Many researchers employ IEEE802.15.4 as communication technology for wireless sensor networks (WSNs). However, medium access control (MAC) layer requirements for communications in wireless sensor networks (WSNs) vary because the network is usually optimized for specific applications. Thus, one particular standard will hardly be suitable for every possible application. Two general categories of MAC techniques exist: contention based and schedule based. This paper explains these two main approaches and includes examples of each one. The paper concludes with a unique performance analysis and comparison of benefits and limitations of each protocol with respect to WSNs.

Low-Power Wide-Area Network technologies allow sending sensor information through long distances with low data rates. LoRa is one of these technologies, which is less susceptible to noise and interference. This technology operates in unlicensed bands, increasing the chances of having interfering devices in the communication link. The issue of LoRa jamming with external interference and the effect of such interference in radio range has not been addressed in the literature. Therefore, tests measured packet loss, received signal strength, and signal to noise ratio with one end node located kilometers away from a gateway. Data was measured with and without external interference, to establish system robustness. The paper computes an empirical model of the Immunity Region, where the level of interference does not affect LoRa communication. Results show that LoRa devices required interference levels up to 14 dBm to have total packet losses. These results are relevant for implementing LoRa systems, motivating researches to perform site surveys of interference and to account for range reduction in network design.

LoRa is a wireless technology for the Internet of Things useful for smart city applications that require node location for monitoring or management. The literature presents multiple surveys for localization in wireless networks but not a comprehensive analysis regarding LoRa localization. Therefore, this article presents different localization techniques along with the metrics employed. Then, this article presents the challenges that the LoRa technology faces when using these techniques and possible solutions from the literature. Next, this article presents a comparative analysis of the reviewed works with unresolved issues. The results reveal that systems using time as a localization metric exhibit smaller localization error than those using signal levels. However, each method was tested under different conditions. Hence, this article is useful for comparing and selecting a localization system for LoRa in a given work scenario.

Long-range wide-area network (LoRaWAN) technology can be a good candidate for industrial applications in the Internet of Things and adaptive data rate (ADR) algorithms help to improve LoRaWAN performance. These algorithms compute a link budget to define the data rate and the transmission power. However, the performance of these algorithms must be evaluated in industrial environments that pose challenging conditions to wireless communications due to obstacles, interference, and movement. Therefore, this article compares the performance of LoRaWAN with six different ADR algorithms using a realistic propagation model from an industrial environment. This research uses the framework for LoRa (FLoRa) environment in objective modular network testbed in C++ (Omnet++) to compare the packet delivery ratio and energy consumption with different gateway locations and data traffic. Results show that the algorithms that decrease the link budget in poor channel conditions have better performance in industrial scenarios. Furthermore, overestimating the channel behavior decreases packet delivery.

The energy consumption rate for sensors in a wireless sensor network vary greatly depending on the protocols the sensors use for communication. The gossip-based sleep protocol (GSP) (X. Hou et al., 2004) is an example of a protocol that implements routing and some MAC functions in an effort to conserve energy. Simulations show that GSP can conserve energy. We expand on this effort by building a prototype system and measuring energy consumption rates. GSP was implemented on the Mica2 platform and measurements were conducted to determine energy consumption. The measurements were then used to build an energy consumption model for GSP

One of the biggest problems with distribution systems correspond to the load unbalance created by power demand of customers. This becomes a difficult task to solve with conventional methods. Therefore, this paper uses integer linear programming and Branch and Bound algorithm to balance the loads in the three phases of the distribution system, employing stored data of power demand. Results show that the method helps to decrease the unbalance factor in more than 10%, by selecting the phase where a load should be connected. The solution may be used as a planning tool in distribution systems applied to installations with systems for measuring power consumption in different time intervals. Furthermore, in conjunction with communications and processing technologies, the solution could be useful to implement with a smart grid.