Unmanned aerial vehicle-aided communications system for disaster recovery

Mobility models serve as the foundation for evaluating and designing airborne networks (ANs). Due to the significant impact of mobility models on the networking performance, the mobility models must realistically capture the attributes of ANs. In this paper, we present a comprehensive survey and comparative analysis of mobility models that are either adapted to or developed for AN evaluation purposes. We evaluate these mobility models based on the following metrics: adaptability, networking performance, and ability to realistically capture the mobility attributes of ANs (including high mobility, mechanical and aerodynamic constraint, and safety requirements). To provide a deeper understanding and facilitate the selection and configuration of these mobility models, we also evaluate them based on randomness levels and associated applications.

A Survey and Analysis of Mobility Models for Airborne Networks

The coordination between unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) is a proactive research topic whose great value of application has attracted vast attention. This paper outlines the motivations for studying the cooperative control of UAVs and UGVs, and attempts to make a comprehensive investigation and analysis on recent research in this field. First, a taxonomy for classification of existing unmanned aerial and ground vehicles systems (UAGVSs) is proposed, and a generalized optimization framework is developed to allow the decision-making problems for different types of UAGVSs to be described in a unified way. By following the proposed taxonomy, we show how different types of UAGVSs can be built to realize the goal of a common task, that is target tracking, and how optimization problems can be formulated for a UAGVS to perform specific tasks. This paper presents an optimization perspective to model and analyze different types of UAGVSs, and serves as a guidance and reference for developing UAGVSs.

Coordination Between Unmanned Aerial and Ground Vehicles: A Taxonomy and Optimization Perspective

A system and method for testing line state. Traffic through a communications path is determined. A test vector is generated. Attributes of the test vector simulate the traffic. The test vector is communicated to one or more end devices. Performance information for each of the attributes of the test vector is measured. A performance map utilizing the attributes and the performance information is generated.

System and method for a testing vector and associated performance map

Multiple unmanned air/ground vehicles heterogeneous cooperation is a novel and challenging filed. Heterogeneous cooperative techniques can widen the application fields of unmanned air or ground vehicles, and enhance the effectiveness of implementing detection, search and rescue tasks. This paper mainly focused on the key issues in multiple unmanned air/ground vehicles heterogeneous cooperation, including heterogeneous flocking, formation control, formation stability, network control, and actual applications. The main problems and future directions in this field were also analyzed in detail. These innovative technologies can significantly enhance the effectiveness of implementing complicated tasks, which definitely provide a series of novel breakthroughs for the intelligence, integration and advancement of future robot systems.

Unmanned air/ground vehicles heterogeneous cooperative techniques: Current status and prospects

In this paper we address the problem of providing full connectivity to disconnected ground MANET nodes by dynamically placing unmanned aerial vehicles (UAVs) to act as relay nodes. We provide a heuristic algorithm to find the minimal number of such aerial vehicles required to provide fall connectivity and find the corresponding locations for these aerial platforms (UAVs). We also track the movement of the ground nodes and update the location of the UAVs. We describe a communication framework that enables the ground nodes to communicate with its peer ground nodes as well as the UAVs that act as relay nodes. The communication architecture is designed to work with existing MANET routing protocols.

Providing full connectivity in large ad-hoc networks by dynamic placement of aerial platforms

This paper focuses on the performance and scalability of mobile, base-station-oriented wireless networks, which have been the subject of research and development projects sponsored by the Defense Advanced Research Projects Agency. The background and rationale for such networks is presented as well as performance and scalability analyses of their routing, mobility, and quality of service models. Using systems-oriented, large-scale discrete event simulation, both performance scalability and complexity scalability are analyzed. Performance scalability addresses the effect of network size on system performance. Complexity scalability, in this case, consists of communication complexity (i.e., amount of control information exchanged to create and maintain network connectivity). Results confirmed that the scalability of base station oriented networks using the routing, and mobility model, and the quality of service models enhanced performance, using over 2,000 fully dynamic hosts and routers.

Performance and scalability of mobile wireless base-station-oriented networks

In a network that includes static bandwidth and dynamic bandwidth links, traffic flow at the OSI network layer is simulated at a traffic-flow level at interfaces to fixed bandwidth links, and simulated at a discrete-packet level at interfaces to dynamic bandwidth links. The resultant discrete-packet reception events at the receiving interface(s) of the dynamic bandwidth link are processed to determine the effective bandwidth/throughput of the link, as well as the allocation of this bandwidth among the individual flows through the link. The discrete-packet level receptions are used to reconstruct the parameters of the traffic flow at the network layer of the receiving interface, and this determined traffic flow is simulated accordingly at the next link, depending upon whether the next link is a static or dynamic bandwidth link.

Modeling and simulating flow propagation in dynamic bandwidth systems

Embodiments provide systems, methods, and computer program products for inferring node and link information from traceroute data in order to generate topology information A system receives traceroute data for a data packet that traverses a path from a source to a destination The system infers port types for the addresses in the traceroute data and groups subsets of the addresses in the traceroute data into logical nodes based on neighbor relationships demonstrated in backward and forward neighbors sets The system then generates node and link information based on the inferred and grouped information

Network topology generation using traceroute data

A transmission channel allocation scheme for a multi-hop wireless network takes into account the priority of users, particular application requirements, applicable contractual requirements, and other factors. The channel allocation scheme determines which nodes can share a common channel for transmission without interference, and distinguishes between resources that must be dedicated to each node based on the requirements associated with each node, and the resources that are dynamically provided to each node, based on the current traffic demand. Additionally, resources that are not required to satisfy explicit requests are allocated among the nodes, thereby allowing nodes to sometimes avoid the delays associated with the access request process.

Karthikeyan Chandrashekar

Papers

Providing full connectivity in large ad-hoc networks by dynamic placement of aerial platforms

Performance and scalability of mobile wireless base-station-oriented networks

Modeling and simulating flow propagation in dynamic bandwidth systems

Network topology generation using traceroute data

Dedicated and priority based allocation in multi-hop wireless systems