## 2 Related Work and Motivations  
Routing in wireless sensor networks is a challenging task. Many different approaches have been proposed in the literature. We can identify three main classes of routing protocols: _(i)_ proactive routing such as OLSR [5]_(ii)_ reactive routing such as AODV [4] and _(iii)_ geographic routing, or georouting. This latter approach is receiving more and more attention since it is a memory-less and scalable approach,unlike the two other ones. In a geographic approach, every node is aware of the exact or virtual coordinates (position) of itself, its neighbors and of the destination. Exact location coordinates may be available from GPS [13] or any other position mean [7]. Each of two families of georouting protocols (with exact and virtual coordinates) can be divided based on its properties with respect to the metric used (hop count or power), and whether or not it guarantees delivery. Therefore there are four classes of algorithms: _(i)_ simple hop count based algorithms without guaranteed delivery, _(ii)_ hop count based with guaranteed delivery, _(iii)_ energy-efficient without guaranteed delivery or _(iv)_ guaranteed-delivery and energy-efficient. Table 1 sums up the different categories and algorithms. There are two well-known algorithms for the case where nodes are aware of their exact geographical coordinates available from GPS [13] or Galileo [15] or any estimation of them [16]. In _Most Forward Routing with progress (MFR)_[12], the node \(S\) currently holding the packet for destination \(D\) forwards it to neighbor \(A\) whose projection on line \(SD\) is closest to \(D\). In \(greedy\) routing [14], \(S\) forwards the message to the node that is closest to \(D\). These are simple localized algorithms that do not guarantee delivery. A packet can be trapped in a local minimum and the algorithms fail to find a path to the destination leading to low delivery rates. In dense networks the algorithms perform well. Greedy georouting has then been enhanced in two directions, toward changing hop count to another metric, and toward providing guaranteed delivery. Power aware greedy routing algorithms were first studied in [17]. Instead of counting hops, power consumption on edges on a route was considered as the cost. An algorithm with general cost metric was proposed in [1]. Cost over Progress based routing [1] (COP) is a localized metric aware greedy routing scheme. A node forwards a packet to the neighbor closer to destination \(D\) such that the ratio of the energy consumed to the progress made (measured as the reduction in distance to \(D\)) is minimized. Though cost efficient, this algorithm does not guarantee delivery. Cost could be an arbitrary metric, such as hop count, power consumption, reluctance to forward packet, delay _etc_. In [2], greedy routing is applied till reaching either the destination or a dead end. In latter case, face routing is applied to recover from failure. Face routing requires the network topology to be a planar graph (_i.e._, no edges intersect each other). The graph planarization (through a Gabriel Graph [18] or a Relative Neighborhood Graph [19]) divides the graph in faces. The face that contains the line (\(SD\)), where \(S\) is the failure node, and \(D\) is the destination node, is traversed by right/left-hand rule (placing a virtual hand on the wall of the face) until a node \(A\) closer to destination than \(S\) is encountered. It has been shown in [2] that face routing guarantees recovery traversing the first face. Greedy routing continues from \(A\) until delivery or another failure node is encountered. GFG guarantees delivery but uses hop count as metric, and is therefore not energy-aware. Many georouting protocols guaranteeing