Algorithms for distributed systems under imperfect status information

A recent trend in computer system design has been to distribute the tasks among the multiple processors and a wide variety of computer systems can be proposed. The potential benefits of this trend include modular expansion, increased cost-performance, availability, and reliability. To fully exploit these potential advantages, the efficient control of the resources is essential. In this dissertation, we attack some of important problems which arise in the distributed system environment. Central to this dissertation is the issue of imperfect information, and how to make control decisions in the face of imperfect information. While a great deal of attention has been lavished on token-ring systems over the past few years, little has been said about synthesizing protocols to satisfy complex priority requirements. We present an algorithm that partly fills this gap. It is a simple, adaptive algorithm which can ensure prescribed differential service to the various job classes. Applications include maintaining a throughput differential between job classes, integrating voice and data packets, and maintaining mean waiting times of the various job classes in prescribed ratios. Such an algorithm is likely to be useful whenever disparate traffic classes must coexist on the same ring. We also study the effect of the decay of status information on the goodness of load balancing algorithms. We study empirically the relationship between the characterizing parameters of a very simple model using the join-the-shortest-queue algorithm. This is done using regression analysis. Our results indicate that these parameters--number of queues, status update rate, and coefficient of variation for the job service time--are far from orthogonal in their impact on system performance. We have empirically obtained expressions for the sensitivity of the response time to the characterizing parameters. Designers can use this expression to determine appropriate status update rates. We also present a comparison of some simple distributed load balancing algorithms which update status information regularly with those which do so adaptively. The adaptive algorithms only broadcast status when it changes by more than a threshold. They are almost as simple to implement as algorithms which periodically exchange status information, and provide better performance. Finally, we introduce a simple, adaptive buffer allocation algorithm. We study the performance of an adaptive buffer allocation algorithm in the face of the imperfect status information for the control of distributed systems in which multiple classes of customers contend for a finite buffer which is served by a single server. We believe that this algorithm is especially useful when the number of the classes changes dynamically, or when the input loading changes dynamically. The adaptive algorithm is especially useful when buffer sizes are small

Reservation-Based 3D Intersection Traffic Control System for Autonomous Unmanned Aerial Vehicles

We present a three-dimensional (3D) intersection traffic management platform for small autonomous Unmanned Aerial Vehicles (UAVs), particularly quadcopters, in urban airspace. Assuming many autonomous UAVs are approaching a shared airspace, where UAVs have varying sources and destinations, we propose a system model for a 3D intersection that aims to provide safe and systematic management of UAVs. We also devised a scheduling scheme to ensure that the intersection is efficiently utilized and that there are no collisions among the UAVs in the intersection. The scheduling scheme applies the reservation-based approach, which is sensitive to the sequence of the UAVs in scheduling, thus genetic algorithm is used to determine the best sequence of the UAVs. Simulations were performed to evaluate the efficiency of the system. We also show through the simulations that our scheduling scheme reduces the UAVs’ average time in the system by 27 percent compared with when the UAVs are scheduled in a first-come, first-served manner for the highly crowded intersection

Velocity Obstacle Based 3D Collision Avoidance Scheme for Low-Cost Micro UAVs

An unmanned aerial vehicle (UAV) must be able to safely reach its destination even, when it can only gather limited information about its environment. When an obstacle is detected, the UAV must be able to choose a path that will avoid collision with the obstacle. For the collision avoidance scheme, we apply the velocity obstacle approach since it is applicable even with the UAV’s limited sensing capability. To be able to apply the velocity obstacle approach, we need to know the parameter values of the obstacle such as its size, current velocity and current position. However, due to the UAV’s limited sensing capability, such information about the obstacle is not available. Thus, by evaluating sensor readings, we get the changes in the possible positions of the obstacle in order to generate the velocity obstacle and make the UAV choose a collision-free trajectory towards the destination. We performed simulation on different obstacle movements and the collision-free trajectory of the UAV is shown in the simulation results

An Obstacle Avoidance Scheme Maintaining Connectivity for Micro-Unmanned Aerial Vehicles

This paper suggests an obstacle avoidance scheme that enables a group of micro-UAV (Unmanned Aerial Vehicles) to avoid colliding with an obstacle that is found in the course of the flight. This scheme considers a method for UAVs to avoid colliding with such obstacles and a plan of action for when the UAVs in the group lose connectivity during flight. The main goal is for UAVs to reach the target without colliding with any obstacles. To achieve this goal, directly after the UAVs avoid the obstacle at a raised altitude above it, they fly at a higher altitude for a while and then descend to their original height. When this approach is judged to be inefficient because the height of the obstacle is too high, the UAVs divide into two groups and move to either side of it while continuing to fly at the same altitude, thereby avoiding the obstacle. Afterwards, they gather into one group again. We verify the proposed scheme and do the performance evaluation by ns-2