## 4 Lifetime Improvement Mechanisms in Routing
### Multi-Path Mechanism
#### 4.3.2 Disjoint Multipath  
_Link-Disjoint Multipath_  
_Adaptive Greedy-Compass Energy-Aware Multi-path (AGEM)_[14], for example, is a kind of link-disjoint multi-path geographic routing that uses the adaptive compass mechanism in order to select the best neighbor in the forwarding phase. The main objective of this algorithm is to maximize  
Figure 5: A source-to-destination meshed multipath [41].  
the network lifetime and achieve better quality of service for audio and video stream transmission in high density wireless sensors networks.  
In this way, AGEM tries to distribute traffic loads on multiple paths based on a greedy routing method. The protocol has two modes as follows: the smart greedy forwarding and the walking back forwarding. According to the greedy mechanism, the first mode will be used when there is at least one neighbor closer to the sink than the sender node. On the other hand, the second mode will be used when the sender hits a void area in which none of the neighbors are eligible to be chosen based on greedy algorithm.  
In smart greedy forwarding mode, each node should keep a table of its _one_-hop neighbors including some information such as the data-rate of the link, the distance of the neighbor to the sink, the estimated distance to its neighbors, and the remaining energy. Since the AGEM is proposed for mobile environment, beacon messages should be employed to update this information. An objective function \"_f(x)_\" is calculated as a score for each neighbor depending on the mentioned information exchanged at fixed intervals. Whereas the protocol selects the best neighbors based on the adaptive compass policy, it selects a series of nodes with smallest angular offset from a supposed line between the sender node and the destination by satisfying minimum candidate nodes to implement online multipath routing. Then among these candidates, the neighbor has the chance to be chosen which serve better the function _f(x)_. The following equation shows the elements of this function:  
\[f\left(N_{i}\right)=N_{i\;Energy}-E_{TX}(N_{i\;Distance})-E_{RX} \tag{6}\]  
where \(E_{TX}\) (\(N_{i\;Distance}\)) = the energy needed to send a packet to the neighbor \(N_{i}\), and \(E_{RX}\) = the energy needed to receive the packet. In order to meet load balancing requirements in the network, each relay node ranks the received data packets based on the number of hops they paced to reach this node. After that it forwards a data packet with the biggest number of hops towards the best neighbor while it sends a packet with the smallest number of hops towards the worst neighboring node. Meanwhile, the protocol can switch to the second mode and use walking back forwarding strategy to avoid holes. In this state, the node delegates the packet forwarding duty to the previous hop. This operation will be repeated recursively till a relay node could be reached to forward the packet successfully [14].  
Experimental results [14] confirm that AGEM improves the distribution of the remaining energy across the network by more than 32% compared to the GPSR routing algorithm. The reason is that most of the nodes can be active due to multipath routing. It also significantly reduces the end-to-end delay and packet loss at a rate of 150% and 900%, respectively. It is because of the use of multiple paths for data packet transmission. Since the protocol is designed for wireless mobile sensor networks (WMSNs), a huge amount of beacon messages for topology update wastes unnecessary power across the sensor field.