## 2 Related Works
Other works using the forbidden area approach can be found in [30; 33; 42]. all these approaches can reduce the data congestion on the hole boundary, but they may create a new congestion area around the hole cover, instead. Moreover, routing paths may be enlarged due to the difference between the hole and the hole cover. [43] is a rare protocol that uses a dynamic forbidden area that is circle-shaped. Although this protocol can alleviate the traffic congestion around the forbidden area, it still suffers from routing path enlargement problems. In [44], [PERSON] et al. proposed a protocol that can guarantee that the route stretch is upper bound by \(\Theta\left(c\right)\), where \(c\) is the path length of the shortest path. In this protocol, the forbidden area is the convex hull of the hole. The packets then are routed along the shortest path from the source to the destination that goes through the vertices of the convex hull. This work is followed in [34] to address the problem of routing between nodes inside the concave regions of the holes. In [34], the authors proposed to describe the hole by a polygon whose vertices are all the nodes staying on the hole boundary. The routing path then is determined by the visibility graph whose vertices are vertices of the holes. The upper bound stretch was proved to \(\Theta\left(\frac{D}{\gamma}\right)\), where \(D\) is the diameter of the network and \(\gamma\) is the communication range of sensor nodes). Although these two protocols are the rare ones that can provide stretch upper bound, they still suffer from the same problem, i.e., traffic concentration around the forbidden area, as the other protocols described above. Moreover, in these two protocols, especially [34], the information needed to represent the forbidden area depends on the holes and it may be significantly large when the holes become complicated. Consequently, they may cause extra overhead in disseminating and storing information about the forbidden areas. Recently, [PERSON] et al. tried to improve the load balance by exploiting energy information in making decisions [45]. Specifically, before sending data packets, every source node sends two so-called burst packets towards the destination. The burst packets are hole-bypassing, one goes along the right-hand side and the other goes along the left-hand side of the holes. These packets collect information on two anchor lists along the routing path. Upon arriving at the destination, the burst packets, with the anchor lists embedded, are pushed back to the source. When a source node has a packet to send, it randomly chooses an anchor list and embeds the location of the anchors into the packet header. The packet then is forwarded towards the anchors gradually, where the next hop is chosen based on the location and the residual energy of the neighbors. In contrast to the other geographic routing protocols, this protocol requires nodes to periodically broadcast beacons to update the energy information. Several approaches exploit heuristic methods to maintain the load balance between the nodes. [PERSON] et al. [46] proposed a scheme to avoid the local minimum problem by identifying the nodes staying inside the concave areas and prevent them from participating in data delivery. Although these schemes can shorten the routing path, they continue to suffer from traffic congestion surrounding the hole. In [47], the next forwarder node is chosen based on a so-called forwarding factor. This factor is proportional with the residual energy and inversely proportional with the distance to the destination of the neighbors. Accordingly, neighbors with higher residual energy and shortest distance to the destination are more likely to be chosen. In [48], the next hop is chosen based on a self-election paradigm. Specifically, upon receiving a packet, all the neighbors of the sending node will start a waiting timer and wait for its timer to expires before broadcasting the packet. The waiting time is proportional to the destination.