## 2 Related Works  
Due to the short-range wireless communication nature of the sensor nodes, data transmission in WSN is performed in a multi-hop paradigm. Therefore, routing becomes an important issue that attracts a lot of attention from the research community [15]. Inherent characteristics of WSN including limited energy supply, limited computation power of sensor nodes and the large scale of network topology pose many challenges to the design of routing protocol. To conserve energy consumption, the routing protocol should be made as simple as possible. Geographic routing [22; 23] which exploits the local geographical information at the GPS-equipped sensors is widely accepted for its simplicity and efficiency. Geographic routing algorithms typically assume: a) that each network node knows its own and its neighbors' positions and b) that the source of a message knows the destination's position. The simplest geographic routing protocol is the greedy forwarding where each node chooses the next hop to be the neighbor node with the most geographical advantage to the destination. Geographic routing works well in networks where the nodes are deployed densely. However, with the occurrence of void areas (which are also called routing holes), i.e., the regions where the nodes have died out and hence, no longer participated in the network communication, geographic routing suffers from the so-called local minimum problem where there is no neighbor which is closer to the destination than the current node [25]. To bypass a hole, traditional schemes appropriately switch between greedy and perimeter forwarding modes, in the latter of which the data packets are forwarded along the hole boundary. These proposals require a specific embedding of a planar graph (e.g., Gabriel Graph), a complicated procedure based on a restrictive assumption about the underlying graph (e.g., a unit-disk graph) [23; 26; 27; 28; 39]. Although these traditional approaches can alleviate the local minimum phenomenon, they face two critical problems. The first problem is the enlargement of routing paths and the second problem is the traffic concentration around the hole boundary [40; 41]. To deal with these two problems, a new approach has been proposed which we call forbidden area approach. The main idea is to create a forbidden area around every hole from which all the packets are kept to stay away from. Typically, forbidden area is a static region covering the hole and with simple shapes such as circle [29; 30], ellipse [31], hexagon [32], convex hull [33; 34] In [29], [PERSON] et al., proposed a routing scheme wherein the forbidden area is a circle covering the hole. First, the nodes on the boundary of the holes are identified using Boundhole algorithm [24] and a virtual circle that exactly covers the hole is formed. The information of the circle is disseminated to all nodes on the boundary of the hole. When a source node \(S\) wants to send a data packet to a destination node \(D\), it first sends the packet along the line \(SD\) by geographic routing. The node on the boundary of the hole receiving the data packet informs the source node of the information of the virtual circle. Then, the source node calculates an anchor location which is the intersection of two tangent lines from \(S\) and \(D\) to the virtual circle. The source node forwards the data packet to the node which is closest to the anchor location by geographic routing and this node will forwards the data packet to the original destination. A routing scheme using virtual hexagon is proposed in [32]. Similar to [29], after identifying the boundary of a hole using the Boundhole algorithm, information of the center and the radius of the virtual circle which exactly covers the hole is calculated. This information is transferred to all nodes on the boundary of the hole and helps to make the routing decision. Instead of a virtual circle, in [31] a virtual ellipse covering the hole is calculated and the information of the ellipse is sent to all nodes inside the ellipse.