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The UAV-Assisted Wireless Ad hoc Network
Published in Suhel Ahmad Khan, Rajeev Kumar, Omprakash Kaiwartya, Mohammad Faisal, Raees Ahmad Khan, Computational Intelligent Security in Wireless Communications, 2022
Mohd Asim Sayeed, Raj Shree, Mohd Waris Khan
A wireless ad hoc network routing provides for the mechanism for link discovery and maintenance of routes to and from all the nodes in the topology. When the speed of the participating node increases, the wireless links are broken frequently and new links are formed. A wireless ad hoc network deals with these fluctuations by transmitting control packets such as route request and hello packets. When new links are discovered the routing table is promptly updated and broken links are removed. With a high degree of mobility, the traditional routing barely copes, as an efficient handover mechanism does not exist. A recent trend in predictive routing protocols tries to handle this situation by using a predictive scheme. The wireless ad hoc network nodes take into account the position and velocity of a destination node to predict the route from source to destination. Predictive routing techniques are most suited routing techniques for using a UAV as a mobile base station (MB) or a mobile relay (MR).
Taxonomy of Mobility Models
Published in Khaleel Ahmad, Nur Izura Udzir, Ganesh Chandra Deka, Opportunistic Networks, 2018
Mobility models are used to represent the movement pattern of the nodes and how its location, acceleration and velocity changes over time in wireless ad hoc networks (WANETs); this in turn affects the performance of network protocols, applications and systems. Mobility models accurately exhibit the behavior of the mobile users’ mobility in an OppNets, which is decisive for the evaluation of protocols for a specific type of mobility scenario. They are studied to predict the future state of network topology, control route reconstruction, minimize disruptions, reduce overheads, eliminate transmission of control packets and find routes in a timely manner. There are various characteristics/properties pertaining to the users’ mobility. On the basis of behavioral patterns, human mobility can be categorized into three levels: strategic, tactical and operational (Hoogendoorn and Bovy, 2004). The strategic level describes the daily movement patterns of an individual, such as shopping, going to work or engaging in outdoor activities. The tactical level focuses on scheduling activities and route choice based on the set of activities (i.e., which is the shortest or fastest path to the destination) and the availability of time depending on the environmental factors (e.g., obstacles on the path or traffic congestion). The operational level describes the physical process of human movement (Hoogendoorn and Bovy, 2004). This level considers walking or driving speed, interaction with other nodes due to collision avoidance and queuing.
Wireless Networks
Published in Jiguo Yu, Xiuzhen Cheng, Honglu Jiang, Dongxiao Yu, Hierarchical Topology Control for Wireless Networks, 2018
Jiguo Yu, Xiuzhen Cheng, Honglu Jiang, Dongxiao Yu
Different from the technology of traditional wireless communication networks, wireless self-organizing networks do not need to support fixed equipment. In ad hoc work, the node working as the user terminal is self-networking and communicates with other user nodes for data forwarding. This kind of network form breaks through the geographical limitation of the traditional wireless cellular network and can be deployed more quickly, conveniently, and efficiently. It is also suitable for the communication needs of some emergency situations, such as individual soldier communication systems on the battlefield. However, wireless ad hoc networks are also limited by the network bandwidth, poor support for real-time services, and low security. The ad hoc network is the foundation and predecessor of the WSN and WMN.
Investigation of wireless sensor node power consumption profile powered by heterogeneous hybrid energy harvesters with EPDD management algorithm
Published in International Journal of Electronics, 2019
Ali M. Abdal-Kadhim, Kok S. Leong
Typically, wireless sensor nodes are autonomous, low-cost and low-power sensors that are able to communicate with each other in a wireless ad-hoc network aspect. These sensor nodes have very limited computing capability and memory and operate with finite power (Varun & Mahesh, 2019). However, the wireless sensor network (WSN) is different from the conventional wireless ad-hoc networks, which normally consists of hundreds or thousands of sensor nodes. These sensor nodes are capable of producing measurable responses to the environment physical stimulus changes such as frequency, light, gases, or temperature. The main reason for utilising such wireless sensors is easy to construct an ad-hoc wireless network that is able to perform distributed monitoring tasks, particularly for applications like structural health monitoring (Adam et al., 2017), smart grid (Sinan, Ugur, Melike, Bulent, & Cagri, 2017), healthcare monitoring (Vijayalakshmi & Muruganand, 2012; Vo, Do, Mai, & Le, 2017), smart environment monitoring (Prabhu, Balakumar, & Antony, 2017) and so on