Internet of things (IoT) becomes a prominent technology in our world. It is enabling the connection between the objects (the "things") and the backend systems via the Internet. Everyday objects can become connected and smart. It has been adopted in different areas and applications such as smart cities, smart agriculture, smart healthcare, smart manufacturing, and others. Moreover, IoT platforms are currently growing up into the market. Each platform provides valuable and specific services and features. This paper presents a survey on IoT platforms, discussing their architectures and fundamentals of IoT building elements and communication protocols between them. The aim of this paper is to help the reader choose a suitable and adequate IoT platform for own demands in the huge number and variety of platforms available. This survey provides a comprehensive view of the components and features of the state-of-the-art IoT platforms.
The massive increase in the Internet of Things (IoT) has brought a diverse long-range, low-power, and low bit-rate wireless network technologies. The LoRa a low-power wide area network (LPWAN) gained popularity as radio technology for the realization of many IoT applications. LoRa is typically employed together with LoRaWAN MAC protocol and operates in the license-free ISM bands. LoRa networks have an issue with scalability when the number of end nodes connected to one network is larger than the shared number of channels, that causes a collision and packets loss through receiving a wide range of different message sizes from various application. In this paper, we describe an accurate and efficient way confirmed by simulation to calculate the probability of collision rate and packet loss in LPWANs under various circumstances. Moreover, based on the LoRaWAN specification, we consider a dense network deployment of IoT devices. In the event of collisions, our proposed algorithms is classified to two approaches. Firstly a time scheduling algorithm is proposed for LoRaWAN networks that consist of devices supporting LoRaWAN class C mode for synchronization in the beginning between the gateway and the end nodes. Afterwards these devices switch to class A to significantly decrease the collision and to enhance scalability by assigning a Guard Time to each end node. Gateway acknowledgment (ACK) messages to the end nodes are used through class C. Secondly, we also propose a distance spreading factor algorithm according to the distance of the end nodes from the gateway to reduce the probability of collision. Furthermore, many of these devices are battery powered, therefore low power consumption is required.
The new era of IoT brings the necessity of smart synergy for diverse communication and computation entities. The two extremes are, on the one hand, the 5G Ultra-Reliable Low-Latency Communications (URLLC) required for Industrial IoT (IIoT) and Vehicle Communications (V2V, V2I, V2X). While on the other hand, the Ultra-Low Power, Wide-Range, Low Bit-rate Communications, such as Sigfox, LoRa/LoRaWAN, NB-IoT, Cat-M1, etc.; used for smart metering, smart logistics, monitoring, alarms, tracking applications. This extreme variety and diversity must work in synergy, all inter-operating/inter-working with the Internet. The communication solutions must mutually cooperate, but there must be a synergy in a broader sense that includes the various communication solutions and all the processing and storage capabilities from the edge cloud to the deep-cloud. In this paper, we consider a non-orthogonal multiple access (NOMA)-based device to device (D2D) communication system coexisting with a cellular network and utilize Greedy Asynchronous Distributed Interference Avoidance Algorithm (GADIA) for dynamic frequency allocation strategy. We analyze a max–min fairness optimization problem with energy budget constraints to provide a reasonable boundary rate for the downlink to all devices and cellular users in the network for a given total transmit power. A comprehensive simulation and numerical evaluation is performed. Further, we compare the performance of maximum achievable rate and energy efficiency (EE) at a given spectral efficiency (SE) while employing NOMA and orthogonal frequency-division multiple access (OFDMA).
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