Council Post: Navigating Challenges in Edge Computing: An Analysis of Key Issues

It is common for the populace to become disinterested in the constant barrage of new technology that promises to transform the personal and commercial world. However, our thorough examination of these critical technological developments confirms that a big change is occurring. The IDC report projects that the global expenditure on edge computing is anticipated to surge to $317 billion by 2026. By 2023, the estimated spending on edge computing is expected to hit $208 billion, marking a significant 13.1% rise from the 2022 expenditure.

While identifying technology trends has been a topic of extensive discussion, the repercussions of these transformations have often been overlooked. Whilst edge computing has become an essential tool for improving data processing and cutting latency, it is not without its challenges. We face enterprise challenges when finding effective edge computing solutions, from network problems to security concerns. 

As industry insiders, we possess a comprehension of the necessary adaptations in management over the next three to five years as a response to the evolving technological landscape. We aim to examine plausible scenarios, consequences, and proactive strategies for these changes.

Security and Privacy

The rapid evolution of edge computing technology is introducing numerous customer touchpoints and a vast influx of customer data, elevating the significance of trust in the IT sector. As edge computing transforms and expands its role, it becomes critical to ensure robust security, privacy, and cybersecurity. While consumers appreciate the convenience of edge computing, their awareness of privacy, trust, and ethical data usage, especially with the escalating data volumes at the edge, is growing. Key challenges include:

• Navigating complex personal data collection.
• Addressing security risks in edge-driven environments.
• Understanding intricate analytics.

The doubts surrounding edge computing stem from past data breaches that have exploited personal devices, highlighting significant digital privacy concerns. Even seemingly secure devices like iPhones have been leveraged for remote tracking, exposing vulnerabilities. Spyware like Pegasus has surreptitiously infiltrated devices, serving as back doors for clandestine data collection.

Given edge computing’s involvement in compromising public privacy, is it a viable choice for businesses? The risk extends beyond individual privacy to encompass broader datasets, raising doubts about its safety for business purposes.

To tackle these hurdles effectively, businesses must integrate identity and trust management into their core edge computing strategies, appoint dedicated leaders, and prioritize trust and security at the board level. It plays a pivotal role in monitoring and mitigating concerns in this intricate scenario, encompassing legal implications, incident tracking, governance of high-risk data processing, and ongoing assessment of consumer trust in edge computing.

Edge computing, much like any groundbreaking technology, necessitates immediate implementation. Regulatory bodies globally harness edge technologies for law enforcement, such as scanning vehicle registration numbers, accessing live dashboard camera feeds, and utilizing indoor surveillance systems for asset monitoring.

To counteract the challenges that emerge from such widespread deployment, companies are swiftly developing patches and fixes to address emerging issues. However, this reactive approach often leads to bottom-level impacts before remedies are available.

In this context, centralized orchestration and management are crucial solutions for bolstering edge computing security and ensuring effective maintenance across numerous devices.

Network Bandwidth and Technological Change:

Network challenges in edge computing are significant, as this technology relies on robust network infrastructure. Key issues include latency, bandwidth limitations, and connectivity problems, particularly in remote areas. 

Bandwidth denotes the volume of data that a network can transmit within a specific period, commonly measured in bits per second. Every network operates within a finite bandwidth capacity, with wireless communication facing more stringent limitations. This constraint signifies a capped threshold for the volume of data or the number of devices capable of exchanging information across the network. While enhancing network bandwidth to accommodate additional data and devices is plausible, this solution poses significant cost implications and only resolves other underlying issues despite extending finite limits.

Overcoming these challenges involves investments in edge-specific network solutions, network optimization, and efficient data routing techniques. Additionally, ensuring interoperability among edge devices from different manufacturers is a challenge, and organizations must carefully select devices and platforms that support seamless integration. 

Edge computing proves invaluable in scenarios where connectivity faces unreliability or bandwidth constraints due to environmental factors at a specific site. This includes settings like oil rigs, sea vessels, remote farms, or isolated locations such as rainforests or deserts. Here, edge computing conducts computations on-site or directly on the edge device, like water quality sensors on remote water purifiers in villages. This approach allows data to be stored locally and transmitted to a central hub only when connectivity is accessible. The shared data volume significantly diminishes by processing data at the edge, increasing the bandwidth and connectivity time required compared to conventional methods.

Scalability and Management in Manufacturing

Edge computing environments are complex, with numerous distributed devices, making scalability and management challenging. Organizations should invest in specialized edge management platforms to address these issues and adopt scalable architectures that adapt to growing needs. Managing distributed edge infrastructure requires specific knowledge and skills in network configurations, security, and remote device management. Continuous monitoring and automation help streamline resource management. Effective management and scalability are essential for unlocking the full potential of edge computing, requiring organizations to allocate resources for training and strategic investments in technology.

Predictably, the pace of technological change will continue to accelerate. Edge Computing significantly changes how data is handled, and applications are rolled out. Its potential to reduce latency, maximize bandwidth utilization, support data privacy, and improve dependability makes it a disruptive force in various industries. With the continuous evolution of technology, we can expect to see more innovative applications and solutions that reshape the digital landscape, fostering enhanced efficiency and responsiveness in our interconnected society. Indeed, edge computing represents the optimal approach for effective data processing in the future, and its advancements are still in their infancy. 

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here.

Srikanth is currently working with Bajaj Auto Consumer Financial as chief of digital and technology, is a technologist with rich experience in identifying and building consensus for enabling technologies that facilitate business priorities, processes, and strategic objectives. Working experience in multinational, global corporations and India-based enterprises -prominent organizations worked Microsoft, GE, IBM, Majoris, and listed companies BFIL Ltd (merged with IndusInd) and co-founding experience ASAP-Tech consulting, with wide domain experience in BFSI services (NBFC inclusive, FinTech, Neo Banking)  Software product & platform, Supply chain & Global Delivery