Piyush Somani Predicts Explosive Growth and AI Integration in Edge Computing

Edge computing has emerged as a transformative force in the tech industry, driven by the growing demand for real-time data processing and the proliferation of Internet of Things (IoT) devices. In an insightful interview with Piyush Somani, we explore the remarkable advancements and future trajectories of edge computing technologies. From the significant milestones achieved in recent years to the anticipated breakthroughs on the horizon, Somani provides a comprehensive overview of how edge computing is reshaping various industries and what lies ahead. This discussion also delves into ongoing research efforts, the evolving role of standards bodies, best practices for deployment in regulated sectors, and innovative use cases that extend beyond traditional applications. Excerpt:

How has the development of edge computing technologies progressed over the past few years, and what key milestones or advancements have been achieved?

In recent years, more recently, edge computing technologies have rapidly been developing due to the growing need for real-time data processing and the spread of Internet of Things devices. According to research, the global edge computing market was valued at USD 16.45 billion in 2023 and is projected to grow at a CAGR of 36.9% from 2024 to 2030. The key breakthroughs and progress involve:

· Development of edge devices: - Edge devices, like routers, gateways, and IoT sensors, now have increased processing capabilities to run advanced analytics at the network edge.

· Proliferation of Edge Computing Platforms: The rise of new-age edge computing platforms and frameworks makes it easy to develop and deploy edge applications.

· Integration with AI and IoT: The edge computing with AI and IoT has led to interesting edge applications. Now AI algorithms can be arranged on the edge for real-time analysis, while IoT devices produce streaming data for local processing and insights.

· Standardization efforts: Finally, industry consortia and standards organizations have worked together to promote the development of the edge computing technology ecosystem. By developing such specifications and reference architectures along with  best practices, companies ensure that the various edge devices, platforms, and applications work collectively.

Such radical advancement of technologies allows companies to control real-time data processing and distributed computing, fostering innovation, efficiency, and effectiveness in modern industry.

As edge computing continues to mature, what specific technological innovations or breakthroughs do you anticipate driving its further development?

Edge Computing development’s next phase will likely see AI and ML integrated directly at the edge, enabling real-time analysis without the need for centralized infrastructure. Driven by Kubernetes frameworks and microservices, there will be an explosion of edge-native applications tailored to the limitations of edge devices. Edge networking will not only improve with the advent of 5G and edge caching but also enhance scalability and performance. In the interim, edge computing developers and firms will push forward standardization to make sure compatibility between edge devices and platforms. These trends will enable organizations to counteract against the rising tide of centralized IT with innovations in efficiency and speed; a reduced latency approach; and, a much more solid basis for data privacy and security. Over the next decade, distributed computing will not be conceivable without the evolution of edge computing, which will enable many new applications and advances.IT will undergo a massive transformation.

Can you discuss any ongoing research or initiatives aimed at overcoming challenges related to scalability, latency, and resource constraints in edge computing environments?

Several efforts, research and initiatives are endlessly attempting scalability, latency, and resource constraint challenges in edge computing. Various  studies lay emphasis on evolving suitable architectures and algorithms to augment resource utilization and scalability. These include lightweight data processing techniques designed for edge devices, which have limited heat dissipation capacity due to their small processors. Latency is further reduced through edge caching, which stores frequently accessed data and applications closer to end-users, enabling quicker retrieval. Moreover, 5G allows with high-speed, low-latency communication between edge devices and modems, improving overall fulfilment.

How do you see edge computing architectures evolving to accommodate the increasing diversity and complexity of connected devices and applications?

With the growing diversity and intricacy of connected devices and applications, edge computing architectures are likely to take on multiple new forms to address them better. Increased flexibility and scalability will ratify the course of including a larger variety of devices and applications and this might lead to the establishment of modular and decentralized architectures that can support easier integration and management of an increased variety of edge resources. New edge orchestration and management technologies will abridge edge environments’ supply distribution and dynamic scaling activities based on the demands of connected hardware and applications diminish complexity and enable optimal performance and scalability of edge environments in a complex setting.

What role do you believe standards bodies and industry consortia play in shaping the development and adoption of interoperable edge computing solutions?

Standards bodies and industry consortia play a crucial role in shaping the development and adoption of interoperable edge computing solutions. Their contributions include:

Establishing Common Frameworks and Protocols: Standards bodies create universally accepted frameworks and protocols to ensure that different edge computing solutions can work together seamlessly which is important for extensive adoption and incorporation across many industries.

Ensuring Compatibility: By defining technical standards, these organizations ensure that hardware and software from different vendors can communicate and function together. In turn this compatibility reduces market fragmentation and fosters a cohesive ecosystem for edge computing solutions.

Driving Adoption and Market Growth: By providing clear guidelines and certifications, standards bodies help build trust among businesses and consumers. This not only builds trust encouraging more companies to invest in but also  adapting edge computing solutions there by driving market growth.

