## 1 Introduction  
Thanks to the rapid advances in the WSN domain (e.g., miniaturization of WSN nodes), Precision Agriculture (PA, also called precision farming in certain contexts) has started to emerge as a new trend in the agricultural sector in the past few years. Generally speaking, a PA system concentrates on providing ways for observing, assessing and controlling agricultural production processes, and covers a wide range of uses from herd management to field crop production [1]. For example, the site-specific crop monitoring application involves numerous different issues. One of them is environmental data collection, such as monitoring soil, crop and climate in one/multiple fields, which are separated by parcels. Furthermore, a Decision Support System (DSS) can use these sensory data for promising treatments analysis of a whole field or a specific parcel. Meanwhile, different actions can be carried out under the guidance of the analysis results and subsequent monitoring, for instance, adjusting in real-time operations such as fertilizer, lime and pesticide utilization, tillage, or sowing rate [2]. PA and WSN applications combine an exciting new topic of research that will greatly improve quality in agricultural production, water management and at the same time will significantly reduce the cost and environmental impact of agricultural production. We note that a WSN is able to provide precise cultivated field information in real-time, and help reduce resource usage to minimize environmental pollution due to overuse of fertilizers, pesticides, _etc_. Furthermore, the open standardized protocols, the ease of deployment and system maintenance open a door to introduce the next generation of WSN--Internet of Things (IoT) technologies in PA. In addition, the cultivated field sensory data can be also used in supply chain management [3]. Most of the current agro-environmental monitoring applications transmit the real-time data in wireless networks through a M2M (machine to machine) support platform. Some systems utilize SMS, Web, WAP patterns, so that the terminal can receive the information to monitor the production. However, these earlier researches count on composite Web applications on the server side. Thanks to the 6 LoWPAN adaptation protocol [4], smart objects are capable of efficiently connecting to the IPv6-based internet [5]. With the other protocols, such as RPL and Constrained Application Protocol (CoAP) [6], it is hoped they will improve the autonomous capability of the resource-constrained WSN nodes in PA systems, and enhance the performance of the whole network. Therefore, as the development of IETF standardization in the fields of IoT and Web of Things (WoT), their use cases will be not limited in the current applicability coverage (e.g., home automation [7,8], commercial building automation, industrial automation, urban environments [9]), and PA application will become a significant and promising one in the near future. Meanwhile, adoption of IoT technologies in PA applications has to tackle the challenges due to the various constraints of specific WSN nodes, their deployment environment and applications. Thus, the WSN of a PA system is a Low-power and Lossy Network (LLN), and RPL [10] has been considered as a natural solution for routing issues in Agricultural LLNs (A-LLN) in our previous work [11]. According to the ROLL Working Group (WG) charter, RPL is designed as a general widespread use routing protocol, independent from the rest of the protocol stack through proposed self-organization mechanisms-topology structures. However, from the evaluations of [12] and the applicability analysis of [11], the original RPL protocol and its existing implementations cannot meet the Quality of Service (QoS) requirements of real world A-LLNs deployments, such as resource constraints, transmission range, network lifetime, automatic topology adjustment and resistance of highly dynamic environment caused by obstacles, adverse weather or vegetation growth [13].