International Workshop on Trustworthy & Real-time Edge Computing for Cyber-Physical Systems
A B O U T T R E C 4 C P S
The increasing proliferation of Internet of Things (IoT) is giving rise to an ever-increasing volume of data that is being generated by the IoT sensors that reside at the edge of the network. Of specific interest to us are IoT applications found in cyber-physical systems where the streamed information must be processed in real-time to make informed decisions for a wide range of societal and environmental applications. For instance, emergency response systems and smart transportation systems are prime examples of multi-domain smart and connected community applications residing at the edge of networks. The term Tactile Internet has also been used to refer to these systems. Conventionally, such systems have been implemented using centralized architectures. However, as the scale and penetration of these data driven applications in the communities are growing, the challenges of these architectures become apparent; for example, the lack of scalability, the existence of single points of failure, and saturated communication resources. Moreover, the sporadic and uncertain arrival patterns for the IoT data streams complicates real-time stream processing because resources must be provisioned on-demand to fuse multiple temporally-unsynchronized data streams. Second, the temporally sensitive nature of the data, the resource constraints on IoT devices, and the large volumes of generated information make it problematic to always move these information streams to a centralized cloud data center that may be multiple network hops away with fluctuating bandwidths and hence the incurred delays, which is detrimental to the cyber physical systems.
To address these issues, the community has been moving towards distributed edge computing solutions that promise to enable city-scale, extensible smart systems that make the best use of available information, network resources, and computing resources, including cloud computing resources. In edge-centric deployments, effective app and system management is critical due to the need to add/remove resources seamlessly, handle failures gracefully, and upgrade/reconfigure distributed applications. Addressing these challenges requires elastic and on-demand, distributed multi-resource provisioning and management. Existing resource management solutions, however, tend to focus on provisioning only one type of resource at a time but seldom consider the problem holistically.
Furthermore, the problem of the trustworthiness of analysis results is becoming an important consideration. Lack of effective assurance mechanisms have brought us to the current reality that includes susceptibility to data integrity attacks and information leakage attacks as shown by a large number of recent incidents even in centralized information flows. The problem is expected to be much worse for resource-constrained edge information flow structures. Effective strategies will have to study trade-offs between security, privacy, trust levels, resources, and performance. Additionally, we urgently require comprehensive exemplar applications and data cases that show how these problems are being studied by industry and the research community.