Wireless sensor networks (WSNs) consist of a large number of sensor nodes which communicate via wireless links for monitoring applications. In several applications, such as the monitoring of pipelines or roads, the network topology is linear. This type of WSN is called linear sensor network (LSN). Our goal is to improve the behavior of a MAC protocol for LSNs, by using a token approach. As usual, the possession of the token grants the node permission to transmit on the medium during a given amount of time. The payload of the token is used to propagate network parameters such as delay between tokens, sleep and wakeup calendar. In this paper, we study the behavior of this MAC protocol and we evaluate the impact of the node position on the packet delivery for two types of LSNs.
In Senegal, agriculture has always been seen as the foundation on which the socioeconomic development of the country rests. However, in the rural world, agriculture remains traditional at a time when the challenges of food self-sufficiency to accompany emergence are launched. In the southern part of Senegal commonly called Casamance, the abundance of rain makes it possible to practice rice cultivation and market gardening research must therefore play a leading role in the introduction of technological innovations, techniques, and decision-support tools to promote productive, competitive, and sustainable agriculture. Therefore, smart agriculture must focus on new solutions for water irrigation, soil quality, and culture monitoring. The emergence of the Internet of Things (IoT) is perceived as a very important lever for successful high-end intelligent agriculture. Indeed, the appearance of increasingly specialized monitoring sensors combined with new wireless communication technologies constitutes good decision-making tools.
The proposal of this paper consists of a new network architecture that can cover a large cultivation area to carry out water irrigation techniques in Casamance. It is, therefore, a question of identifying the best communication technology among new Low-Power, WideArea Networks (LPWANs) such as Long-Range (LoRa), SigFox, etc which is suited to the environment considered. Also, the choice of the best deployment of sensors for better coverage. The choice of technology must be motivated by the financial costs and the range of transmission. The deployment must fix the optimal distance between the sensors minimizing the interferences according to some parameters specific to the environment. An analytical study is used on the deployment to determine the optimal distance between two gateway nodes to reduce induced interference.
Summary
Wireless sensor networks (WSNs) have received a lot of attention from both academia and industry due to the increasing need for ubiquitous computing for monitoring applications, the continuous advances in miniaturization of electronic devices, and the ultra‐low‐power wireless technologies. These innovations in technology have driven the curiosity to use sensor networks in a new kind of applications such as road track or railway monitoring, border monitoring, oil and gas, or even water pipeline monitoring. Due to the underlying linear topology of these applications, a new type of network, called a linear sensor network (LSN), has emerged. Because of the specific characteristics of this application and the resource constraints of sensors, some of the major challenges faced in LSNs are to reduce end‐to‐end delays, to maximize the packet delivery ratio to a sink, and an even distribution of the load between nodes. To achieve these objectives, it is necessary to control node‐to‐node packet traffic conditions and to manage radio interference created by simultaneously active nodes. This paper addresses these challenges and proposes a new method of clustering LSNs that reduces or controls radio interference risks in order to satisfy these objectives, application needs, and the resource limitations of sensor nodes in the best possible way. This method is applied for LSNs using a token‐passing mechanism to access the medium. The performance evaluation is conducted by using a realistic propagation model in the analytical evaluation and also a NS‐2 simulation process.
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