Robust and reliable routing decisions are enablers to minimize redundancy and to optimize throughput. This might be nice to have in non-time critical transmissions but required in QoS related data delivery, like VoIP and video calls. MANETs, are error-prone considering their wireless and mobile nature. Relying on an up-to-date and complete topology overview makes routing easier and more efficient and also facilitates mentioned routing goals. MANETs must consider interference if routing follows Ford-Fulkerson's objective to compute maximum throughput. However, preconditions must be met before one optimizes flow distributions. Such major precondition in the field of MANETs is an algorithm that constructs a graph equal to the actual MANET topology. This graph must be complete and almost instant in terms of connections and construction to guarantee that each node's position does not deviate from its actual. We centralize the routing, inspired by SDN advancements, to a controller that obtains the topology by triggering an algorithm, called RFTKR. Nodes assemble a tree, having the controller as their root while gathering neighborhood information. Afterwards, they convey their adjacent lists towards the controller. We present a proof-of-concept evaluation with microcontrollers and discuss the scalability of RFTKR with an extensive simulation.
With an increased adoption of uninhabited platforms in tactical environments such as search and rescue operations the proliferation of tactical assets equipped with advanced computing, sensing and networking capabilities becomes complex to manage. Edge/tactical cloud architectures provide the necessary automation processes for managing and scaling services and applications deployed across a larger number of platforms. However, size weight and power restrictions on tactical platforms leads to a heterogeneity in deployed infrastructure for both compute capabilities and available network bearers which raises complexities that need to be addressed by the underlying cloud infrastructure. In this paper we propose and demonstrate a heterogeneous cloud architecture used for a search and rescue training operation conducted by Surf Life Saving South Australia in collaboration with the Defence Science and Technology Group.
The main technologies currently used for Space Domain Awareness (SDA) are radar, optical telescope, and reflected laser tracking. These technologies alone cannot provide the comprehensive and persistent SDA that is becoming increasingly vital due to the increase in space traffic and the resulting higher probability of collisions. Passive Radio Frequency (RF) sensing is a promising technology to support the SDA mission, particularly due to its ability to operate 24/7 in all weather conditions. By observing the Doppler shift and angle of arrival of signals transmitted by satellites, their orbit can be determined. This paper describes an algorithm for Doppler estimation and demonstrates its efficacy for Low Earth Orbit (LEO) satellites. The algorithm can effectively estimate Doppler for both continuous and intermittent satellite transmissions.
Emulation environments are an effective approach to experimenting with and evaluating network protocols, algorithms, and components. However, implementing a complete waveform for an emulation environment requires a significant effort. This paper describes two simplified approaches to implement and include a Synchronized Cooperative Broadcast (SCB) waveform within the Anglova scenario and the EMANE network emulation framework. The result is two different implementations of SCB, having different levels of abstraction regarding the specific details of SCB and offering different capabilities. The SCB implementations are tested and compared in the militarily-realistic Anglova scenario. The performance of SCB is also theoretically estimated within the Anglova scenario as a baseline for comparison purposes. The results show that the approaches taken to emulate SCB within EMANE and the Anglova scenario perform as expected when compared to the theoretical results.
To minimise the probability of detection of a military network the power received at a distant point should be reduced. This can be achieved in various ways. Topology control has been shown to be able to reduce transmission power in these networks, lowering the network's RF power footprint and so the probability of detection. This paper looks at how positioning autonomous vehicles can also be used to further reduce the received power at a adversary position and hence the probability of detection. An algorithm for this positioning is described and results presented.
