Self-stabilizing interval routing algorithm with low stretch factor

A compact routing scheme is a routing strategy which suggests routing tables that are space efficient compared to traditional all-pairs shortest path routing algorithms. An Interval Routing algorithm is a compact routing algorithm which uses a routing table at every node in which a set of destination addresses that use the same output port are grouped into intervals of consecutive addresses. Self-stabilization is a property by which a system is guaranteed to reach a legitimate state in a finite number of steps starting from any arbitrary state. A self-stabilizing Pivot Interval Routing (PIR) algorithm is proposed in this work. The PIR strategy allows routing along paths whose stretch factor is at most five, and whose average stretch factor is at most three with routing tables of size O(n3/2log 23/2n) bits in total, where n is the number of nodes in the network. Stretch factor is the maximum ratio taken over all source-destination pairs between the length of the paths computed by the routing algorithm and the distance between the source and the destination. PIR is also an Interval Routing Scheme (IRS) using at most 2n( 1+lnn)1/2 intervals per link for the weighted graphs and 3n(1+ lnn)1/2 intervals per link for the unweighted graphs. The preprocessing stage of the PIR algorithm consists of nodelabeling and arc-labeling functions. The nodelabeling function re-labels the nodes with unique integers so as to facilitate fewer number of intervals per arc. The arc-labeling is done in such a fashion that the message delivery protocol takes an optimal path if both the source and the destination are located within a particular range from each other and takes a near-optimal path if they are farther from each other

Robust network computation

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 91-98).In this thesis, we present various models of distributed computation and algorithms for these models. The underlying theme is to come up with fast algorithms that can tolerate faults in the underlying network. We begin with the classical message-passing model of computation, surveying many known results. We give a new, universally optimal, edge-biconnectivity algorithm for the classical model. We also give a near-optimal sub-linear algorithm for identifying bridges, when all nodes are activated simultaneously. After discussing some ways in which the classical model is unrealistic, we survey known techniques for adapting the classical model to the real world. We describe a new balancing model of computation. The intent is that algorithms in this model should be automatically fault-tolerant. Existing algorithms that can be expressed in this model are discussed, including ones for clustering, maximum flow, and synchronization. We discuss the use of agents in our model, and give new agent-based algorithms for census and biconnectivity. Inspired by the balancing model, we look at two problems in more depth.(cont.) First, we give matching upper and lower bounds on the time complexity of the census algorithm, and we show how the census algorithm can be used to name nodes uniquely in a faulty network. Second, we consider using discrete harmonic functions as a computational tool. These functions are a natural exemplar of the balancing model. We prove new results concerning the stability and convergence of discrete harmonic functions, and describe a method which we call Eulerization for speeding up convergence.by David Pritchard.M.Eng

Declarative symbolic pure-logic model checking

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 173-181).Model checking, a technique for findings errors in systems, involves building a formal model that describes possible system behaviors and correctness conditions, and using a tool to search for model behaviors violating correctness properties. Existing model checkers are well-suited for analyzing control-intensive algorithms (e.g. network protocols with simple node state). Many important analyses, however, fall outside the capabilities of existing model checkers. Examples include checking algorithms with complex state, distributed algorithms over all network topologies, and highly declarative models. This thesis addresses the problem of building an efficient model checker that overcomes these limitations. The work builds on Alloy, a relational modeling language. Previous work has defined the language and shown that it can be analyzed by translation to SAT. The primary contributions of this thesis include: a modeling paradigm for describing complex structures in Alloy; significant improvements in scalability of the analyzer; and improvements in usability of the analyzer via addition of a debugger for over constraints. Together, these changes make model-checking practical for important new classes of analyses. While the work was done in the context of Alloy, some techniques generalize to other verification tools.by Ilya A. Shlyakhter.S.M

Network Analysis of Scientific Collaboration and Co-authorship of the Trifecta of Malaria, Tuberculosis and Hiv/aids in Benin.

Despite the international mobilization and increase in research funding, Malaria, Tuberculosis and HIV/AIDS are three infectious diseases that have claimed more lives in sub Saharan Africa than any other place in the World. Consortia, research network and research centers both in Africa and around the world team up in a multidisciplinary and transdisciplinary approach to boost efforts to curb these diseases. Despite the progress in research, very little is known about the dynamics of research collaboration in the fight of these Infectious Diseases in Africa resulting in a lack of information on the relationship between African research collaborators. This dissertation addresses the problem by documenting, describing and analyzing the scientific collaboration and co-authorship network of Malaria, Tuberculosis and HIV/AIDS in the Republic of Benin. We collected published scientific records from the Web Of Science over the last 20 years (From January 1996 to December 2016). We parsed the records and constructed the coauthorship networks for each disease. Authors in the networks were represented by vertices and an edge was created between any two authors whenever they coauthor a document together. We conducted a descriptive social network analysis of the networks, then used mathematical models to characterize them. We further modeled the complexity of the structure of each network, the interactions between researchers, and built predictive models for the establishment of future collaboration ties. Furthermore, we implemented the models in a shiny-based application for co-authorship network visualization and scientific collaboration link prediction tool which we named AuthorVis. Our findings suggest that each one of the collaborative research networks of Malaria, HIV/AIDS and TB has a complex structure and the mechanism underlying their formation is not random. All collaboration networks proved vulnerable to structural weaknesses. In the Malaria coauthorship network, we found an overwhelming dominance of regional and international contributors who tend to collaborate among themselves. We also observed a tendency of transnational collaboration to occur via long tenure authors. We also find that TB research in Benin is a low research productivity area. We modeled the structure of each network with an overall performance accuracy of 79.9%, 89.9%, and 93.7% for respectively the malaria, HIV/AIDS, and TB coauthorship network. Our research is relevant for the funding agencies operating and the national control programs of those three diseases in Benin (the National Malaria Control Program, the National AIDS Control Program and the National Tuberculosis Control Program)

Initialisation Problems in Feature Composition

Composing features that have inconsistent requirements may lead to feature interactions that violate requirements satisfied by each feature in isolation. These interactions manifest themselves as conflicts on shared resources. Arbitration is a common approach to resolving such conflicts that uses prioritisation to decide which feature has access to resources when there is a conflict. However, arbitration alone does not guarantee satisfaction of the requirement of the feature that eventually gains access to a resource. This is because arbitration does not take into account that the resource may be in a state that is inconsistent with that expected by the feature. We call this the initialisation problem. In this thesis we propose an approach to addressing the initialisation problem which combines arbitration with contingencies. Contingency means having several specifications per feature satisfying the same requirement, depending on the current resource state. We illustrate and validate our approach by applying it to resolving conflicts between features in smart home and automotive domains. The validation shows that contingencies complement arbitration by enabling satisfaction of the requirement of the feature that eventually gains access to a shared resource, regardless of the current state of the resource. The main contribution of this thesis is an approach to analysing initialisation concerns in feature composition. At the core of our approach is an explicit consideration of all possible states of a resource as potential initial states. Given each initial state we then derive corresponding specifications that would enable a feature to satisfy its requirement in those states. We show that our approach to initialisation problems is relevant to addressing the feature interaction problem by characterising some types of conflicts as initialisation concerns