## 1 Introduction
Usually, this problem is simultaneously solved by synchronizing the clock first then locating the position of unknown sensors. Because of the poor efficiency of handling this problem independently, joint efforts have started to get good results due to the dependency of these two processes of localization and time synchronization. In UWSNs most of the techniques of accurate localization are based on the measurement of time of arrival (ToA) and their clock synchronization between the nodes, in contrast to this process of time synchronization takes advantage of the location information which can be further use in calculating the propagation delay. The message exchange between anchor and sensors has got both the information of location and clock information. Based on this information, the localization of sensor nodes and clock information can be calculated simultaneously with the help of a single sort of message, which ultimately reduces the energy. Due to all the above-mentioned facts that explain the dependency of localization and time synchronization on each other, we can say that solving these two problems in a single framework, not only gives accuracy but also provides energy efficiency. Besides the most important challenges of underwater that is, localization and time synchronization, consideration of the depth-dependent SSP (sound speed profile) which does not travel in a straight line and dependent upon the pressure, temperature, and salinity [4] is another main challenge, because in a real UWSNs environment, sound waves do not travel in a straight line. Propagation path bents and the node distance between the nodes do not travel by an acoustic wave. This phenomenon is called the stratification effect [5; 6]. Based on the ray tracing approach, the object of this study is to apply the joint synchronization and localization five-phase algorithm called \"Energy Efficient Joint Time Synchronization and Localization\" using ray tracing model \(E^{2}JSL\) with the consideration of the stratification effect. To handle the stratification effect, first, we use to introduce the ray-tracing model that develops a framework in which the stratification effect, clock drift, and sensor node location are estimated. The algorithm starts with a message exchange procedure between the anchor and sensor node. Ordinary sensor nodes that need to be localized are moving with depth information whereas the static anchor node has got all the information such as its location and time. A Comparison with different approaches has been made to prove the validity of the proposed technique in the simulation section with the estimation of the Cramer-Rao lower bound (CRLB) for the convergence analysis. Also, the complexity of the proposed algorithm is calculated to show that the provided study takes less running time compared to the existing techniques. As far as the limitation of the provided technique is concerned, provided study will not work in a multi-hop environment due to the one-way message exchange condition, but by making some additional assumptions, the proposed algorithm will work for the multi-hop environment for a large scale underwater localization and time synchronization. The proposed research work is based on the following sections. Section 1 gives the introduction, Section 2 provides some information about the challenges in underwater sensors, Section 3 shows the comprehensive related work, Section 4 indicates that how the ray-tracing approach is beneficial for the proposed work. Section 5 gives the network assumptions followed by Section 5.1 which provides the proposed ray-tracing model, which is further extended in subsections Section 5.2 with the calculation of direct distance traveled by the ray. Section 6 calculates the pairwise localization and time synchronization, wherein Section 6.1 shows that how the proposed model works iteratively to get the accuracy, Section 6.2 gives the summary of each phase. Section 7 calculates the Cramer-Rao lower bound for the proposed algorithm along with the complexity computation in Section 7.1.