# Survey on Power-Aware Optimization Solutions for MANETs
## 2 Related Work
### Power-Aware Routing Metrics  
The conventional forwarding (routing) protocols for wireless networks instinctively consider minimum-hop and shortest-delay forwarding as a metric to assess optimal paths. Such protocols are Destination-Sequenced Distance Vector (DSDV) [68], Wireless Routing Protocol [69], Temporally-Ordered Routing Algorithm (TORA) [8], Ad hoc On-Demand Distance Vector Routing (AODV) [70; 71], and Dynamic Source Routing (DSR) [72]. While, [PERSON] et al. [73] have suggested the Signal-Stability based Adaptive (SSA) forwarding scheme, which utilizes the steadiness of the distinguishable host, location permanence, and signal strength as forwarding metrics. The SSA scheme suggests that picking the most suitable stable links will lead to strongly connected network paths. Understandably, some of these well-known orthodox metrics have a harsh consequence on network lifetime, since such metrics unintentionally over-utilize the power resources of the nodes (i.e., no consideration of power at all had been done). [PERSON] et al. [61] have effectively shown that none of the abovementioned forwarding metrics (currently deployed in many routing protocols) can achieve the goal of carefully utilizing power resources. In general, energy-aware forwarding policies can be categorized based on their adjusted route selection procedures (or routing metrics used) [20; 36]:  
1. Induced power-cost from the transmission. 2. Residual power capacity of the node. 3. Probable node lifetime. 4. Hybrid energy-aware metrics. Energy-aware forwarding policies often utilize more than one set of energy-allied metrics to estimate and determine the optimum routes, depending on the conditions, briefly defined as:  
* _Reducing the Energy Exhaustion per Packet Transmission and Reception_: This metric shows how the overall average power consumption per packet transmission and reception can be reduced. According to [61], under lighter traffic conditions, if we utilize this metric to assess the paths then there is the possibility (in most cases) that the chosen path will be equivalent to paths that get selected by the minimum-hop forwarding metric. So, in such a case, we cannot expect much change in power consumption performance. Nevertheless, under heavy traffic conditions, the path selected via such a metric may be different from the path chosen via the minimum-hop forwarding metric. Subsequently, if a node (or more than one node) on the selected path (i.e., it may or may not be the shortest route) suffers from severe congestion, then per-packet power consumption at each congested node will also differ because there may be a case of higher variations in contention level at each congested node, hence, per-packet power consumption will also get vary. Consequently, this metric may tend to forward packets in highly congested network areas. Nevertheless, taking this metric blindly without examining the individual residual energy of nodes may lead to the problem of unfair energy residual distribution in the network. We conclude that this metric does not assist in increasing network lifetime in any case. * _Maximizing Period to Network Segregation_: According to [61], the set of critical nodes in the network must be identified. If critical nodes detach from the network for any reason, the entire network will divide into many parts. The paths between such partitions must pass through one such crucial mobile node. The forwarding process has to be modified in such a way that the load is evenly distributed over all such critical nodes via a \"load-balancing\" scheme. Nevertheless, trouble will arise if multiple network parts are connecting with a single node, as shown in Figure 1--for instance, in the network topology node \"0\", depicted in Figure 1, is a critical node. If node \"0\" stops working for any reason, then this entire network will be separated into many small parts. Here, the main idea is to ensure that the rate of power consumption should be similar in all critical nodes if we want to maximize the network lifetime.