Open Access

ARTICLE

Middleware for Internet of Things: Survey and Challenges

by

^a Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint AbdulRahman University, Riyadh, Kingdom of Saudi Arabia;
^b College of Computer and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Kingdom of Saudi Arabia;
^c Department of Mathematics, Faculty of Science, Cairo University, Giza, Egypt

* Corresponding Author: Samia Allaoua Chelloug,

Intelligent Automation & Soft Computing 2018, 24(2), 309-318. https://doi.org/10.1080/10798587.2017.1290328

Abstract

The Internet of things (IoT) applications span many potential fields. Furthermore, smart homes, smart cities, smart vehicular networks, and healthcare are very attractive and intelligent applications. In most of these applications, the system consists of smart objects that are equipped by sensors and Radio Frequency Identification (RFID) and may rely on other technological computing and paradigm solutions such as M2 M (machine to machine) computing, Wifi, Wimax, LTE, cloud computing, etc. Thus, the IoT vision foresees that we can shift from traditional sensor networks to pervasive systems, which deliver intelligent automation by running services on objects. Actually, a significant attention has been given to designing a middleware that supports many features; heterogeneity, mobility, scalability, multiplicity, and security. This papers reviews the-state-of-the-art techniques for IoT middleware systems and reveals an interesting classification for these systems into service and agent-oriented systems. Therefore two visions have emerged to provide the IoT middleware systems: Via designing the middleware for IoT system as an eco-system of services or as an eco-system of agents. The most common feature of the two approaches is the ability to overcome heterogeneity issues. However, the agent approach provides context awareness and intelligent elements. The review presented in this paper includes a detailed comparison between the IoT middleware approaches. The paper also explores challenges that form directions for future research on IoT middleware systems. Some of the challenges arise, because some crucial features are not provided (or at most partially provided) by the existing middleware systems, while others have not been yet tackled by current research in IoT.

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