Enhancing Security and Compliance: Establishing security standards and compliance frameworks is vital for protecting data and ensuring privacy in edge computing environments. Standards bodies develop and enforce these guidelines, helping companies maintain strong security practices.

Facilitating Regulatory Alignment: Standards bodies often work with regulatory authorities to align industry standards with legal requirements. This alignment ensures that edge computing solutions comply with regional and international regulations, simplifying the deployment process for global companies.

Providing Educational Resources and Training: Industry consortia offer training programs, workshops, and educational resources to help organizations understand and implement edge computing standards. This support aids in building a skilled workforce capable of leveraging edge computing technologies effectively.

In terms of software development, what are some best practices for designing and deploying applications in edge computing environments, particularly in industries with stringent regulatory requirements such as healthcare and finance?

Industries with high regulatory pressure, including healthcare and finance, also need to follow several best practices when designing and deploying applications in edge computing environments. To guarantee compliance, security, and reliability, the following practices are recommended: 

· Data Encryption and Security: - It is suggested to use strong encryption methodologies to guarantee data protection when being transmitted and stored. Secure communication protocols and cryptographic algorithms must be used to guarantee information integrity and secrecy.

· Compliance with regulatory Standards: - Ensure that your applications are compliant with industry-specific regulatory standards and requirements like HIPAA in healthcare or PCI DSS in finance. 

· Data Residency and Sovereignty: - When building edge computing applications, you should also consider local data residency and sovereignty requirements. For highly regulated industries, ensure that data processing and storage are in accordance with local regulations on data residency and cross-border data transfers. Implement data localization and jurisdiction capability to support legal compliance and mitigate legal risk.

· Redundancy and Fault Tolerance: Design highly available and reliable applications with redundancy and fault tolerance. Redundancy occurs at the hardware level, when multiple instances exist to prevent single-point failure, and is also achieved at the software level. Use techniques such as load balancing, failover clustering, and data replication. Resilient edge architectures should be designed so that they can be immune to network failures, hardware failures, and other disruptions compromising on service availability and data integrity.  

·  Monitoring and Compliance Auditing: Implement robust monitoring and auditing mechanisms to monitor the application performance, incident security, and regulatory violations in real-time. Use logging monitoring and auditing tools to detect anomalies or threats, specify what to look for, and ensure compliance with standards. Run compliance audits and assessments on a regular basis to maintain compliance with regulatory standards.

How do you envision the development of edge computing ecosystems and partnerships evolving to foster collaboration among technology providers, service providers, and end-users across different sectors?

Edge computing ecosystems- both within and beyond industrial edge- across technology providers, service providers in various industries, and end-users will continue to drive collaboration. The extent of collaboration will expand with more strategic alignment, joint ventures, and its statement among ecosystems to co-innovate edge solutions that resonate with industry-specific requirements. This requires even closer integration of hardware, software, and service providers to offer edge offerings that simplify industry use cases while addressing a wide range of concerns. Industry-specific consortia and standards-working groups will also expand to spread best practices and standards, all governed by an entity ecosystem of technology providers, service providers, and end-users who collaborate to innovate and support the best of edge across these industries.

Can you share any examples of innovative edge computing use cases or pilot projects currently underway in industries beyond telecom and IoT? What lessons have been learned from these initiatives?

Apart from telecom and IoT there are the other cool edge computing projects that are bringing some great innovative solution to different industry. For an example, in the healthcare sector/ field we are seeing some new services for real time monitoring of patients which can lead to better care and fewer hospital reengagement. And in retail, it also personalized the shopping experience and targeted promotions, because of edge computing. One of the important factors is like data privacy, security, and the robust infrastructure.

One of the most critical and evolving applications of edge computing is in national defense systems around the world. Countries like India, Israel, the United States, various European nations, and Japan are increasingly incorporating edge computing technologies into their military strategies, particularly in (UAVs), commonly known as drones. The data collected by these drones—which includes video feeds, sensor data, and communication intercepts—is processed at this master edge before being transmitted to core data centers. This technique radically decreases the bandwidth needed for data transmission and fast-tracks the overall speed of data processing. A standout example of edge computing's effectiveness in defense was recently demonstrated by Israel. During an assault where multiple drones and missiles were launched towards its territory, Israel successfully intercepted and neutralized these threats using its advanced edge computing-enabled defense systems which highlights the tactical benefit in real-time threat analysis and intervention.

Statistics indicate that the global market for military drones is expected to grow significantly, with projections suggesting a market size of over $21 billion by 2026, from $13 billion in 2020, at a CAGR of 8.2% during the forecast period. This is a result of enhanced integration of edge computing into these systems, increasing their operational efficacy and success. In the future the acceptance of edge computing in defense will expand with more sophisticated applications being developed and these developments are expected to include independent swarms of drones that can operate collaboratively through edge computing, additionally enhancing situational awareness and response capabilities in military operations.