Topology-Based Routing Protocols and Mobility Models for Flying Ad Hoc Networks: A Contemporary Review and Future Research Directions

Telecommunications among unmanned aerial vehicles (UAVs) have emerged recently due to rapid improvements in wireless technology, low-cost equipment, advancement in networking communication techniques, and demand from various industries that seek to leverage aerial data to improve their business and operations. As such, UAVs have started to become extremely prevalent for a variety of civilian, commercial, and military uses over the past few years. UAVs form a flying ad hoc network (FANET) as they communicate and collaborate wirelessly. FANETs may be utilized to quickly complete complex operations. FANETs are frequently deployed in three dimensions, with a mobility model determined by the work they are to do, and hence differ between vehicular ad hoc networks (VANETs) and mobile ad hoc networks (MANETs) in terms of features and attributes. Furthermore, different flight constraints and the high dynamic topology of FANETs make the design of routing protocols difficult. This paper presents a comprehensive review covering the UAV network, the several communication links, the routing protocols, the mobility models, the important research issues, and simulation software dedicated to FANETs. A topology-based routing protocol specialized to FANETs is discussed in-depth, with detailed categorization, descriptions, and qualitatively compared analyses. In addition, the paper demonstrates open research topics and future challenge issues that need to be resolved by the researchers, before UAVs communications are expected to become a reality and practical in the industry.

Mover

Human mobility models typically produce mobility data to capture human mobility patterns individually or collectively based on real-world observations or assumptions, which are essential for many use cases in research and practice, e.g., mobile networking, autonomous driving, urban planning, and epidemic control. However, most existing mobility models suffer from practical issues like unknown accuracy and uncertain parameters in new use cases because they are normally designed and verified based on a particular use case (e.g., mobile phones, taxis, or mobile payments). This causes significant challenges for researchers when they try to select a representative human mobility model with appropriate parameters for new use cases. In this paper, we introduce a MObility VERification framework called MOVER to systematically measure the performance of a set of representative mobility models including both theoretical and empirical models based on a diverse set of use cases with various measures. Based on a taxonomy built upon spatial granularity and temporal continuity, we selected four representative mobility use cases (e.g., the vehicle tracking system, the camera-based system, the mobile payment system, and the cellular network system) to verify the generalizability of the state-of-the-art human mobility models. MOVER methodically characterizes the accuracy of five different mobility models in these four use cases based on a comprehensive set of mobility measures and provide two key lessons learned: (i) For the collective level measures, the finer spatial granularity of the user cases, the better generalization of the theoretical models; (ii) For the individual-level measures, the lower periodic temporal continuity of the user cases, the theoretical models typically generalize better than the empirical models. The verification results can help the research community to select appropriate mobility models and parameters in different use cases.

Understanding the Heterogeneity of Human Mobility Patterns: User Characteristics and Modal Preferences

Characterizing individual mobility is critical to understand urban dynamics and to develop high-resolution mobility models. Previously, large-scale trajectory datasets have been used to characterize universal mobility patterns. However, due to the limitations of the underlying datasets, these studies could not investigate how mobility patterns differ over user characteristics among demographic groups. In this study, we analyzed a large-scale Automatic Fare Collection (AFC) dataset of the transit system of Seoul, South Korea and investigated how mobility patterns vary over user characteristics and modal preferences. We identified users’ commuting locations and estimated the statistical distributions required to characterize their spatio-temporal mobility patterns. Our findings show the heterogeneity of mobility patterns across demographic user groups. This result will significantly impact future mobility models based on trajectory datasets.

Drifting 3D Underwater Wireless Sensor Networks for Pollution Monitoring

<p>Increasing demands by a growing population for food and oil have resulted in synchronous rises in the past 40 years of aquaculture and offshore oil drilling. Growth in these industries has highlighted the potential crippling impacts of coastal pollution, with marine farms likely to be susceptible to damage from harmful algal blooms and oil platforms to cause oil spills, as headlined by the 2010 Deepwater Horizon incident in the Gulf of Mexico. Drifting underwater wireless sensor networks (UWSNs) represent a technology that can greatly enhance our understanding of such processes. Consisting of a swarm of untethered sensor nodes, an UWSN can be deployed over a large segment of the feature. The feature is carried through to different positions by underwater currents, the nodes, also drifting with the currents, are able to follow it and track it. To enable UWSNs, work is proceeding at multiple laboratories throughout the world on the design of localization, medium access control and routing protocols that can adapt to the problem that a drifting network topology has over short time intervals: frequent neighbour changes. However, the long-term impact that current drift has on 3D drifting UWSNs is poorly understood. Current mobility models used to generate the motion of drifting nodes in simulation do not reflect how devices in real-life will disperse in water. At present, UWSN protocol schemes are evaluated in simulations where the current mobility of nodes is generated by unrealistic land-based random waypoint and other stochastic mobility models, or coarsely resolved numerical ocean models. Recently, a physically-inspired current mobility model known as MCM has been proposed. This is only defined along the water's surface, in 2D, however, and 3D extensions of this model have been simplistic and arbitrary. The lack of realistic 3D current mobility models motivates this thesis to develop one so that the simulated evolution of UWSNs can more accurately reflect real-life. A consideration of the oceanographic data on which MCM is based is used to derive a 3D extension of the model that reflects observed features of the Gulf Stream current. The speed of the current declines with depth. This model is utilized to advect a drifting UWSN in an oil plume monitoring scenario and study the performance of two pressure routing protocols, Depth Based Routing (DBR) and HydroCast, over time. Previously, these schemes had only been validated in unrealistic stochastic and depth-invariant mobility models and their time-averaged performances were only reported. Our findings show that 3D UWSNs cannot expect to stay connected and functioning if nodes only passively drift with the currents, with results demonstrating that a fully connected network can be so dispersed after three hours that no paths to sinks exist at all. Nodes must be equipped with some form of mobility to prevent their being separated and carried out of the monitoring region. Autonomous underwater vehicles (AUVs) capable of omnidirectional motion are expensive however, and instead UWSNs consisting of pro ling floats are considered in this thesis. Floats can move up and down by adjusting their buoyancy, which also allow them to move in 3D by exploiting water layers that are flowing in different directions to proceed along a desired heading. Recently, promising results in 2D path planning and formation control of floats have been presented. However, these works consider the floats to have infinite vertical velocity whereas in reality this is around 0:3 metres per second. In this thesis, a practical node movement scheme is proposed for extending the coverage lifetime of a 3D UWSN consisting of floats. By accounting for the finite profiling velocity of floats, the scheme is able to position nodes at coverage holes with greater precision than existing 2D strategies. The scheme's performance is analysed by simulations. The results support the use of floats for achieving partial coverage, which can achieve similar levels of coverage as an AUV strategy while requiring less cost to deploy. In determining the lifetime of the network, we find that both energy and dispersion limit the lifetime of the network. Without propulsion, the nodes are carried out of and cease to cover the monitoring region. Using mobility to remain with the region, at the end of a 5 day mission duration floats have had to use up some or almost all of their battery capacity in profiling.</p>