Hyunyoung Lee

Finding available parking spaces made easy

We discuss the problem of predicting the number of available parking spaces in a parking lot. The parking lot is modeled by a continuous-time Markov chain, following Caliskan, Barthels, Scheuermann, and Mauve. The parking lot regularly communicates the number of occupied spaces, capacity, arrival and parking rate through a vehicular network. The navigation system in the vehicle has to compute from these data the probability of an available parking space upon arrival. We derive a structural result that considerably simplifies the computation of the transition probabilities in the navigation system of the vehicle.

Location tracking using quorums in mobile ad hoc networks

Abstract We explore applications of quorum systems to the problem of tracking locations of mobile users in mobile ad hoc networks (MANETs). The location tracking system uses biquorum systems, a generalization of traditional quorum systems. We performed extensive simulations of the location tracking system. The simulation results show that our strict biquorum implementation has better performance than the traditional strict quorum implementations. Moreover, our results show that randomized dynamic quorum implementations have better overall performance than strict (bi)quorum implementations.

A distributed pool architecture for genetic algorithms

The genetic algorithm (GA) paradigm is a well-known heuristic for solving many problems in science and engineering. As problem sizes increase, a natural question is how to exploit advances in distributed and parallel computing to speed up the execution of GAs. This paper proposes a new distributed architecture for GAs, based on distributed storage of the individuals in a persistent pool. Processors extract individuals from the pool in order to perform the computations and then insert the resulting individuals back into the pool. Unlike previously proposed approaches, the new approach is tailored for distributed systems in which processors are loosely coupled, failure-prone and can run at different speeds. Proof-of-concept simulation results are presented indicating that the approach can deliver improved performance due to the distribution and tolerates a large fraction of crash failures.

Multiwriter Consistency Conditions for Shared Memory Registers

Regularity is a shared memory consistency condition that has received considerable attention. Lamports original definition of regularity assumed a single-writer model, however, and is not well defined when the shared register may have multiple writers. In this paper, we consider four possible definitions of multiwriter regularity. The definitions are motivated by variations on a quorum-based algorithm schema for implementing them. We study the relationships between these definitions and a number of other well-known consistency conditions, and we give a partial order describing the relative strengths of these consistency conditions. Finally, we provide a practical context for our results by studying the correctness of two well-known algorithms for mutual exclusion under each of our proposed consistency conditions.

Applications of probabilistic quorums to iterative algorithms

Presents a definition of a read-write register that sometimes returns out-of-date values, shows that the definition is implemented by the probabilistic quorum algorithm of D. Malkhi et al. (1997), and shows how to program with such registers using the framework of A. U/spl uml/resin and M. Dubois (1990). Consequently, existing iterative algorithms for an interesting class of problems (including finding shortest paths, constraint satisfaction and transitive closure) converge with high probability if executed in a system in which the shared data is implemented with registers satisfying the new definition. Furthermore, the algorithms in this framework inherit positive attributes concerning load and availability from the underlying register implementation. A monotone version of the new register definition is specified and implemented; it can provide improved expected convergence time and message complexity for iterative algorithms.

Randomized registers and iterative algorithms

Abstract.We present three different specifications of a read-write register that may occasionally return out-of-date values - namely, a (basic) random register, a P-random register, and a monotone random register. We show that these specifications are implemented by the probabilistic quorum algorithm of Malkhi, Reiter, Wool, and Wright, and we illustrate how to program with such registers in the framework of Bertsekas, using the notation of Üresin and Dubois. Consequently, existing iterative algorithms for a significant class of problems (including solving systems of linear equations, finding shortest paths, constraint satisfaction, and transitive closure) will converge with high probability if executed in a system in which the shared data is implemented with registers satisfying the new specifications. Furthermore, the algorithms in this framework will inherit positive attributes concerning load and fault-tolerance from the underlying register implementation. The expected convergence time for iterative algorithms using the monotone implementation is analyzed and shown experimentally to improve on that of the original implementation. The message complexity for iterative algorithms using the monotone probabilistic quorum implementation is shown to improve on that of non-probabilistic implementations in a quantifiable situation.

Energy efficient data management for wireless sensor networks with data sink failure

This paper proposes an energy efficient protocol for sensor data management. The protocol employs replicated data sinks to achieve (1) resiliency to data sink failure, and (2) efficiency in storing and retrieving sensor data. A simple address assignment scheme is introduced that partitions the sensor field into cells, where each cell contains one data sink and all sensors that are closest to this data sink. It is shown that this scheme is scalable and resilient against data sink and sensor node failures. Furthermore, the scheme has a reasonably low message complexity and a high energy efficiency

Distributed algorithms for dynamic coverage in sensor networks

The coverage problem is of great interest for many sensor network applications, for example, detection of intruders in the sensor field. Topological changes in sensor networks may affect qualities of sensor coverage. In this paper, we present two suites of algorithms for dynamically maintaining the coverage and the measures of its qualities. Using only local knowledge, our algorithms capture the dynamic changes of network topology and efficiently maintain the coverage by updating the radii of sensors combined with limited sensor mobility. Our algorithms are fully distributed and have the advantages of low communication complexity with no need of a tight bound on message propagation delay.

Online stable matching as a means of allocating distributed resources

Abstract In heterogeneous distributed systems, achieving optimality in both effective use of computational resources (e.g. throughput) and user satisfaction (e.g. response time) is an important unresolved problem. If the users of the system participate dynamically as consumers as well as donors of computational resources, the task of optimizing the exchange of these computational resources leads to a combinatorial problem. As a solution, we propose a novel algorithm, adaptive online stable matching (AOSM). We present experimental data which compare the performance of AOSM with the performance of two alternative algorithms, first-come first-served (FCFS) and fixed- k online.

Improved Time Bounds for Linearizable Implementations of Abstract Data Types

Linearizability is a well-known consistency condition for shared objects in concurrent systems. We focus on the problem of implementing linearizable objects of arbitrary data types in message-passing systems with bounded, but uncertain, message delay and bounded, but non-zero, clock skew. We present an algorithm that exploits axiomatic properties of different operations to reduce the running time of each operation below that obtainable with previously known algorithms. We also prove lower bounds on the time complexity of various kinds of operations, specified by the axioms they satisfy, resulting in reduced gaps in some cases and tight bounds in others.