Artificial intelligence and game theory controlled autonomous UAV swarms

Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself such that the swarm main-tains mobile ad-hoc network (MANET) connectivity and uniform asset distribution over an area of interest. Typical tasks for swarms using our algorithms include detection, localization and tracking of mobile EM transmitters. We present a formal analysis showing that our algorithms can guide a swarm to maintain a connected MANET, promote a uniform network spread-ing, while avoiding overcrowding with other swarm members. We also prove that they maintain MANET connectivity and, at the same time, they can lead a swarm of autonomous UAVs to follow or avoid an EM transmitter. Simulation experiments in OPNET modeler verify the results of formal analysis that our algorithms are capable of providing an adequate area coverage over a mobile EM source and maintain MANET connectivity. These algorithms are good candidates for civilian and military applications that require agile responses to the changes in dynamic environments for tasks such as detection, localization and tracking mobile EM transmitters

Performance Study of Reliable Server Pooling +

The reliable server pooling allows redundant information sources to be viewed as a single transport endpoint, and therefore is able to provide persistent connections and balanced traffic. The IETF RSerPool Working Group has proposed an architecture to implement the reliable server pooling. We conducted a number of simulation experiments with the current definitions of the RSerPool protocols to quantify their performance in both wired and wireless environments. The simulation results show that the RSerPool works well in fixed and relatively reliable environments, but its performance worsens rapidly as the networks become more unreliable or mobile. The issues we identified in wireless mobile ad-hoc networks include network partitioning, high signaling overhead, and excessive aggressiveness in handling failures. These problems are partly due to the heavy reliance of the RSerPool architecture on the reliability of the underlying network, which is unlikely to be guaranteed in a wireless mobile ad-hoc environment

Using Semicontrollable Interfaces In Testing Army Communications Protocols: Application To Mil-Std 188-220b

Testing Army communications protocols is considered for a testing environment where tester has limited degrees of controllability on applying inputs to an Implementation Under Test. The inputs fall into three categories: directly controllable, semicontrollable, or uncontrollable. A graph conversion algorithm is presented to utilize the semicontrollable inputs, thereby increasing the number of testable transitions. The research was motivated while generating tests for MIL-STD 188-220B. The number of testable transitions for 188-220B Class A--Type 1 Datalink Service module is approximately 200 without utilizing semicontrollable inputs. These 200 account for only 30% of the transitions defined in the protocol specification. The presented methodology makes it possible to increase the number of testable transitions to over 700. Combined with our previous work on testing protocols with timing constraints, the methodology allows us to generate tests free of interruptions due to timeouts, and covering more than 95% of the defined transitions in 188-220B's Type 1 Datalink Layer

Self-organization of nodes in mobile ad hoc networks using evolutionary games and genetic algorithms

In this paper, we present a distributed and scalable evolutionary game played by autonomous mobile ad hoc network (MANET) nodes to place themselves uniformly over a dynamically changing environment without a centralized controller. A node spreading evolutionary game, called NSEG, runs at each mobile node, autonomously makes movement decisions based on localized data while the movement probabilities of possible next locations are assigned by a forced-based genetic algorithm (FGA). Because FGA takes only into account the current position of the neighboring nodes, our NSEG, combining FGA with game theory, can find better locations. In NSEG, autonomous node movement decisions are based on the outcome of the locally run FGA and the spatial game set up among it and the nodes in its neighborhood. NSEG is a good candidate for the node spreading class of applications used in both military tasks and commercial applications. We present a formal analysis of our NSEG to prove that an evolutionary stable state is its convergence point. Simulation experiments demonstrate that NSEG performs well with respect to network area coverage, uniform distribution of mobile nodes, and convergence speed

Optimum Test Sequence Generation From Estelle Specifications

The recent research results from the Protocol Engineering Lab of the University of Delaware in minimum-length test generation based on Estelle specifications are summarized. The methods use models restricting the number of self-loops to be consecutively traversed for each state, and utilizing semicontrollable interfaces of the IUT to increase the number of testable transitions. The initial results show that test sequences can be successfully generated for real-life Estelle specifications, such as MILSTD 188-220B. The test sequences are free of interruptions due to unexpected timeouts. Also, the number of testable transitions is increased by 300%