# Adapted Diffusion for Energy-Efficient Routing in Wireless Sensor Networks
## 2 Wireless Sensor Networks and Routing--Background/Survey
### Literature Survey
[PERSON] states that the current means of AUV underwater path planning mainly include the ant colony algorithm [6; 7], fuzzy algorithm [8], genetic algorithm [5; 9], algorithms based on neural networks [10], and algorithms based on the artificial potential field theory [11; 12]. [PERSON] et al. [4] consider optimizing the performance of the artificial electric field algorithm (AEFA) and broadening its application domain in order to aid in providing robot path planning in 3D complex scenes. [PERSON] [13] uses mathematical models of wireless body area networks (WBANs) to monitor patient care and uses a multi-hop routing protocol. The simple energy-aware and reliable (SEAR) routing protocol is proposed to transmit reliable data packets in a WBAN. Energy savings are compared to energy-efficient and reliable routing based on reinforcement learning and fuzzy logic. Our model compares energy savings compared to DD. Methods include allocating resources base levels, a cross-layer design, opportunistic transmission such as sleep-wake scheduling, routing, and clustering, coverage, connectivity and optimal deployment, mobile relays and sinks, data gathering and network coding, data correlation, beamforming, and energy harvesting. Other work includes an ABM of a WSN [14] that does not use NetLogo. [PERSON] [15] broadly categorized energy conservation schemes under three main headings: duty-cycling, data-driven, and mobility-driven techniques. Duty cycling is aimed at reducing idle listening when the node's radio waits in vain for frames and overhearing when nodes stay active listening to uninterested frames. Data-driven techniques use some parameters of the data themselves to make decisions to reduce energy consumption during communication, while mobility schemes consider the mobility of the sink or relay nodes as a factor affecting the energy consumed in the network. Energy conservation involves minimizing the communication cost in nodes. As the radio is the biggest consumer of energy, this can be achieved by energy-efficient routing protocols. For example, there is a NetLogo model [16] that investigates a mobile ad hoc network (MANET). In this paper, distributed Dijkstra's shortest path algorithm is used to solve the routing problem. This algorithm is frequently used to solve routing problems in telecommunication networks. This algorithm determines the shortest path between the source and all other nodes in the graph. This paper is different from our paper in that in our paper we track energy usage and use a fixed sink and changing source. We can also modify the model for a mobile sink or multiple sinks. [PERSON] et al. [17] focused on various issues of the healthcare system and their solutions. An energy-efficient routing protocol that can provide sensed data to the collection center or data hub for further processing and treatment of the patients was proposed. Here, the authors fixed zones for sending data to the zone head using distance-aware routing, and then, the zone head sent the aggregated data to the data hub wireless sensor network. It was better than the low-energy adaptive clustering hierarchy (LEACH) by 42% and than the distance-based residual energy-efficient protocol (DREEP) by 30% in energy efficiency, and stability was 58% better than LEACH and 39% than DREEP. [PERSON] [18] studies a directional diffusion routing protocol for WBANs, and establishes a gradient with a minimum hop count and the remaining energy of the node, so that it can meet the requirements of the WBANs in terms of reliability and energy consumption. This paper uses the Network Simulator (NS2) software to generate improved directional diffusion protocol (ENDD) and compares it to DD. It compares flood, DD, and ENDD. There is no similar model to our ABM model in the literature to the best of our knowledge. We also develop two new versions of DD, which we call lazy diffusion and gradient diffusion, which have the potential to reduce the energy usage, and provide us with a vehicle for investigating diffusion protocols.