Linguistic Abstractions for Interoperability of IoT Platforms

Abstract

The Internet of Things (IoT) advocates for multi-layered platformsfrom edge devices to Cloud nodeswhere each layer adopts its own communication standards (media and data formats). While this freedom is optimal for in-layer communication, it puzzles cross-layer integration due to incompatibilities among standards. Also enforcing a unique communication stack within the same IoT platform is not a solution, as it leads to the current phenomenon of IoT islands, where disparate platforms hardly interact with each other. In this paper we tackle the problem of IoT cross-layer and cross-platform integration following a language-based approach. We build on the Jolie programming language, which provides uniform linguistic abstractions to exploit heterogeneous communication stacks, allowing the programmer to specify in a declarative way the desired stack, and to easily change it, even at runtime. Jolie currently supports the main technologies from Service-Oriented Computing, such as TCP/IP, Bluetooth, and RMI at transport level, and HTTP and SOAP at application level. We integrate in Jolie the two most adopted protocols for IoT communication, i.e., CoAP and MQTT. We report our experience on a case study on Cloud-based home automation, and we present high-level concepts valuable both for the general implementation of interoperable systems and for the development of other language-based solutions. 1 Introduction The Internet of Things (IoT) advocates for multi-layered software platforms, each adopting its own media protocols and data formats [1, 2, 3]. The problem of integrating layers of the same IoT platform, as well as dierent IoT vertical solutions, involves many levels of the communication stack, spanning from linklayer communication technologies, such as ZigBee and WiFi, to application-layer protocols like HTTP, CoAP [4, 5], and MQTT [6, 7], reaching the topmost layers of data-format integration [8]. Technology-wise, architects of IoT platforms can choose between two approaches at odds. The rst approach favors optimal in-layer communications, i.e., choosing media protocols and data formats best suited for the interactions happening among homogeneous elements, e.g., edge devices (connectionless protocols and binary data formats [3]), mid-tier controllers (gateways and aggre

A Systematic Review on the Data Interoperability of Application Layer Protocols in Industrial IoT

“…Moreover, a research study [36] performs integration of IoT devices using Application Protocol Abstraction Layer (APAL) offering event consumer and dispatching facilities for incoming and outgoing messages. Similarly, [37] implements Jolie for IoT (JIoT) that is a javabased programming language to enable IoT cross-layer and cross-platform communication possible.In [38], integration is performed with the help of the Software Defined Network (SDN) as discussed in section II-B. Generally, interoperability has its own issues which involves cost, overhead, scalability and security.…”

“…From these research studies, it is also analyzed that incoming data towards IoT application layer protocols are either stored in cloud or server for further processing. In six (6) research papers [10], [30], [33], [36], [37] and [38], the cloud is used to store data because here, the data is locally processed in a centralized manner to enable decision making. Cloud is frequently used to store and process the data for IoT devices because it is secure and cost effective than other approached used.…”

“…Other hardware platforms are also mentioned in Table 8. Four research studies [33], [37], [44] and [49] have used Arduino as a micro-controller for mostly client services. When Arduino is used as client it selects and implement the lightweight protocol.…”

Ephemeral data handling in microservices with Tquery

“…( Montesi, 2016 ). Jolie instructions can further be composed in workflows ( Gabbrielli, Giallorenzo & Montesi, 2014 ); a feature that simplifies the programming of data collection and distribution in IoT and edge environments ( Gabbrielli et al, 2019 ).…”