## 5 Protocol Comparison  
A common objective of all mechanisms surveyed in this paper is to prolong the network lifetime. In all approaches, it is assumed that sinks have unlimited energy resources while sensor nodes are energy constrained. Multiple and mobile sink strategies, multi-path strategy, power control schemes and bio-inspired mechanisms are examples of methods that can be employed in routing algorithms to increase network lifetime. The multi-sink and mobile sink mechanisms as discussed in Sections 4.1 and 4.2 respectively are compared in Table 1 based on the following criteria:  
* _Multi-sink_: As mentioned before, the network lifetime could be improved by preventing network partitioning caused by fast energy depletion around the sink. Increasing the number of sinks is one of the methods to distribute the traffic load through the sensor field and balance energy consumption around the sinks. The algorithms presented in [5; 6; 7], are samples of multi-sink mechanisms for lifetime enhancement. Although some other protocols [8; 9; 10] are originally designed for mobile sink strategy, they can also support multi-sink mechanisms as well as previous approaches. Therefore, the researchers can use these two techniques simultaneously to get better results. * _Mobile sink_: It is another solution for \"sink neighborhood problem\" caused by network partitioning around the sink. A mobile sink can replace its neighbors with low residual energy by relocating to fresh part of the network periodically. Some of the protocols [8; 9; 10; 11] in Table 1 use this mechanism to prolong the network lifetime. * _Multi-path_: Since employing a single path for data transmission between a source and the sink can decrease the energy level of sensor nodes on the path quickly and cause network partitioning along the route, making use of the multi-path mechanism results in traffic load and energy balancing over the sensor field. In MSDD [5] and MSLBR [7], for instance, each source node can implement multiple paths towards the multiple sinks to increase reliability and fault tolerance as far as possible. It is worth mentioning that there is no protocol listed in Table 1 using mobile sink and multi-path mechanisms simultaneously. * _Power control_: according to this mechanism, each sensor node tries to compute the energy needed to send a packet to the next hop in multi-hop routing protocols. In this way, the node is capable to adjust the transmission power level based on the distance to the next hop and avoid using maximum power level. As a result, the network lifetime will be improved by saving nodes' energy individually on the path. Only one protocol [11] in this table can employ a power control scheme. * _Sensor mobility_: As mentioned before, the ability to change the position of sensor nodes helps to maintain connectivity by avoiding network partitioning and sink neighborhood problems. In Table 1, none of the protocols use this method. * _Sink movement pattern_: There are three methods used by the sink node to identify the next position during the movement. In stochastic mobility pattern [8, 10], a random path is followed by the sink node while the path is predefined in a fixed [9] strategy. In controlled mobility pattern [10, 11], the sink is able to define the next position autonomously based on variations of the energy factors in the sensor field. The algorithm proposed in [11] uses a fixed sink mobility method for the first round. However, it switches to controlled sink mobility in subsequent rounds. * _Location awareness_: Location information is a powerful tool to find the best next hop in routing mechanisms. It can also be used for determining the next location of mobile nodes in the network. This information can be acquired from GPS directly or calculated on other localization methods. None of the multi-sink approaches in Table 1 are location aware. Although the sink node in all mobile sink mechanisms knows its position, there is only one [9] algorithm in which all nodes are location aware.