## 4 Lifetime Improvement Mechanisms in Routing
### Multi-Sink Mechanisms  
As mentioned before, network partitioning caused by energy depletion around the sink (the sink neighborhood problem) is one of the main issues that affect the network lifetime. Therefore, many techniques have been used in previous works to overcome this problem. One possible method is to employ multiple sink nodes throughout the network. Researchers who work on multi-sink mechanisms believe that by increasing the number of static sink nodes one can distribute the traffic load all over the network and consequently balance energy consumption around the sink. Finding an optimal location for the sink nodes and looking for low cost paths from each source node to one or several sinks [5] are the main concerns in this research area. _Multi-Sink Directed Diffusion (MSDD)_, which was proposed in [5], is a kind of multi-sink approach that employs the basic idea of a Directed Diffusion (DD) routing protocol to construct routes from each source node to the nearest sink node. Network lifetime could be increased in this protocol by switching the data flow to the next nearest sink when the power level of relay nodes on the primary path falls below a certain threshold. Just like the DD algorithm, the sinks propagate interest messages through the network to find the sources which contain the data of interest. When a source node receives such messages from multiple sinks, it responds by broadcasting an exploratory data (ED) message through the network. Then bi-directional paths are constructed towards the source node and the sinks start to send positive reinforcement messages to the source. In this state, if the source node accepts all reinforcement messages from multiple sinks, the data packets should be forwarded to all of them, which imposes a large overhead caused by the redundant data. Therefore, it registers the neighbor node that sends the positive reinforcement with smallest _Hop_Count_ value into the _Path_List_ table. It also retains the information about other paths to use them as backup routes when the residual energy of the primary path falls below a certain threshold. In some situations, as shown in Figure 3, a single neighbor of the source may be shared among several paths from different sinks. Thus, by choosing this node, data packets will be relayed towards all the paths including this neighbor. In order to avoid this problem, each sink node assigns a random number as _Path_Id_ to the positive reinforcement messages. These path identifiers that distinguish the paths from each other are also registered in Path_List table. As illustrated in Figure 3, D represents the sink node (destination) and S indicates the source. There is also a source neighbor that is common between the paths with Path_Ids 1 and 2. In MSDD, a negative reinforcement message is employed to inform the source node of a path failure. In this state, it then removes this path from its Path_List table. Simulation results [5] show that MSDD could enhance the average energy of network nodes and the energy of nodes with the minimum energy by increasing the number of sink nodes. The authors also proved that connection lifetimes up to three times longer could be achieved using a multi-path routing algorithm. The routing overhead of Directed Diffusion is decreased in MSDD, which results in up to two times higher network lifetime. Nevertheless, the algorithm could only be used in query-driven applications according to the main operation of Directed Diffusion family protocols. _Gradient-Based Routing Protocol for Load Balancing (GLOBAL)_[6] is another multi-sink protocol that maximizes network lifetime with the help of a new gradient model. This algorithm selects the least-loaded path for data forwarding that also excludes the most overloaded sensor nodes. By applying this method, network lifetime is not limited by the short lifetime of such overloaded nodes. Each sensor node in this protocol computes its residual energy depletion rate (_REDR_) that will be used later in gradient field construction phase.