The future of network engineering presents an exciting frontier of innovation, streamlined operations, and enhanced efficiency driven by cutting-edge technologies. Powered by artificial intelligence (AI), machine learning (ML), and automation, the networks of tomorrow promise unprecedented agility and efficiency. Software-defined networking (SDN) and network function virtualization (NFV) seamlessly integrate with cloud infrastructure, unlocking unparalleled scalability and cost efficiencies. Quantum computing and blockchain bolster security measures, ensuring robust protection for sensitive data in cloud environments. As the Internet of Things (IoT) becomes more ubiquitous and 5G expansion accelerates, organizations and network engineers stand ready to architect resilient, high-performance networks that seamlessly integrate cloud services, driving organizational growth and facilitating digital transformation initiatives with unparalleled reliability.
Trends and Innovations
As technology advances, it will provide more options and opportunities for organizations to improve their performance, productivity, and profitability. For example, AI and ML can help ensure smarter adaptive network management and threat mitigation through predictive analytics, anomaly detection, and automated responses to security threats. One organization, CISCO, utilizes machine learning to optimize network performance, predict issues, and automate routine tasks.1 Meanwhile, Zero trust security models2 enhance security by requiring verification at every stage of network access. For example, Google’s BeyondCorp initiative implements a zero trust architecture where network access is granted based on user identity and device health, rather than location on the network.3
Network engineering will continue to streamline operations with automation such as AI and ML, scalability using virtualized resources, and efficiency through continually advancing technologies. One technology, edge computing, processes data closer to the network’s source in order to reduce latency and improve performance. Amazon’s AWS Wavelength extends AWS cloud services to the edge of the 5G network, minimizing latency by bringing data processing closer to the end user and improving application performance.
IoT and 5G growth are crucial in supporting vast numbers of connected devices while allowing for high-speed, reliable network performance. These innovations also result in low latency, enabling real-time communication for critical applications. The most recent 5G technology enables more reliable connections and increased data speeds that are in high demand. For example, Verizon’s 5G rollout incorporates network slicing, which allows for creating multiple virtual networks on a single physical 5G network infrastructure, tailored to different service requirements. This allows Verizon to offer more tailored, efficient, and high-performing network services.4
Network engineering integrates with cloud infrastructure via hybrid and multicloud strategies that support seamless connectivity between on premises and cloud environments.5 Network engineering can integrate robust security measures within cloud architectures, leveraging NFV and SDN to enhance flexibility and scalability. This integration not only fortifies the cloud infrastructure but also ensures that security measures are adaptable to evolving threats and compliance requirements. Quantum computing and blockchain are also revolutionizing network security and efficiency.6 Through rapidly evolving quantum technology, unprecedented computational speed and capabilities drive network optimization, resulting in more advanced security procedures. Organizations and network engineers can prepare for the advent of emergent technologies by staying informed on advancements in quantum computing and its implications, and collaborating with researchers and specialists to develop and implement quantum-resistant technologies. For example, blockchain technology provides tamper-proof logs of network transactions, enhancing transparency, data integrity, traceability, and security in supply chain networks. It also reduces the risk of centralized points of failure. Furthermore, identity management can be simplified and strengthened through blockchain by implementing decentralized and secure identity verification systems, granting organizations greater control over their digital assets.
NFV and SDN
To further improve speed, NFV allows for more efficient resource utilization and faster deployment of network services. NFV involves decoupling network functions from proprietary hardware, allowing them to run on virtual machines. This offers 3 significant contributions:
- Flexibility enables rapid deployment and scaling of network services.
- The reduced need for specialized hardware results in cost savings for the organization.
- NFV allows for more experimentation, providing faster rollouts of new services.
This flexibility allows organizations to innovate more rapidly, adapt to market changes, and optimize their operations, ultimately driving growth and efficiency. One organization, AT&T, has deployed NFV to virtualize its network functions such as firewalls and routers, reducing the reliance on proprietary hardware and enabling more flexible and scalable service delivery.7
Furthermore, networks leverage SDN for more flexible and programmable network infrastructures and traffic. SDN separates the control plane from the data plane, enabling centralized network traffic control. It plays a crucial role in flexibility through dynamic adjustments to network configurations and enables organizations to improve security by implementing comprehensive, centralized security policies. SDN boosts efficiency by streamlining resource allocation and utilization, thereby optimizing operations and delivering significant benefits to organizations. For example, Google’s B4 network8 uses SDN to manage its global data center interconnections. SDN allows dynamic bandwidth allocation and efficient traffic management by decoupling the control plane from the data plane, allowing Google to manage resources and improve processes efficiently and effectively.
Challenges
Various network engineering challenges may arise, but being prepared for them is the first step to mitigation. One obstacle is finding employees with the necessary skills and expertise. An expert will have a deep understanding of advanced security protocols and threat mitigation and will be proficient in AI and ML to leverage optimization. Organizations must ensure that they are hiring candidates with cloud infrastructure and hybrid environment mastery. To facilitate this mastery internally, organizations should consider offering continuous learning and certification programs to further develop the skills and expertise of their workforce. Practical experience is crucial in network engineering. Labs and simulation tools allow engineers to test configurations, troubleshoot issues, and understand network behaviors in a controlled environment, reducing the risk of errors in live systems.
