Computing offloading is a key challenge of new rising computing paradigms of the Internet of Things (IoT) like edge computing, which shifts computations to data sources as near as possible to gain the benefits, such as low latency and energy efficiency. However, the fragmentation problem of IoT devices results in a heterogeneous and disordered ecosystem, hindering the interoperating demands of computing offloading. What we need is an open-enabled ecosystem which allows third-party developers to create and update functions of deployed devices dynamically. We propose Things-representational state transfer (T-REST) which is an extension of the representational state transfer (REST) architectural style to address this problem. It integrates contents and computations together to inherit the uniform interface principle from REST. Three architectural constraints are added to REST: 1) reusable remote evaluation; 2) dynamic time series representation; and 3) computational hypertext. A novel event triggering mechanism is designed to decouple the tight coupling of front-end content accesses and back-end computations for resources. A reference prototype, named T-REST engine, is implemented to verify the proposed architecture with the open-enabled style, distributed semantics, and computing offloading features. Discussions show that T-REST preserves the benefits of REST. In addition, it achieves extremely lightweight footprints and can perform computing offloading through open-enabled architectures.
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