Detecting Intentional AIS Shutdown in Open Sea Maritime Surveillance Using Self-Supervised Deep Learning

In maritime traffic surveillance, detecting illegal activities, such as illegal fishing or transshipment of illicit products is a crucial task of the coastal administration. In the open sea, one has to rely on Automatic Identification System (AIS) message transmitted by on-board transponders, which are captured by surveillance satellites. However, insincere vessels often intentionally shut down their AIS transponders to hide illegal activities. In the open sea, it is very challenging to differentiate intentional AIS shutdowns from missing reception due to protocol limitations, bad weather conditions or restricting satellite positions. This paper presents a novel approach for the detection of abnormal AIS missing reception based on self-supervised deep learning techniques and transformer models. Using historical data, the trained model predicts if a message should be received in the upcoming minute or not. Afterwards, the model reports on detected anomalies by comparing the prediction with what actually happens. Our method can process AIS messages in real-time, in particular, more than 500 Millions AIS messages per month, corresponding to the trajectories of more than 60 000 ships. The method is evaluated on 1-year of real-world data coming from four Norwegian surveillance satellites. Using related research results, we validated our method by rediscovering already detected intentional AIS shutdowns.Comment: IEEE Transactions on Intelligent Transportation System

Quality of Service in Virtual Cut-through Networks

This thesis explores the possibility of achieving class level and flow level Quality of Service guarantees in a Virtual Cut-Through network with a class based Quality of Service mechanism in conjunction with admission control. There is an increasing number of System Area Network technologies based on the Virtual Cut-Through principle. Many of these support Quality of Service mechanisms, but little work has been done on performing admission control in Virtual Cut-Through networks. Three different admission control algorithms for use in Virtual Cut-Through networks are proposed in this thesis. All three algorithms operate in accordance with the DiffServ philosophy, but the basis for their admission control decisions differ. The first relies on apriori knowledge of the capacity of each link, and has information about the load on each link in the network. Its decision is based on whether the links can support more traffic. The second method performs measurements at the egress of the network to ascertain whether the network can tolerate an increase in traffic with a given latency requirement. The third and final method for admission control measures the jitter of special probe packets as the basis for its decision. An evaluation of the proposed algorithms is presented through extensive simulation results. The Quality of Service properties that are studied are the ability to give bandwidth guarantees to each individual flow, and to the service class as a whole, and the latency and jitter characteristics that the traffic displays with the different admission control algorithms. Through these simulations the apparent limits of the admission control algorithms are discovered, and the range of QoS guarantees that may be achieved in Virtual Cut-Through networks becomes clear. The simulations show that throughput guarantees on the class level and the flow level are achievable, but that latency and jitter in VCT networks are hard to control. Finally, packet dropping is investigated as a method for reducing packet jitter. The results show that this method is able to reduce the jitter perceived by the network traffic, but it does not outperform some of the admission control algorithms

Dynamic Fault Tolerance with Misrouting in Fat Trees

Fault tolerance is critical for efficient utilisation of large computer systems. Dynamic fault tolerance allows the network to remain available through the occurance of faults as opposed to static fault tolerance which requires the network to be halted to reconfigure it. Although dynamic fault tolerance may lead to less efficient solutions than static fault tolerance, it allows for a much higher availability of the system. In this paper we devise a dynamic fault tolerant adaptive routing algorithm for the fat tree, a much used interconnect topology, which relies on misrouting around link faults. We show that we are guaranteed to tolerate any combination of less than num switch ports 2 link faults without the need for additional network resources for deadlock freedom. There is also a high probability of tolerating an even larger number of link faults. Simulation results show that network performance degrades very little when faults are dynamically tolerated. 1

Cost-Effective Contention Avoidance in a CMP with Shared Memory Controllers

Efficient CMP utilisation requires virtualisation. This forces multiple applications to contend for the same network resources and memory bandwidth. In this paper we study the cause and effect of network congestion with respect to traffic local to the applications, and traffic caused by memory access. This reveals that applications close to the memory controller suffer because of congestion caused by memory controller traffic from other applications. We present a simple mechanism to reduce head-of-line blocking in the switches, which efficiently reduces network congestion, increases network performance, and evens out the performance differences between the CMP applications

An Efficient, Low-Cost Routing Framework for Convex Mesh Partitions to Support Virtualisation

At the core of an efficient chip multiprocessors (CMP) is support for unicast and multicast routing, low implementation costs, and the ability to isolate concurrent applications with maximum utilization of the CMP. We present an efficient logic-based unicast and multicast routing algorithm that guarantees isolation of local application traffic within any near-convex region on the chip, and the algorithms to recognize supported partitions and configure the cores accordingly. Evaluations show that the routing algorithm has a 57 percent; more compact implementation than a recent multicast solution with the same coverage, and it achieves 5&percent; higher throughput with 13 percent; lower latency