Deep learning is a wildly popular topic in machine learning and is structured as a series of nonlinear layers that learns various levels of data representations. Deep learning employs numerous layers to represent data abstractions to implement various computer models. Deep learning approaches like generative, discriminative models and model transfer have transformed information processing. This article proposes a comprehensive review of various deep learning algorithms Multi layer perception, Self-organizing map and deep belief networks algorithms. It first briefly introduces historical and recent state-of-the-art reviews with suitable architectures and implementation steps. Moreover, the various applications of those algorithms in various fields such as wireless networks, Adhoc networks, Mobile ad-hoc and vehicular ad-hoc networks, speech recognition engineering, medical applications, natural language processing, material science and remote sensing applications, etc. are classified.

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Some sensitive applications such as volcanic monitoring, fire detection data should be transmitted within a specified delay to the base station. Multipath-GT (Multipath-Generalized Topology) model uses an on-demand approach to estimate a delay based on processing time, packet loss rate between two neighbouring nodes. In existing work, if a node or link failure occurs multipath routing didn't spread traffic over alternate paths. This paper take a view that, when certain nodes and links become over-utilized and cause congestion, proposed work can spread traffic over alternate paths to balance the load over those paths and increase the degree of fault tolerance. The simulation results show that reduces the probability of communication disruption and data loss during link failures.

Wireless Body Area Network (WBAN) is a recent technologically advanced sub-category of Wireless Sensor Networks (WSN) which consists of many bio-sensors, attached in and around of human body, for monitoring the health-related issues from remote places. Energy conservation in WBAN has always been the most crucial issue for the sensor nodes, which are powered by limited capacity battery sources. During sensing and communication, sensing elements emit high temperature from its circuit and transmitting antenna due to inefficient data routing designs. This energy may lead to form hot-spot, which affects the human tissues at a different level. So designing an energy-efficient routing protocol is a very challenging issue to reduce the high emission of temperatures. Different energy-efficient routing protocols have been projected in this survey over the years. The energy-efficient routing protocols endeavor to prolong the network lifetime by minimizing the energy consumption in each deployed nodes. There have been a variety of survey papers put forwarded by researchers to evaluate the performance and categorize the different energy-efficient routing protocols for WBANs. This paper describes an overview of WBAN, a systematic survey of existing contracts for routing and open research issues are discussed.

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