An energy aware scheme for layered chain in underwater wireless sensor networks using genetic algorithm

Extending the network lifetime is a very challenging problem that needs to be taken into account during routing data in wireless sensor networks in general and particularly in underwater wireless sensor networks (UWSN). For this purpose, the present paper proposes a multilayer chain based on genetic algorithm routing (MCGA) for routing data from nodes to the sink. This algorithm consists to create a limited number of local chains constructed by using genetic algorithm in order to obtain the shortest path between nodes; furthermore, a leader node (LN) is elected in each chain followed by constructing a global chain containing LNs. The selection of the LN in the closest chain to the sink is as follows: Initially, the closest node to sink is elected LN in this latter because all nodes have initially the same energy value; then the future selection of the LN is based on the residual energy of the nodes. LNs in the other chains are selected based on the proximity to the previous LNs. Data transmission is performed in two steps: intra-chain transmission and inter-chain transmission. Furthermore, MCGA is simulated for different scenarios of mobility and density of nodes in the networks. The performance evaluation of the proposed technique shows a considerable reduction in terms of energy consumption and network lifespan

A Survey of Routing Issues and Associated Protocols in Underwater Wireless Sensor Networks

Underwater Wireless Sensor Network is newly emerging wireless technology in which small size sensors with limited energy, limited memory and bandwidth are deployed in deep sea water and various monitoring operation like tactical surveillance, environmental monitoring and data collection are performed through these tiny sensor. Underwater Wireless Sensor Network is used for exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance system and unmanned underwater vehicles. Sensor node consist of small memory, central processing unit and antenna. Underwater network is much different from terrestrial sensor network as radio waves cannot be used in Underwater Wireless Sensor Network. Acoustic channels are used for communication in deep sea water. Acoustic Signals carries with itself many limitation. Such as Limited bandwidth, higher end to end delay, network path loss, higher propagation delay and dynamic topology. Usually these limitation results in higher energy consumption with less number of packets delivered. The main aim now a days is to operate sensor node having smaller battery for a longer time in network. This survey has discussed the state of the art Localization based and Localization free routing protocols. Routing associated issues in the area of Underwater Wireless Sensor Network has also been discussed

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Self-organizing Fast Routing Protocols for Underwater Acoustic Communications Networks

To address this problem, in this thesis we propose a cross-layer proactive routing initialization mechanism that does not require additional measurements and, at the same time, is energy efficient. Two routing protocols are proposed: Self-Organized Fast Routing Protocol for Radial Underwater Networks (SOFRP) for radial topology and Self-organized Proactive Routing Protocol for Non-uniformly Deployed Underwater Networks (SPRINT) for a randomly deployed network. SOFRP is based on the algorithm to recreate a radial topology with a gateway node, such that packets always use the shortest possible path from source to sink, thus minimizing consumed energy. Collisions are avoided as much as possible during the path initialization. The algorithm is suitable for 2D or 3D areas, and automatically adapts to a varying number of nodes. In SPRINT the routing path to the gateway is formed on the basis of the distance, measured by the signal strength received. The data sending node prefers to choose the neighbor node which is closest to it. It is designed to achieve high data throughput and low energy consumption of the nodes. There is a tradeoff between the throughput and the energy consumption: more distance needs more transmission energy, and more relay nodes (hops) to the destination node affects the throughput. Each hop increases the packet delay and decreases the throughput. Hence, energy consumption requires nearest nodes to be chosen as forwarding node whereas the throughput requires farthest node to be selected to minimize the number of hops. Fecha de lectura de Tesis Doctoral: 11 mayo 2020Underwater Wireless Sensor Networks (UWSNs) constitute an emerging technology for marine surveillance, natural disaster alert and environmental monitoring. Unlike terrestrial Wireless Sensor Networks (WSNs), electromagnetic waves cannot propagate more than few meters in water (high absorption rate). However, acoustic waves can travel long distances in underwater. Therefore, acoustic waves are preferred for underwater communications, but they travel very slow compare to EM waves (typical speed in water is 1500 m/s against 2x10^8 m/s for EM waves). This physical effect makes a high propagation delay and cannot be avoided, but the end-to-end packet delay it can be reduced. Routing delay is one of the major factors in end-to-end packet delay. In reactive routing protocols, when a packet arrives to a node, the node takes some time to select the node to which the data packet would be forwarded. We may reduce the routing delay for time-critical applications by using proactive routing protocols. Other two critical issues in UWSNs are determining the position of the nodes and time synchronization. Wireless sensor nodes need to determine the position of the surrounding nodes to select the next node in the path to reach the sink node. A Global Navigation Satellite System (GNSS) cannot be used because of the very short underwater range of the GNSS signal. Timestamping to estimate the distance is possible but the limited mobility of the UWSN nodes and variation in the propagation speed of the acoustic waves make the time synchronization a challenging task. For these reasons, terrestrial WSN protocols cannot be readily used for underwater acoustic networks