## 1 Introduction  
Wireless Sensor Networks (WSN) have been considered during the last decades, as a result of wireless communication that has been in use since 1990 [1,2]. WSN have been developed for different applications, such as environmental monitoring, military projects, automobile tracking, human monitoring or medical management [3-6]. A WSN is a wireless network formed by a large number of sensors, including thermal, pressure or accelerator sensors, to name a few. These sensors can sense and detect the environmental statistics, including temperature, pressure, movement, _etc._[7]. Within the network, the sensors are referred to as nodes. Low cost, large-scale, and low power sensors are some of the main reasons to deploy wireless communication technology to sensor networks. Assuming that a node does not have any information about neighboring nodes and the overall topology of the network before its deployment, the node therefore needs to go through an initial self-organization phase. This self-organization causes nodes to be aware of the neighbors and other criteria of the network, which will subsequently be used in the routing procedure. There are three kinds of routing protocols: data-centric, hierarchical, and location based routing protocols [8]. In data-centric routing, the data that is generated by one node is stored in another node determined by the name of the data. One of the primary requirements in sensor networks is the design and development of an energy efficient routing protocol. Minimizing power consumption is another important attribute of routing algorithms in WSN. Nevertheless, network lifetime is the most useful attribute of a routing method's performance. Some routing algorithms, including the Dynamic Source Routing (DSR) [9] and the Hierarchical routing [10], have been proposed for wireless networks. While these algorithms can be applied in traditional wireless networks, they cannot be used in sensor networks: disagreements between both types of networks are the principal reason for this incompatibility [11,12]. Further differences are the size of the networks, the node capacity, and the communication patterns. Most of the previous routing protocols use the global information of a network to route data packets from sensor nodes to the base station, hence generating much more extra packets. The traffic load and the total energy consumption of these networks are high. This leads to a reduction of the network life, incomplete transmissions of data packets to the base station, and delays in forwarding data packets to the base station. We here propose an inferential routing protocol called _Static Three-Dimensional Fuzzy Routing based on the Receiving Probability_ (SFRRP), which uses the local neighborhood information of the network and a fuzzy procedure to take the best decision to forward packets towards the base station. Every node that has a sensed data or a gathered data packet that should be transmitted to the base station selects one of its neighbors as _selected node_ by the proposed fuzzy system to forward the data packet to the base station. Selecting an appropriate neighbor node by a fuzzy procedure is done by considering two parameters, namely _distance_ and _number of neighbors_. In fact, the proposed protocol applies an inferential manner based on the human reasoning to select a proper path from every node to the base station without participating much more intermediate nodes in the transmission path. These features lead the network life to be enhanced considerably, the number of data packets delivered to the base station to be increased, and more data packets being transmitted to the base station in an acceptable time. The remainder of this paper is organized as follows: Section 2 presents previous, related works about routing protocols. A brief review on the fuzzy logic applications are given in Section 3.