Brandon Dixon

Verification and sensitivity analysis of minimum spanning trees in linear time

Komlos has devised a way to use a linear number of binary comparisons to test whether a given spanning tree of a graph with edge costs is a minimum spanning tree. The total computational work required by his method is much larger than linear, however. This paper describes a linear-time algorithm for verifying a minimum spanning tree. This algorithm combines the result of Komlos with a preprocessing and table look-up method for small subproblems and with a previously known almost-linear-time algorithm. Additionally, an optimal deterministic algorithm and a linear-time randomized algorithm for sensitivity analysis of minimum spanning trees are presented.

A conceptual foundation for component-based software deployment

Abstract We use the term component-based software deployment (CBSD) to refer to the process of deploying a software application in a component-based format. In this paper, we propose a formal conceptual framework for CBSD. This framework allows us to articulate various strategies for deploying component-based software. In addition, the framework permits us to express conditions under which various forms of CBSD are both successful (the deployed application works) and safe (no existing applications are damaged).

CARE: an automobile crash data analysis tool

The Critical Analysis Reporting Environment provides an efficient tool for transportation safer engineers and policymakers to use in analyzing the categorical crash data typically obtained from police reports. CAPE has proven successful in the traffic safety community for two reasons: its simplicity and its efficiency. It is currently being used in several states.

Enhancing the Cocomo estimation models

In software engineering, team task assignments appear to have a significant potential impact on a projects overall success. The authors propose task assignment effort adjustment factors that can help tune existing estimation models. They show significant improvements in the predictive abilities of both Cocomo I and II by enhancing them with these factors.

A belief-consistent multilevel secure relational data model☆

Abstract Multilevel relations, based on the current multilevel secure (MLS) relational data models, can present a user with information that is difficult to interpret and may display an inconsistent outlook about the views of other users. Such ambiguity is due to the lack of a comprehensive method for asserting and interpreting beliefs about information at lower security levels. In this paper we present a belief-consistent MLS relational database model which provides an unambiguous interpretation of all visible information and gives the user access to the beliefs of users at lower security levels, neither of which was possible in any of the existing models. We identify different beliefs that can be held by users at higher security levels about information at lower security levels, and introduce a mechanism for asserting beliefs about all accessible tuples. This mechanism provides every user with an unambiguous interpretation of all viewable information and presents a consistent account of the views at all levels visible to the user. In order to implement this assertion mechanism, new database operations, such as verify true and verify false, are presented. We specify the constraints for the write operations, such as update and delete, that maintain belief consistency and redefine the relational algebra operations, such as select, project, union, difference and join.

Efficient multi-hop connectivity analysis in urban vehicular networks

Vehicle to Vehicle (V2V) communication provides a flexible and real-time information dissemination mechanism through various applications of Intelligent Transportation Systems (ITS). Achieving seamless connectivity through multi-hop vehicular communication with sparse network is a challenging issue. In this paper, we have studied this multi-hop vehicular connectivity in an urban scenario using GPS traces obtained from San Francisco Yellow cabs. Our current work describes a new algorithm for the analysis of topological properties like connectivity and partitions for any kind of vehicular or mobile computing environment. The novel approach uses bitwise manipulation of sparse matrix with an efficient storage technique for determining multi-hop connectivity. The computation mechanism can be further scaled to parallel processing environment. The main contribution of this research is threefold. First, developing an efficient algorithm to quantify multi-hop connectivity with the aid of bitwise manipulation of sparse matrix. Second, investigating the time varying nature of multi-hop vehicular connectivity and dynamic network partitioning of the topology. Third, deriving a mathematical model for calculating message propagation rate in an urban environment.

A characterization of important algorithms for quantum-dot cellular automata

Abstract Feature sizes in chip manufacturing are becoming so small that quantum mechanical behavior will soon have a deleterious effect on the function of devices. Quantum-dot cellular automata (QDCA) have been proposed as computing devices which are helped, rather than hindered, by the quantum behavior of electrons. QDCA compute by relaxing to a configuration of minimal energy. Previously, it has been shown that a quantum-dot device may not compute properly if all of its relaxed configurations are not equal in energy level. Such an automation is termed unbalanced . A necessary condition for an automaton to be balanced is that the number of distinguished configurations with minimum energy should equal the number of input combinations the automaton handles. Does an efficient algorithm for determining the number of distinguished ground states exist? If so, it will be difficult to find, as such an algorithm is shown to be NP-hard. Furthermore, the related problem of determining the minimum energy level of arbitrary automata is also shown to be NP-hard. These results have important implications for simulating and analyzing QDCA on conventional computers.

Factoring integers using SIMD sieves

We describe our single-instruction multiple data (SIMD) implementation of the multiple polynomial quadratic sieve integer factoring algorithm. On a 16K MasPar massively parallel computer, our implementation can factor 100 digit integers in a few days. Its most notable success was the factorization of the 110-digit RSA-challenge number, which took about a month.

Analysis of mobility patterns for urban taxi cabs

This paper analyzes urban taxi mobility traces obtained from San Francisco Yellow cabs. The paper presents a rigorous analysis of taxi mobility pattern with the instantaneous velocity profile, spatio-temporal distribution, connectivity of vehicle communications, clustering, hotspots and other characteristics like trip duration and empty cruise interval. The empirical data analyses presented here can be a helpful resource for wireless researchers, government organizations, taxi companies and even for the drivers or passengers. While wireless researchers can estimate the capabilities and constraints of vehicular communication from connectivity and mobility patterns, government can plan and work on issues related to implementing proper DSRC infrastructure. Finally, taxi companies and drivers can benefit from maximizing the trip revenue and minimize empty cruise time though balanced load distribution and awareness of the hotspots.

Articulation Node Based Routing in delay tolerant networks

Routing in delay tolerant networks (DTNs) is a challenging problem in networking research. Existing DTN routing solutions have used many approaches to increase the success rate of message delivery, such as meeting probabilities between nodes, packet replication and flooding. One important feature of these protocols is using local connection information to find the “best” path with high likelihood to deliver a packet. In this paper, we propose a new routing protocol called ANBR (Articulation Node Based Routing). From a global view, a general disconnected network can have many small instantaneously clustered mobile nodes. Mobility allows nodes carrying messages to deliver them to other clusters. Selecting appropriate nodes to carry and deliver messages becomes important in order to reduce message delay and overhead. The proposed ANBR tackles this issue by utilizing articulation nodes among a local sub-graph formed by including all neighbors of two “meeting” nodes. Articulation nodes are the articulation points or cut vertices of this local sub-graph, and by definition are the nodes, whose removal will disconnect the graph. Thus, these articulation nodes are more likely to be able to deliver messages outside the local cluster. Packets will be buffered in these nodes and forwarded to other articulation nodes when they meet. The process repeats until messages reach their destinations. We evaluate our algorithm by using real world data from the MIT reality mining project. The simulation results show that ANBR algorithm performs better than related protocols in terms of delivery rate and efficiency.