The State of Edge Computing Research: An Overview of Current Developments
An Overview on Edge Computing Research
Edge computing is a paradigm that aims to bring computation and data storage closer to the sources of data, such as sensors, devices, and users, in order to reduce latency, bandwidth consumption, and energy consumption. Edge computing can enable new applications and services that require real-time processing, context-awareness, privacy preservation, and scalability.
In this blog post, we will provide an overview of the main challenges and opportunities in edge computing research, as well as some of the recent advances and open problems. We will focus on four aspects: edge architecture, edge resource management, edge security and privacy, and edge applications.
Edge Architecture
The edge architecture defines the physical and logical components of the edge computing system, such as the edge nodes, the edge network, the edge cloud, and the interfaces between them. The edge nodes are the devices that perform computation and storage at the edge of the network, such as smartphones, tablets, laptops, IoT devices, drones, vehicles, etc. The edge network is the communication infrastructure that connects the edge nodes with each other and with the edge cloud. The edge cloud is the collection of servers and data centers that provide centralized computation and storage services for the edge nodes. The interfaces between the edge nodes, the edge network, and the edge cloud are the protocols and standards that enable data exchange and coordination among them.
One of the main challenges in edge architecture is how to design a scalable, reliable, and efficient system that can handle the heterogeneity, dynamism, and resource constraints of
the edge nodes and the edge network.
Some of the research topics in this area include:
- How to discover, register, and manage the availability and capabilities of the edge nodes?
- How to partition and distribute the computation and storage tasks among the edge nodes
and the edge cloud?
- How to optimize the communication performance and cost between the edge nodes and the edge cloud?
- How to enable interoperability and compatibility among different types of edge nodes and edge clouds?
- How to support mobility and migration of the edge nodes and their data?
Edge Resource Management
The edge resource management deals with how to allocate and utilize the computation and storage resources of the edge nodes and the edge cloud in order to meet the quality of service (QoS) requirements of the edge applications. The QoS requirements can include latency, throughput, accuracy, reliability, availability, etc. The resource management also involves how to balance the trade-offs between performance, cost, energy consumption, and environmental impact.
One of the main challenges in edge resource management is how to cope with the uncertainty and variability of the resource availability and demand at the edge. Some of the research topics in this area include:
- How to model and predict the resource availability and demand at the edge?
- How to schedule and orchestrate the computation and storage tasks at the edge?
- How to monitor and adapt to the resource utilization and QoS at the edge?
- How to coordinate and cooperate among multiple edge nodes and multiple edge clouds?
- How to leverage machine learning and artificial intelligence techniques for resource management at the edge?
Edge Security and Privacy
The edge security and privacy addresses how to protect.
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