Scaling at the Edge: How Edge Computing is Augmenting Data Processing

Edge Computing Market Report Overview

Edge computing is an emerging computing architecture that processes data close to the source with an aim to resolve latency issues for critical applications across sectors. It minimizes the processing and transmission strain on cloud computing centers by reducing the time it takes for users to input data and moving computing capacity to the network’s edge. This can transform various business processes, notably for data-intensive services. The report highlights various innovations with contemporary use cases across the edge computing value chain.

Key Benefits of Edge Computing

Increased resilience: Edge computing improves resilience by eliminating a single point of failure, as is the case with centralized servers where the failure at one edge device will not affect the performance of the other edge devices in the ecosystem, which vastly improves the overall reliability of the connected environment.

Improved efficiency: Edge computing obviates the need for data to be moved from endpoints to the cloud and back. Reducing travel time shortens the entire process as the time saved can be quantified into seconds, and in some cases, milliseconds.

Reduced costs: Although data storage costs have decreased significantly over the last decade or so, the cost of moving data is increasing as its volume grows. Users require greater bandwidth to handle the load at the same time, which increases the cost. By reducing the amount of data moved to and fro the cloud, edge computing can help keep costs under control or at least keep them from increasing very high.

Scalability: Organizations can add edge devices as their use cases broaden, deploying and managing only what they require. Moreover, endpoint hardware and edge devices are generally less expensive than increasing computing resources within a centralized data center. This makes more sense for organizations to scale at the edge.

Enhanced privacy and security: Edge computing can provide enhanced security and privacy protection, as it keeps data close to the edge and away from centralized servers. Moreover, edge devices store only a limited amount of data and frequently and do not contain complete data sets that hackers could exploit.

For more insights on the advantages of edge computing, download a free report sample

Edge Computing Value Chain Framework

The key components of the edge computing value chain are device edge, remote edge, branch edge, enterprise edge, telco/MEC edge, and cloud edge.

Streaming Media Delivery: Amazon Web Services (AWS) has launched ‘Secure Media Delivery at the Edge on AWS’ solution to protect video content from unauthorized access when delivered through the content distribution network (CDN), Amazon CloudFront. It provides an additional layer of protection based on individual access tokens added to the delivery uniform resource locator (URL).

Edge Computing Value Chain Framework

For more insights on the edge computing value chain framework, download a free report sample

Key Challenges of Edge Computing

Distributed computing: Edge infrastructure must always be appropriately sized. For example, distributed compute in a remote micro data center can be just as resource-intensive as distributed compute in a centralized data center.

Data backup: Enterprises require a comprehensive data protection strategy that can grasp data from any location. When deciding how to protect these assets, network bandwidth requirements will be just as important as storage media considerations, since backup over the network may not make sense.

Control and management: Regardless of location, enterprises should ideally use newer orchestration tools to help manage and control applications consistently.

Network bandwidth: As enterprises move to compute and data to the edge, network bandwidth shifts. Conventionally, enterprises allocate more bandwidth to data centers and less to endpoints. Edge computing necessitates a significant increase in network bandwidth

Data aggregation: Data is a critical business asset and collecting them at the edge introduces new challenges and risks if not handled according to existing data handling rules. Data storage and access are important, and both must include the network as part of the data lifecycle.

To understand more about the challenges impacting the edge computing market, download a free report sample

Edge Computing Market Report Overview

Scope

Innovation Insights: innovation examples by each use cases segment of various sectors to present key trends.

Reasons to Buy

• No surprise that technology has been a driving force in business transformation for years, but the term ‘emerging technologies’ has all of the sudden become the key catalyst to drive the next wave of innovation across sectors.
• The sense of urgency weighs differently across different sectors, where the direct customer-facing sectors are at the forefront compared to other capital-intensive sectors. Companies in one sector can take cues from successful innovations in other sectors to either draw analogies with existing products, services, and processes or transfer strategic approaches for a revolutionary transformation.
• Against this backdrop, enterprises need to understand which emerging technologies are impacting their sector and how various companies are implementing them to meet various challenges.
• The innovation landscape report on edge computing, published by GlobalData as part of an ongoing series, covers some real-world examples to advance the development and implementation of the technology across some major sectors.