Mesmerizer: A Effective Tool for a Complete Peer-to-Peer Software Development Life-cycle

In this paper we present what are, in our experience, the best practices in Peer-To-Peer(P2P) application development and how we combined them in a middleware platform called Mesmerizer. We explain how simulation is an integral part of the development process and not just an assessment tool. We then present our component-based event-driven framework for P2P application development, which can be used to execute multiple instances of the same application in a strictly controlled manner over an emulated network layer for simulation/testing, or a single application in a concurrent environment for deployment purpose. We highlight modeling aspects that are of critical importance for designing and testing P2P applications, e.g. the emulation of Network Address Translation and bandwidth dynamics. We show how our simulator scales when emulating low-level bandwidth characteristics of thousands of concurrent peers while preserving a good degree of accuracy compared to a packet-level simulator

Secure Time-Aware Provenance for Distributed Systems

Operators of distributed systems often find themselves needing to answer forensic questions, to perform a variety of managerial tasks including fault detection, system debugging, accountability enforcement, and attack analysis. In this dissertation, we present Secure Time-Aware Provenance (STAP), a novel approach that provides the fundamental functionality required to answer such forensic questions – the capability to “explain” the existence (or change) of a certain distributed system state at a given time in a potentially adversarial environment. This dissertation makes the following contributions. First, we propose the STAP model, to explicitly represent time and state changes. The STAP model allows consistent and complete explanations of system state (and changes) in dynamic environments. Second, we show that it is both possible and practical to efficiently and scalably maintain and query provenance in a distributed fashion, where provenance maintenance and querying are modeled as recursive continuous queries over distributed relations. Third, we present security extensions that allow operators to reliably query provenance information in adversarial environments. Our extensions incorporate tamper-evident properties that guarantee eventual detection of compromised nodes that lie or falsely implicate correct nodes. Finally, the proposed research results in a proof-of-concept prototype, which includes a declarative query language for specifying a range of useful provenance queries, an interactive exploration tool, and a distributed provenance engine for operators to conduct analysis of their distributed systems. We discuss the applicability of this tool in several use cases, including Internet routing, overlay routing, and cloud data processing

Parallel programming using functional languages

It has been argued for many years that functional programs are well suited to parallel evaluation. This thesis investigates this claim from a programming perspective; that is, it investigates parallel programming using functional languages. The approach taken has been to determine the minimum programming which is necessary in order to write efficient parallel programs. This has been attempted without the aid of clever compile-time analyses. It is argued that parallel evaluation should be explicitly expressed, by the programmer, in programs. To do achieve this a lazy functional language is extended with parallel and sequential combinators. The mathematical nature of functional languages means that programs can be formally derived by program transformation. To date, most work on program derivation has concerned sequential programs. In this thesis Squigol has been used to derive three parallel algorithms. Squigol is a functional calculus from program derivation, which is becoming increasingly popular. It is shown that some aspects of Squigol are suitable for parallel program derivation, while others aspects are specifically orientated towards sequential algorithm derivation. In order to write efficient parallel programs, parallelism must be controlled. Parallelism must be controlled in order to limit storage usage, the number of tasks and the minimum size of tasks. In particular over-eager evaluation or generating excessive numbers of tasks can consume too much storage. Also, tasks can be too small to be worth evaluating in parallel. Several program techniques for parallelism control were tried. These were compared with a run-time system heuristic for parallelism control. It was discovered that the best control was effected by a combination of run-time system and programmer control of parallelism. One of the problems with parallel programming using functional languages is that non-deterministic algorithms cannot be expressed. A bag (multiset) data type is proposed to allow a limited form of non-determinism to be expressed. Bags can be given a non-deterministic parallel implementation. However, providing the operations used to combine bag elements are associative and commutative, the result of bag operations will be deterministic. The onus is on the programmer to prove this, but usually this is not difficult. Also bags' insensitivity to ordering means that more transformations are directly applicable than if, say, lists were used instead. It is necessary to be able to reason about and measure the performance of parallel programs. For example, sometimes algorithms which seem intuitively to be good parallel ones, are not. For some higher order functions it is posible to devise parameterised formulae describing their performance. This is done for divide and conquer functions, which enables constraints to be formulated which guarantee that they have a good performance. Pipelined parallelism is difficult to analyse. Therefore a formal semantics for calculating the performance of pipelined programs is devised. This is used to analyse the performance of a pipelined Quicksort. By treating the performance semantics as a set of transformation rules, the simulation of parallel programs may be achieved by transforming programs. Some parallel programs perform poorly due to programming errors. A pragmatic method of debugging such programming errors is illustrated by some examples

Scaling Causality Analysis for Production Systems.

Causality analysis reveals how program values influence each other. It is important for debugging, optimizing, and understanding the execution of programs. This thesis scales causality analysis to production systems consisting of desktop and server applications as well as large-scale Internet services. This enables developers to employ causality analysis to debug and optimize complex, modern software systems. This thesis shows that it is possible to scale causality analysis to both fine-grained instruction level analysis and analysis of Internet scale distributed systems with thousands of discrete software components by developing and employing automated methods to observe and reason about causality. First, we observe causality at a fine-grained instruction level by developing the first taint tracking framework to support tracking millions of input sources. We also introduce flexible taint tracking to allow for scoping different queries and dynamic filtering of inputs, outputs, and relationships. Next, we introduce the Mystery Machine, which uses a ``big data'' approach to discover causal relationships between software components in a large-scale Internet service. We leverage the fact that large-scale Internet services receive a large number of requests in order to observe counterexamples to hypothesized causal relationships. Using discovered casual relationships, we identify the critical path for request execution and use the critical path analysis to explore potential scheduling optimizations. Finally, we explore using causality to make data-quality tradeoffs in Internet services. A data-quality tradeoff is an explicit decision by a software component to return lower-fidelity data in order to improve response time or minimize resource usage. We perform a study of data-quality tradeoffs in a large-scale Internet service to show the pervasiveness of these tradeoffs. We develop DQBarge, a system that enables better data-quality tradeoffs by propagating critical information along the causal path of request processing. Our evaluation shows that DQBarge helps Internet services mitigate load spikes, improve utilization of spare resources, and implement dynamic capacity planning.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135888/1/mcchow_1.pd

