Energy-aware peering routing protocol for indoor hospital body area network communication

The recent research in Body Area Networks (BAN) is focused on making its communication more reliable, energy efficient, secure, and to better utilize system resources. In this paper we propose a novel BAN network architecture for indoor hospital environments, and a new mechanism of peer discovery with routing table construction that helps to reduce network traffic load, energy consumption, and improves BAN reliability. We have performed extensive simulations in the Castalia simulation environment to show that our proposed protocol has better performance in terms of reduced BAN traffic load, increased number of successful packets received by nodes, reduced number of packets forwarded by intermediate nodes, and overall lower energy consumption compared to other protocols

Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks

Combined Coverage Area Reporting and Geographical Routing in Wireless Sensor-Actuator Networks for Cooperating with Unmanned Aerial Vehicles

In wireless sensor network (WSN) applications with multiple gateways, it is key to route location dependent subscriptions efficiently at two levels in the system. At the gateway level, data sinks must not waste the energy of the WSN by injecting subscriptions that are not relevant for the nodes in their coverage area and at WSN level, energy-efficient delivery of subscriptions to target areas is required. In this paper, we propose a mechanism in which (1) the WSN provides an accurate and up-to-date coverage area description to gateways and (2) the wireless sensor network re-uses the collected coverage area information to enable efficient geographical routing of location dependent subscriptions and other messages. The latter has a focus on routing of messages injected from sink nodes to nodes in the region of interest. Our proposed mechanisms are evaluated in simulation

Analyzing the energy efficient path in Wireless Sensor Network using Machine Learning

As the sensor nodes are energy constrained, an important factor for successful implementation of a Wireless Sensor Network (WSN) is designing energy efficient routing protocols and improving its lifetime. Network life time has been described in many ways such as   the time when the network lost its connectivity or the time when the first node gets disconnected. Whatever may be the description, the main focus of many researchers is to design algorithms that enable the network to perform continuously for a longer duration. So, improving the energy efficiency and increasing the network lifetime are the two key issues in WSN routing. Because of the intelligent nature and learning capacity, reinforcement learning (RL) algorithms are very suitable for complex distributed problems such as routing in WSN. RL is a subclass of Machine Learning techniques.  It can be used to choose the best forwarding node for transmitting data in multipath routing protocols. A survey has been made in this paper regarding the implementation of RL techniques to solve routing problems in WSN. Also, an algorithm has been proposed which is a modified version of original Directed Diffusion (DD) protocol. The proposed algorithm uses Q-learning technique which is a special class of RL. Also, the significance of balancing the exploration and exploitation rate during path finding in Q-learning has been demonstrated using an experiment implemented in python. The result of the experiment shows that if exploration-exploitation rate is properly balanced, it always yields an optimum value of the reward and thus path found from source to the destination is efficient