## 5 Routing Layer in WMSN
### Routing Methodologies in WMSN  
The recent work in routing layer of WMSN, as shown in Table 3 and summarized below, tries to handle these new characteristics of WMSNs and their design challenges by either modifying the previous work done in WSNs (e.g., using multiple performance metrics to meet the additional QoS requirements), or proposing new solutions based on new methodologies (e.g., using multi radio or MIMO systems, switching between multiple channels, selecting multi routing paths, or mixing among these methods). Moreover, we should point to the fact that these additional challenges and requirements of WMSNs, mainly by streaming real-time multimedia content, open the call for new research on cross layer design for more optimizing solutions. For example, cross layer design between multimedia source coding techniques at the application layer and the routing protocol in the routing layer can be exploited for better multipath selection or in-network processing. Also, cross layer design between the routing layer and the MAC layer can allow for packet-level service differentiation or priority-based scheduling and for more power efficient routing mechanisms. The work in [32] presents an Ant-based Service-aware routing algorithm (ASAR), a QoS routing model for WMSN, that chooses appropriate paths for different QoS requirements from different types of services. The proposed algorithm mainly addresses the routing scheme between the cluster head and sink node in which a cluster head transfers the different classes of data. The process starts at the cluster head when it generates the ants for each type of service and then depending on the objective function of each type of data and pheromone value of each path, different paths are found to meet the different QoS requirements. In order to quicken the convergence of the algorithm and optimize network resources, the algorithm quantifies the pheromone value on the sink to decrease the sending frequency of reverse ants or control messages. Presented results show that: ASAR has a significant advantage over Dijkstra andDirectional Diffusion (DD) in most metrics; except in packet loss rate for stream query service and delay when compared with DD. A geographic routing algorithm, Two-Phase Greedy Forwarding (TPGF), is proposed in [33]. It explores near shortest hole-bypassing node-disjoint routing paths for WMSNs. TPGF supports multipath transmission by repeatedly executing the algorithm to find more on-demand node-disjoint routing paths. TPGF also supports near shortest and hole-bypassing path without including the face routing or planarization algorithms in order to maximize the number of available paths. It assumes that all the nodes know their location information and the source nodes know also the location of the base station. The first phase of TPGF is responsible for finding the possible routing path and it consists of two steps: greedy forwarding and step back \(\&\) mark. The process starts at a source node that chooses the next-hop node which is closest to the sink among all the neighboring nodes and so on. In case that the next-hop does not have any farther neighbor except the previous node, it steps back to its previous-hop and marks itself as a block node. The second phase of TPGF is responsible for optimizing the found routing paths with the least number of hops and by eliminating the paths circles (if any) in the found paths using label based optimization technique. Presented results show that the average path length obtained by TPGF is much shorter than the one obtained by GPSR [34]. The work in [35] suggested to use landmark ad hoc routing protocol (LANMAR) in WMSNs with deploying limited number of mobile swarms, in which the network is divided into groups (LANMAR groups) and each group has a landmark node which is dynamically elected. A swarm is a group of nodes physically close to each other and usually share the same mobility pattern.