## 2 Related Work
Apart from clustering and due to potentially unlimited harvested energy, several authors proposed various ideas about how to efficiently use the harvested power to achieve best performance [32]. One of the ways that is explored is by adjusting transmission power of the nodes. Optimal energy management policies for energy harvesting sensors are considered in Reference [33]. The discounted throughput is maximized over an infinite horizon, where queuing for data is also considered. In Reference [34], the authors proposed a solution to maintain the battery at a certain level in a network with time-varying battery recharging rate. In this work, two algorithms, namely, QuickFix and SnapIt, to compute the sampling rate and routes and to adapt to the rate, are respectively proposed. In Reference [35], to maximize the successful transmission and control energy-error probability tradeoff, MarkovDecision Processes (MDP) have been used to choose between multiple transmissions. The authors in Reference [36] developed a discrete time Markov model for different energy profile and storage capabilities to analyze node outage probabilities. A complete information Markov decision process model is developed in Reference [37] to characterize sensor's battery recharge/discharge process to achieve optimal transmit policies. In Reference [38], the authors used an infinite time-horizon Markov decision process (MDP) to formulate the power control. They obtained a closed-form threshold-based optimal power control solution for EH-WSN. The authors in Reference [39] formulate the power control as a stochastic optimization problem and solve the optimization problem using Lyapunov techniques. Without requiring historical knowledge of energy harvesting only based on the channel fade conditions and current energy state of the battery, their proposed algorithm adjusts the transmission power. To the best of our knowledge, there is a limited number of contributions in the literature about clustering and power control on energy harvesting sensor networks. However, there are some similar works on conventional battery powered sensors. [PERSON] et al. [40] proposes an Energy-Efficient Unequal Clustering (EEUC) mechanism, which partitions nodes into unequal cluster sizes in a way that clusters closer to the base station have smaller sizes than those clusters that are farther away from the base station. Using this method, there would be less power consumption due to intra-cluster data forwarding for cluster heads closer to the base station. [PERSON] et al. [41] proposed two routing protocols, namely power-controlled routing (PCR) and enhanced power-controlled routing (EPCR), where the basic idea of both is nodes only change their transmission power when they want to transfer their data to the cluster-heads. Thus, nodes that are closer to the cluster-head can transmit with lower power, which eventually results in less power consumption. The authors in Reference [42] propose a clustering algorithm and a transmission power control mechanism for an ad hoc network, aiming to reduce the impacts of mobility and adaptive transmission power. The idea is that the cluster-head adjusts its transmission power to the changes in its cluster. For example, if CH receives a weak signal from a sensor or a report about unusual error rate, it increases its transmission power to the maximum to cover all the nodes in its vicinity. In another work, the authors in Reference [43] propose a power aware multihop routing protocol for a cluster based sensor network, where the objective is to minimize the power consumption of CH, then it sends the data in a power-aware multihop manner to the base station through a quasi-fixed route (QFR), where nodes vary their transmission power based on the distance to the receiver. This paper does not aim to propose a novel clustering scheme for energy harvesting sensors, nor does it intend to propose a novel power control scheme for WSN. As energy harvesting is spatio-temporal dependent, nodes might harvest energy with different ratios.