## 2 Related Work
Moreover, [PERSON] _et al._[23] considers many-to-one communication and analyzes the efficiency in forwarding packets as a function, not only of the hop count, but also of the link quality. This is reflected in lower energy consumption, due to a reduction in the packet loss. In addition, the influence of packet retransmissions in communication and its effects on energy efficiency in the network are analyzed. All factors related to the occupancy of the channel in wireless communications influence the multiple-hop networks and affect the network performance. Some of the most adaptable protocols to this type of network are AODV and DSR, which aim at reducing cost and energy consumption and improving reliability. These protocols allow multi-hopping among the actively involved nodes that want to establish and maintain routes in a network [24]. On the other hand, ZTR, a widely referenced algorithm, has low overhead and is simple with regard to the memory capacity of the nodes, since they do not have routing tables, which eliminates path searching and updating. Nevertheless, it has some drawbacks in terms of flexibility and adaptation, especially when it is deployed in wide network environments [25]. Regarding the energy problem, [PERSON] _et al._ in [26], introduce a method for balancing costs with a clustered spanning hierarchical algorithm and an energy model based on transmission energy. In addition, they assigned weights to the links in a graph model and explain how the algorithm provides the best routes of the hierarchical tree. Self-organization of these distributed algorithms maximizes sensors lifetime. On the other hand, related to the power balance in the network, [27] treats the issue of energy distribution among the nodes as a function of the traffic load. In that paper, the authors set coronas around the sink node with the purpose of showing that the nodes closest to the sink carry more traffic load and, thus, spend energy more rapidly. Then, they propose as a solution the non-uniform distribution of the nodes, so that energy depletion is balanced. Along the same topic, the authors in [28] complement the analysis with the study of multi-hop routing and its impact on node distribution contrasted with direct the transmission mode and its effects on node distribution. They also address the problem through a topology of coronas around the sink node and analyze the inter-corona and intra-corona energies. [PERSON] _et al._ in [29], study the network formation process and the topology focused on energy consumption. They vary factors, such as the number of sink nodes and their distribution in the network. Relationships between the number of sink nodes and energy consumption are established, and static and mobile scenarios are studied. The work in [30] introduces the relationship of energy with the performance of the network. This problem is greater in networks with static nodes. The nodes closest to the root node or collector node are likely to deplete their energy first, because they generate traffic and also carry traffic from other network nodes. This difficulty is known as the depletion energy sink-hole problem. This can cause connectivity problems between the root node and the rest of the network, completely missing information at the destination. [PERSON] _et al._[31] also tackle the energy reduction problem of the nodes nearer to the collector node. The authors propose a solution using mobile sinks. This balance solution works due to the topology changing, and the nodes are sometimes away from and sometimes near of the collector. However, this will affect overhead and delay, and it will improve the network performance, but traffic and energy are balanced, representing an important advantage. Moreover, metrics, such as energy, latency and reliability for the mobile sink routing protocol, are discussed.