The Impact of Rogue Nodes on the Dependability of Opportunistic Networks

Opportunistic Networks (OppNets) are an extension to the classical Mobile Ad hoc Networks (MANETs) where the network is not dependent on any infrastructure (e.g. Access Points or centralized administrative nodes). OppNets can be more flexible than MANETs because an end to end path does not exist and much longer delays can be expected. Whereas a Rogue Access Point is typically immobile in the legacy infrastructure based networks and can have considerable impact on the overall connectivity, the research question in this project evaluates how the pattern and mobility of a rogue nodes impact the dependability and overall "Average Latency" in an Opportunistic Network Environment. We have simulated a subset of the mathematical modeling performed in a previous publication in this regard. Ad hoc networks are very challenging to model due to their mobility and intricate routing schemes. We strategically started our research by exploring the evolution of Opportunistic networks, and then implemented the rogue behavior by utilizing The ONE (Opportunistic Network Environment, by Nokia Research Centre) simulator to carry out our research over rogue behavior. The ONE simulator is an open source simulator developed in Java, simulating the layer 3 of the OSI model. The Rogue behavior is implemented in the simulator to observe the effect of rogue nodes. Finally we extracted the desired dataset to measure the latency by carefully simulating the intended behavior, keeping rest of the parameters (e.g. Node Movement Models, Signal Range and Strength, Point of Interest (POI) etc) unchanged. Our results are encouraging, and coincide with the average latency deterioration patterns as modeled by the previous researchers, with a few exceptions. The practical implementation of plug-in in ONE simulator has shown that only a very high degree of rogue nodes impact the latency, making OppNets more resilient and less vulnerable to malicious attacks

Behavior Trees in Robotics and AI: An Introduction

A Behavior Tree (BT) is a way to structure the switching between different tasks in an autonomous agent, such as a robot or a virtual entity in a computer game. BTs are a very efficient way of creating complex systems that are both modular and reactive. These properties are crucial in many applications, which has led to the spread of BT from computer game programming to many branches of AI and Robotics. In this book, we will first give an introduction to BTs, then we describe how BTs relate to, and in many cases generalize, earlier switching structures. These ideas are then used as a foundation for a set of efficient and easy to use design principles. Properties such as safety, robustness, and efficiency are important for an autonomous system, and we describe a set of tools for formally analyzing these using a state space description of BTs. With the new analysis tools, we can formalize the descriptions of how BTs generalize earlier approaches. We also show the use of BTs in automated planning and machine learning. Finally, we describe an extended set of tools to capture the behavior of Stochastic BTs, where the outcomes of actions are described by probabilities. These tools enable the computation of both success probabilities and time to completion

Programmiersprachen und Rechenkonzepte

Seit 1984 veranstaltet die GI-Fachgruppe "Programmiersprachen und Rechenkonzepte", die aus den ehemaligen Fachgruppen 2.1.3 "Implementierung von Programmiersprachen" und 2.1.4 "Alternative Konzepte für Sprachen und Rechner" hervorgegangen ist, regelmäßig im Frühjahr einen Workshop im Physikzentrum Bad Honnef. Das Treffen dient in erster Linie dem gegenseitigen Kennenlernen, dem Erfahrungsaustausch, der Diskussion und der Vertiefung gegenseitiger Kontakte

VIRTUALIZED BASEBAND UNITS CONSOLIDATION IN ADVANCED LTE NETWORKS USING MOBILITY- AND POWER-AWARE ALGORITHMS

Virtualization of baseband units in Advanced Long-Term Evolution networks and a rapid performance growth of general purpose processors naturally raise the interest in resource multiplexing. The concept of resource sharing and management between virtualized instances is not new and extensively used in data centers. We adopt some of the resource management techniques to organize virtualized baseband units on a pool of hosts and investigate the behavior of the system in order to identify features which are particularly relevant to mobile environment. Subsequently, we introduce our own resource management algorithm specifically targeted to address some of the peculiarities identified by experimental results

A model-based reasoning architecture for system-level fault diagnosis

This dissertation presents a model-based reasoning architecture with a two fold purpose: to detect and classify component faults from observable system behavior, and to generate fault propagation models so as to make a more accurate estimation of current operational risks. It incorporates a novel approach to system level diagnostics by addressing the need to reason about low-level inaccessible components from observable high-level system behavior. In the field of complex system maintenance it can be invaluable as an aid to human operators. The first step is the compilation of the database of functional descriptions and associated fault-specific features for each of the system components. The system is then analyzed to extract structural information, which, in addition to the functional database, is used to create the structural and functional models. A fault-symptom matrix is constructed from the functional model and the features database. The fault threshold levels for these symptoms are founded on the nominal baseline data. Based on the fault-symptom matrix and these thresholds, a diagnostic decision tree is formulated in order to intelligently query about the system health. For each faulty candidate, a fault propagation tree is generated from the structural model. Finally, the overall system health status report includes both the faulty components and the associated at risk components, as predicted by the fault propagation model.Ph.D.Committee Chair: Vachtsevanos, George; Committee Member: Liang, Steven; Committee Member: Michaels, Thomas; Committee Member: Vela, Patricio; Committee Member: Wardi, Yora