## 2 Routing Protocols in Large-Scale WSNs
### Energy Consumption Mitigation Algorithms
In order to increase the energy efficiency of ARPEES in a large-scale scenario and balance energy consumption required for sensing data, forming clusters, selecting cluster heads, and relaying data to different sensor nodes to prolong the whole network lifetime, the so-called SC-ARPEES protocol was proposed by [PERSON] _et al._ in [31]. In SC-ARPEES, the processing phases are similar to those in ARPEES, except for an additional phase of removing redundant nodes. SC-ARPEES inherits the advantages of ARPEES, but it may cover a larger area using fewer sensors. In large-scale WSNs, substantial numbers of nodes are deployed randomly over the entire desired area, and the sensing regions of different nodes may partially overlap. Therefore, the network will contain numerous redundant nodes. When the cluster formation phase is done, each non-cluster node will check whether it is redundant by Maximum Sensing Coverage Region (MSCR) algorithm put forward in [31]. If so, then it sends a sleep message to the cluster head, or else it sends an active message to the cluster head and waits for a TDMA schedule message from the cluster head. The clusters in ARPEES are constructed on demand, which makes the protocol scalable to the network extension. The property whereby a node with the most descriptive event information is selected as a CH node helps the ARPEES protocol reduce the data packets transmitted within a cluster and decrease energy consumption correspondingly. Moreover, data aggregation at CH nodes further reduces transmitted data packets. SC-ARPEES outperforms ARPEES in reducing redundant nodes and thus improves network performance. According to the simulation results presented in [31], SC-ARPEES reduces the average residual energy up to 30% compared with the original ARPEES, because SC-ARPEES achieves energy balance by checking redundant information and scheduling the nodes' activities. Therefore the network life time is prolonged. However, in order to calculate the distance from the BS, the BS has to broadcast beacon messages periodically with the maximum radio power to cover the whole network field. On the other hand, in every round the CH node has to keep the transceiver active all the time in order to receive packets from cluster member nodes and the possibility of energy exhaustion is not handled. _DGMA_. In terms of energy consumption reduction and network end-to-end delay decrease, a Data Gathering algorithm based on Mobile Agent (DGMA) for the cluster-based wireless sensor network was proposed in [32]. The region where an emergent event occurs is clustered dynamically based on the event severity, by which the scale and lifetime of clusters are determined. In each cluster a mobile agent is utilized to traverse every member node to collect sensed data. In the higher level of the network, a virtual cluster is formed among the cluster heads and the base station, and multi-hop communication is adopted for sensed data delivery to the base station. In DGMA, all the sensor nodes are in \"restraining\" state and they are activated only when some emergent event occurs. Then the nodes having monitored the event are clustered. After the event intension gets reduced, the clustered nodes will change to a \"restraining\" state for the sake of energy consumption reduction. In the cluster, the tree structure is used to save energy instead of single hop communication between the sensor nodes and the cluster head. After the cluster construction is complete, a route for the mobile agent, which is equipped on the cluster head, is used to traverse all the member nodes for collecting the sensed event data. This process is started up by the cluster head and repeated at every cluster member by broadcasting a request packet, and anticipating a reply from its each neighbor for getting residual energy, path loss, and event intension information of the neighbor.