# Energy-Aware Forwarding Strategies for Delay Tolerant Network Routing Protocols
## 1 Introduction  
Wireless Sensor Networks (WSNs) are an active area of research that has gained significant attention in the past decade. WSNs are commonly used for monitoring indoor or outdoor environments and relaying sensed data to a database via a gateway. An important and challenging application of WSNs is monitoring wildlife where attached sensors on the animals can track movement with high temporal and spatial resolution [1]. A WSN node has three components, viz., sensing for measuring properties of the environment, processing for storing-processing the data and wireless communication for transmitting the sensed data to a Base Station (BS) or data sink [2]. WSN nodes can track the location and activity of those animals to investigate their behaviour. However, for small animals, these sensors must be lightweight and necessarily have limited energy available. Therefore, new approaches are needed to design WSN system architectures and protocols to maximize the data delivery, while considering available energy. WSN nodes are typically powered with batteries. Power sources such as solar panels can be added to the nodes to replenish its energy. A key issue is how to use limited energy resources within the WSN node in an effective and efficient way. Since externally recharging or replacing the battery is infeasible in some applications, efficient utilization of energy resources and optimization techniques are required to prolong the network lifetime. WSN nodes spend a large proportion of their energy on communicating data back to a BS. While extensive related work exists for WSN protocols, the most relevant background is in the area of an Intermittently Connected Network (ICN), in which there is no end-to-end connection between the source and the destination. Specifically, a networking paradigm called Delay Tolerant Networking (DTN) has been proposed to address challenges such as communication disruptions and delays in ICNs [3]. The main challenge of DTNs is limited energy resources that constrain nodes to local area communications, which means the data cannot be continuously streamed to a remote base station. DTN is an intermittently connected (wireless) mobile ad hoc network (MANET), which provides no guarantees of end-to-end connectivity between the source and the destination. For successful data transmission over the network in the presence of delay and interruption, cooperation between nodes is required [4]. Routing protocols for conventional networks and MANETs are inadequate to provide successful data transmission in DTNs owing to a lack of persistent end-to-end connectivity. To overcome intermittent connectivity, DTNs use a common method called the store-carry-forward approach for data delivery [5]. In this approach, messages can be transferred between the source and the destination in several hops. When the message is generated, it will be stored in the buffer of the source node then forwarded to other encountered nodes. When the next node is not immediately available, then the message would be stored in a buffer and carried until an appropriate communication opportunity arises. This is repeated until the message reaches its destination. The main challenges under investigation are limited available energy resources and limited node connectivity in long-term animal tracking applications. While previous researchers investigated energy consumption of DTN protocols, they have not addressed the performance of the algorithms in terms of available energy and have not considered energy harvesting. With energy harvesting, the energy budget available for DTN protocols is dynamic, which requires adaptive protocols. How to reconfigure forwarding protocols in DTNs as the energy budget changes is challenging. To the best of the authors' knowledge, there is no previous work on energy-aware protocols for DTNs. To address this challenge, three new generalized strategies are examined to augment existing routing protocols with the consideration of energy awareness, in terms of energy harvesting and energy storage.