Common challenges faced during the adoption of new network engineering technologies include integration compatibility with existing systems, which can be overcome through pilot programs to test tech in controlled environments, and skill gaps, which can be mitigated by investing in staff training, education, and certifications such as a Cisco’s Certified Network Professional (CCNP), AWS Certified Solutions Architect, Microsoft Azure Administrator, Certified Information Systems Security Architect (CISSP), and more. Security concerns are also common when implementing new technology, so integrating comprehensive security measures from the outset is critical.9 Organizations can incorporate robust data protection measures by utilizing strong authentication and authorization mechanisms and setting up end-to-end encryption for data in transit and at rest. Employing AI and ML for real-time threat detection and responses is highly beneficial, as is ensuring adherence to regulatory standards and best practices.
Various network engineering challenges may arise, but being prepared for them is the first step to mitigation.
Evolving regulatory frameworks impact network engineering through the implementation of stronger data protection and privacy practices mandates. Even sectors that are not traditionally stringent with compliance requirements are showing a need for stronger regulations within the European Union General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA) in the US, and the United States Health Insurance Portability and Accountability Act (HIPAA). An increase in comprehensive monitoring and reporting mechanisms requirements continues to challenge industries . For example, retail companies often face challenges with GDPR compliance as they collect customer data for marketing. This collection requires explicit consent and strong data protection measures, which were not previously stringent. Moreover, many tech startups that gather user data through apps must comply with CCPA, which mandates transparency and user rights to access and delete their data. Even Healthcare organizations, particularly smaller ones, struggle with securing patient data under HIPAA due to limited resources. However, there are solutions available for organizations looking to protect their data as they implement new technologies.
Solutions for Organizations
To prepare for the future of network engineering, organizations should invest in targeted research and development focused on innovative technologies. This includes areas such as AI-driven network optimization, blockchain for secure transactions, and quantum-resistant cryptography. For example, Google’s use of AI to optimize data center energy efficiency highlights how machine learning can significantly reduce operational costs and carbon footprints.
Organizations should establish dedicated emerging technology teams, distinct from traditional IT teams. These teams focus on innovation and consist of data scientists, blockchain developers, and cybersecurity experts. Unlike IT teams that maintain existing systems, these teams are tasked with exploring and implementing technologies such as Cisco’s intent-based networking, which uses AI and machine learning to automate network management.
Continuous learning is crucial, and organizations can promote this through partnerships with platforms like Coursera or Udacity for ongoing training in new technologies. Encouraging certifications in cloud services from AWS or Azure can keep skills sharp and relevant. For example, many security platforms have achieved the Federal Risk and Authorization Management Program (FedRAMP) federal government certification, the highest authorization level available for high-security sectors. FedRAMP is a United States government initiative that provides a standardized approach to security assessment, authorization, and continuous monitoring for cloud products and services.10
Furthermore, collaboration with technology providers and research institutions is vital. This can involve partnerships with companies like IBM for quantum computing initiatives or joining consortiums such as the Linux Foundation11 for open-source projects.
Implementing agile methodologies, such as Scrum or Kanban, around new trends and challenges allows organizations to iterate quickly and integrate new solutions efficiently. For instance, Spotify’s use of agile practices to continuously improve its music recommendation algorithms serves as a model for how rapid iteration can lead to superior customer experiences.12
The expected outcome of these strategies is a robust, innovative organization capable of adapting to technological changes. This approach ensures enhanced security, efficiency, and competitiveness in the rapidly evolving landscape of network engineering.
Conclusion
Adopting advanced technologies and frameworks in networking is critical. Leveraging AI/ML, SDN, NFV, and blockchain can significantly enhance network efficiency and security. However, organizations must remember that robust data protection measures are essential for safeguarding sensitive information and maintaining regulatory compliance. By staying informed about the latest trends and acquiring new skills, organizations and network engineers can better prepare for the evolving landscape of network engineering.
Endnotes
1 Centoni, L.; “From AI to Quantum, Innovating for a Better World,” CISCO, 6 June 2023
2 National Security Agency/Central Security Service, “NSA Releases Guidance on Zero Trust Maturity Throughout the Application and Workload Pillar,” USA, 22 May 2024
3 Google Cloud, Beyond Corp
4 Kinney, S.; “How is Verizon Approaching 5G Standalone in 2024?,” RCR Wireless News, 22 January 2024
5 Zscaler, Inc., “Zscaler Achieves Zero Trust Security-as-a-Service FedRAMP High Authorization,” Yahoo Finance, 1 August 2022
6 National Institute of Standards and Technology, “NIST Announces First Four Quantum-Resistant Cryptographic Algorithms,” USA, 5 July 2022
7 AT&T Business, AT&T Network Functions Virtualization Simplifies Network Infrastructure
8 Salisbury, B.; “Inside Google's Software-Defined Network,” Network Computing, 13 May 2023
9 Meneses, M.; “Citizen Action Combines With Innovative New Methods to Combat Cybersecurity Threats,” The Quantum Record, 16 June 2024
10 FedRAMP
11 The Linux Foundation
12 Borg, J.; “Ultimate Guide to How the Spotify Music Discovery Algorithm Works,” Hypebot, 7 March 2024
Abdul Qayyum Mohammed
Is a senior network engineer for Zebra Technologies, a world leader in innovative digital solutions, hardware, and software. He has more than 11 years of experience designing and implementing IT network architecture, including configuration, optimization, and supporting network management systems. Connect with Mohammed on LinkedIn: http://www.linkedin.com/in/abdul-mohammed-9a0828128/.
