A service typically implements a set of distinct features or functionality, such as connectivity management, vertical application, etc. Instead of building a single monstrous, monolithic application, the idea is to split your application into set of smaller, interconnected services. EIS enables local IoT networks to perform edge intelligence to maximize energy efficiency, reduce privacy threats, easy implementation, modularization(containerized) and minimize latencies.ĮIS adopted the Microservice Architecture pattern. Data that is less time sensitive is sent to the cloud for historical analysis, big data analytics, and long-term storage.Īdvantech EIS adopts the Edge computing Architecture for IoT gateway solution. Time-sensitive data in an edge computing may be processed at the point of origin by an intelligent device or sent to an intermediary server located in close geographical proximity to the client.
Edge computing is a distributed information technology (IT) architecture in which client data is processed at the periphery of the network, as close to the originating source as possible. In some cases, it is much more efficient to process data near its source and send only the data that has value over the network to a Cloud center. Transmitting massive amounts of raw data over a network puts a tremendous load on network resources. IoT data can be large in terms of volume and the applications typically have real-time requirements.
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One the first challenges that many companies face is how to migrate to an IoT application while balancing design time, time to market, and risk. To develop an IoT product will cover various technical fields include: Sensor, Connectivity, Secure, Cloud, Storage, device maintenance, Edge/Cloud Analytics, System Integration, Device Hardware, and Application development, and so on. This page introduces Advantech Edge Intelligence Server (EIS) for Internet of Things gateway solution.
2.3.2.1 WISE-PaaS/EnSaaS Management Portal.
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