Indoor Positioning Systems (IPS) using Bluetooth Low Energy (BLE) technology are currently becoming real and available, which has made them grow in popularity and use. However, there are still plenty of challenges related to this technology, especially in terms of Received Signal Strength Indicator (RSSI) fluctuations due to the behaviour of the channels and the multipath effect, that lead to poor precision. In order to mitigate these effects, in this paper we propose and implement a real Indoor Positioning System based on Bluetooth Low Energy, that improves accuracy while reducing power consumption and costs. The three main proposals are: frequency diversity, Kalman filtering and a trilateration method what we have denominated “weighted trilateration”. The analysis of the results proves that all the proposals improve the precision of the system, which goes up to 1.82 m 90% of the time for a device moving in a middle-size room and 0.7 m for static devices. Furthermore, we have proved that the system is scalable and efficient in terms of cost and power consumption. The implemented approach allows using a very simple device (like a SensorTag) on the items to locate. The system enables a very low density of anchor points or references and with a precision better than existing solutions.

MQTT-S and CoAP are two protocols able to use the publish/subscribe model in Wireless Sensor Networks (WSNs). The high scalability provided by the publish/subscribe model may incur a high packet loss and therefore requires an efficient reliability mechanism to cope with this situation. The reliability mechanism of MQTT-S and CoAP employs a method which defines a fixed value for the retransmission timeout (RTO). This article argues that this method is not efficient for deploying publish/subscribe in WSN, because it may be unable to recover a packet, therefore resulting in a lower packet delivery ratio (PDR) at the subscriber nodes. This article proposes and evaluates an adaptive RTO method, which consists in using a Smooth Round-trip Time and multiplying it by a constant parameter (K). Thanks to this method, the reliability mechanism of MQTT-S and CoAP would be able to react properly to packet loss and would also be lightweight in terms of energy, memory and computing for sensor nodes where these resources are critical. We present a detailed evaluation of the effects of the K value on the calculation of the adaptive RTO method. We also establish the setting for obtaining the highest PDR on the subscriber nodes for single-hop and multi-hop scenarios. The results for single-hop scenario show that use of the appropriate K value for the adaptive RTO method increases the PDR up to 76% for MQTT-S and up to 38% for CoAP when compared with the use of fixed RTO method for both protocols, respectively. Meanwhile the same comparison for multi-hop scenario, the adaptive RTO method increases the PDR up to 36% for MQTT-S and up to 14% for CoAP.

Since the appearance of 5G, Internet of Things (IoT) has gained an increased interest, with multiple technologies emerging and converging to cover different user needs. One of the biggest challenges today is to have global IoT coverage, ensuring seamless communication with IoT devices placed in rural and even remote areas. Satellite constellations, and in particular CubeSats orbiting in Low Earth Orbit, can provide a solution to these challenges. Out of the technologies available, LoRa (Long Range) has a great potential for implementation in space-to-Earth satellite communications. As the space-to-Earth channel is different with respect to the conventional Earth-to-Earth one, it is important to asses the capabilities of LoRa in this new environment. This paper presents a study of different LoRa device configurations to identify the constrains for each one and determine which one is better for particular mission requirements. Also, the effect of ionospheric scintillation is assessed with a SDR-based (Software-Defined Radio) test setup that evaluates the performance of this technology against with Humprey's ionospheric scintillation model. This phenomena produces deep signal intensity fadings and phase fluctuations in equatorial regions, and mainly phase fluctuations in high latitudes. The obtained metrics are the received power and the packet delivery ratio as a function of the intensity scintillation index, and show the robustness of the LoRa modulation in these new environments.

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Wireless Sensor Networks (WSNs) are attracting more and more interest since they offer a low-cost solution to the problem of providing a means to deploy large sensor networks in a number of application domains. We believe that a crucial aspect to facilitate WSN diffusion is to make them interoperable with external IP networks. This can be achieved by using the 6LoWPAN protocol stack. 6LoWPAN enables the transmission of IPv6 packets over WSNs based on the IEEE 802.15.4 standard. IPv6 packet size is considerably larger than that of IEEE 802.15.4 data frame. To overcome this problem, 6LoWPAN introduces an adaptation layer between the network and data link layers, allowing IPv6 packets to be adapted to the lower layer constraints. This adaptation layer provides fragmentation and header compression of IP packets. Furthermore, it also can be involved in routing decisions. Depending on which layer is responsible for routing decisions, 6LoWPAN divides routing in two categories: mesh under if the layer concerned is the adaptation layer and route over if it is the network layer. In this paper we analyze different routing solutions (route over, mesh under and enhanced route over) focusing on how they forward fragments. We evaluate their performance in terms of latency and energy consumption when transmitting IP fragmented packets. All the tests have been performed in a real 6LoWPAN implementation. After consideration of the main problems in forwarding of mesh frames in WSN, we propose and analyze a new alternative scheme based on mesh under, which we call controlled mesh under.