# Energy Efficient Routing in Wireless Sensor Networks: A Comprehensive Survey
## 7 Open Research Issues  
WSNs are considered to be among the most emerging scientific domains and have an ever growing range of applications. However, the operation of WSNs is harshly obstructed due to both the specific limitations of their sensor nodes and the inherent problems of wireless communications in overall. It is generally adopted that, among all the factors that have detrimental effect, the energy constraints of sensor nodes constitute the real Achilles' heel of WSNs. Given that energy depletion in sensor nodes is mainly performed during their communication, numerous research efforts focus on the attainment of energy efficiency in data routing. The comparative investigation of such works was the aim of the survey presented in this article. Of course, energy conservation in communication can be even greater by applying additional measures. For instance, it is true that a great part of the data sensed by the sensor nodes in WSNs are redundant. Hence, passing out redundant data decreases the volume of data transmitted along with the energy expenditure and the latency associated. This is why there is need for novel data aggregation schemes [166; 167; 168]. Likewise, the use of compression and restoration schemes provides substantial reduction of communication load [169; 170; 171]. Likewise, whenever a sensor node becomes inactive, because of either the depletion of its energy residues or a malfunction, the communication cost for the remaining active nodes is increased. Thus, the preservation of network connectivity is very important for the execution of the routing process and the extension of network lifetime. This is the aim of relative protocols proposed [172; 173]. At the same time, the attainment of the maximum possible coverage of the network field for a given number of sensor nodes is anticipated. For these reasons, methodologies that pursue coverage maximization in two dimensions [174; 175], three dimensions [176], or in conjunction with connectivity preservation are proposed [177; 178; 179]. In addition, the presence of congestion not only obstructs the transmission of data, but it also causes packet losses and consequently necessitates packet retransmissions that deplete the energy reserves of sensor nodes. Congestion avoidance [180; 181; 182; 183] and congestion control [184; 185; 186] methods are used to prevent the occurrence of upcoming congestion and eradicate existent congestion, respectively. In addition, QoS provision in terms of general performance metrics such as reliable and timely delivery of data or other application specified features obliges the development of such schemes [187; 188; 189; 190]. Moreover, wireless communications are susceptible to numerous types of potential attacks. Specifically, confidentiality, authentication, integrity, availability, and freshness are the main security considerations for WSNs. In order to cope with such issues, the development of security schemes that are specialized for WSNs is necessitated [191; 192; 193; 194]. Of course, the achievement of energy efficiency along with other performance metrics is not an easy task because of the contradictory conditions that must be met. For this reason, multi-objective optimization algorithms have been proposed which aim to optimize the operation of WSNs by pursuing the simultaneous accomplishment of multiple criteria [195; 196; 197]. In addition, WSNs, by their nature, are dynamic environments in terms of both their structure and their operation. Therefore, the use of Machine Learning (ML) is an excellent alternative for the development of energy efficient routing protocols in WSNs because it provides the ability of self-learning from the experience gathered and thus self-adapt to the modifications occurring [198; 199; 200]. Likewise, Artificial Intelligence methods, such as Fuzzy Logic, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, and Artificial Immune Algorithm are a very promising in supporting the development of energy efficient routing protocols in WSNs [201; 202].