et al., 2018). The third issue is that traffic load by cloud devices is hard to predict; thus, it may cause abrupt failures in cloud operation (Nedyalkov et al., 2018). The fourth complication in cloud networking is that centralized cloud data centers can fail, affecting many users (Varghese & Buyya, 2018). Indeed, the decentralization of cloud infrastructure improved its performance (Varghese & Buyya, 2018). However, many businesses depend on cloud computing now; therefore, ensuring the constant operating of a data center is critical.
Another critical issue that needs to be discussed separately is privacy and security in cloud networking. According to Varghese and Buyya (2018), cloud networks are not entirely safe because they provide access to storage and computing for multiple users, requiring several routers. Furthermore, hackers can access various nodes through the edge router, resulting in data leakage from public clouds and malicious use of stored information, posing a danger to customers’ and providers’ privacy (Varghese & Buyya, 2018). Indeed, the lack of proper data encryption and management of access can compromise cloud security. Therefore, developing methods for preserving public cloud data safety from malware and spyware attacks is crucial.
Cloud-Based Models
Cloud networking incorporates cloud-based models that allow clients and providers comfortable operation options. Three types of cloud service delivery models are known: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) (Pourvali, 2017). According to Vogel (2017), “IaaS is considered the base layer in cloud architecture,” which means PaaS and SaaS are built on the Infrastructure Service (p. 468). All three models possess features that are controlled by clients and providers (Pourvali, 2017). Specifically, networking, storage, servers, and virtualization are run by providers while customers handle middleware, data, applications, and runtime in IaaS (Pourvali, 2017). Platform and software services allow for more cloud control for clients (Pourvali, 2017). According to Wulf et al. (2021), the advantages of SaaS are the availability of information systems, quick delivery, and strategic differentiation. The primary benefits of IaaS and PaaS utilization in companies are sizing flexibility and faster delivery of products to market (Wulf et al., 2021). These three cloud-based models allow companies to increase work efficiency, especially at times of global lockdown, like during the ongoing COVID-19 pandemic.
Ways to Improve Performance of Cloud Data Centers
Computer scientists constantly work on the improvement of cloud networking performance. Various software tools are used to boost virtualization in cloud networks. For example, Kernel-based Virtual machine (KVM) is the most popular virtualization software for clouds at the hardware level, which mainly uses Linux systems (Vogel et al., 2017). Cloud-based models can also utilize Linux Containers (LXC) which are also virtualization methods but on the operating system level. Both virtualization containers possess certain benefits, but their performance can be increased. For example, according to Vogel et al. (2017), increasing the number of nodes in Ubuntu servers, which resembled Linux-based cloud centers in their study, doubled virtualization containers’ production. Since nodes in this study represented the back ends, including application, server, and database, increasing their numbers and decentralization can significantly improve cloud function. Moreover, artificial intelligence and neural network can be used for traffic prediction (Sofia & GaneshKumar, 2018). Implementing these machine learning algorithms can help accurately assess and calculate potential energy consumption by cloud data centers, develop sustainable operations in the real world, and solve iteration issues in research.
Security issues can be addressed by employing proper data enciphering. According to Varghese and Buyya (2018), current models utilize identity authentication and encryption to ensure information protection in clouds from hackers’ attacks. However, these methods do not always provide data safety from malicious invasion. Therefore, a “secure reprogrammable protocol” that will be re-checking unauthorized installations can become an additional layer of protection (Varghese & Buyya, 2018, p. 854). Still, research in the sphere of cloud computing security should constantly develop novel methods of defense against malware programs.
Conclusion
To sum up, cloud networking is a vast field that became incorporated into many organizations. Cloud service allows flexibility and cost-efficiency due to the possibility to outsource computing tasks. Three cloud-based models are available to users: infrastructure, platform, and software – are known as IaaS, PaaS, and SaaS, respectively. PaaS and SaaS are based on IaaS with slight differences in controlling power between clients and providers. However, some issues that arise in cloud networks still require the development of innovative solutions. For example, energy consumption, data traffic, and large cloud centers’ maintenance need significant investments. Furthermore, public clouds are vulnerable to malicious hacker attacks, which compromise user information security. One of the ways to reduce risks associated with the large cloud data center is decentralization. Indeed, decentralization was found to boost KVM and LXC virtualization software performance twice their original activity. Machine learning algorithms can be employed to predict traffic and energy consumption by cloud centers. Finally, data security can be protected by authentication, encryption, and utilizing reprogrammable protocols to prevent the installation of malware programs.
References
Kim, J., Manaligod, H. J. T., Lee, J., & Jo, S. (2019). Cloud networking computing. Wireless Personal Communications, 105: 399-404. Web.
Nedyalkov, I., Stefanov, A., & Georgiev, G. (2018). Modelling and studying of cloud infrastructures. 2018 International Conference on High Technology for Sustainable Development (HiTech), 1–4. Web.
Pourvali, M. (2017). Resilience of cloud networking services for large scale outages [Doctoral dissertation, University of South Florida]. Scholar Commons.
Sofia, A. S., & GaneshKumar, P. (2018). Multi-objective task scheduling to minimize energy consumption and makespan of cloud computing using NSGA-II. Journal of Network and Systems Management, 26(2), 463-485.
Varghese, B., & Buyya, R. (2018). Next generation cloud computing: New trends and research directions. Future Generation Computer Systems, 79, 849–861. Web.
Vogel, A., Griebler, D., Schepke, C., & Fernandes, L. G. (2017). An intra-cloud networking performance evaluation on CloudStack environment. 25th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 468–472. Web.
Wulf, F., Lindner, T., Strahringer, S., & Westner, M. (2021). IaaS, PaaS, or SaaS? The why of cloud computing delivery model selection. Proceedings of the 54th Hawaii International Conference on System Sciences, 6285–6294. Web.