Open predicate path expressions for distributed environments: notation, implementation, and extensions

This dissertation introduces open predicate path expressions --a non-procedural, very-high-level language notation for the synchronization of concurrent accesses to shared data in distributed computer systems. The target environment is one in which resource modules (totally encapsulated instances of abstract data types) are the basic building blocks in a network of conventional, von Neumann computers or of functional, highly parallel machines. Each resource module will contain two independent submodules: a synchronization submodule which coordinates requests for access to the resource\u27s data and an access-mechanism submodule which localizes the code for operations on that data;Open predicate path expressions are proposed as a specification language for the synchronization submodule and represent a blend of two existing path notations: open path expressions and predicate path expressions. Motivations for the adoption of this new notation are presented, and an implementation semantics for the notation is presented in the form of dataflow graphs;An algorithm is presented which will automatically synthesize an open predicate path expression into a dataflow graph, which is then implemented by a network of communicating submodules written in either a sequential or an applicative language. Finally, an extended notation for the synchronization submodule is proposed, the purpose of which is to provide greater expressive power for certain synchronization problems which are difficult to specify using path expressions alone

Quorum Based Conflict Resolution Algorithms In Distributed Systems

Mutual exclusion is one of the most fundamental issues in the study of distributed systems. The problem arises when two or more processes are competing to use a mutual exclusive resource concurrently, i.e., the resource can only be used by at most one process at a time. Synchronizations adopting quorum systems are an important class of distributed algorithms since they are gracefully and significantly tolerate process and communication failures that may lead to network partitioning. Coterie based algorithm is a typical quorum based algorithm for mutual exclusion: A process can use the resource  only if it obtains permissions from all processes in any quorum ofcoterie, and since each quorum intersects with each other and each process only issues one permission, the mutual exclusion can be guaranteed. Many quorum systems have been defined based on the relaxation of the properties of coterie system. Each of them is designed to resolve its corresponding problem, e.g., k-coterie based algorithm to resolve the k-mutual exclusion, local coterie for the generalized mutual exclusion, (h, k)-arbiter for h-out of-k resource allocation problem, etc. Therefore, design an algorithm for any distributed conflict resolution problem is only meant to define a new quorum system which can be implemented to the corresponding problem. Since most of distributed conflict resolution problems are designed based on the relaxation of the safety property of mutual exclusion, understanding the way to relaxing the safety property and its quorum system is important to study any kind of conflict resolution problem in distributed systems

Implementing SOS with active objects: A case study of a multicore memory system

This paper describes the development of a parallel simulator of a multicore memory system from a model formalized as a structural operational semantics (SOS). Our implementation uses the Abstract Behavioral Specification (ABS) language, an executable, active object modelling language with a formal semantics, targeting distributed systems. We develop general design patterns in ABS for implementing SOS, and describe their application to the SOS model of multicore memory systems. We show how these patterns allow a formal correctness proof that the implementation simulates the formal operational model and discuss further parallelization and fairness of the simulator

The Good Behaviour Game intervention to improve behavioural and other outcomes for children aged 7–8 years: a cluster RCT

BackgroundUniversal, school-based behaviour management interventions can produce meaningful improvements in children’s behaviour and other outcomes. However, the UK evidence base for these remains limited.ObjectiveThe objective of this trial was to investigate the impact, value for money and longer-term outcomes of the Good Behaviour Game. Study hypotheses centred on immediate impact (hypothesis 1); subgroup effects (at-risk boys, hypothesis 2); implementation effects (dosage, hypothesis 3); maintenance/sleeper effects (12- and 24-month post-intervention follow-ups, hypothesis 4); the temporal association between mental health and academic attainment (hypothesis 5); and the health economic impact of the Good Behaviour Game (hypothesis 6).DesignThis was a two-group, parallel, cluster-randomised controlled trial. Primary schools (n = 77) were randomly assigned to implement the Good Behaviour Game for 2 years or continue their usual practice, after which there was a 2-year follow-up period.SettingThe trial was set in primary schools across 23 local authorities in England.ParticipantsParticipants were children (n = 3084) aged 7–8 years attending participating schools.InterventionThe Good Behaviour Game is a universal behaviour management intervention. Its core components are classroom rules, team membership, monitoring behaviour and positive reinforcement. It is played alongside a normal classroom activity for a set time, during which children work in teams to win the game to access the agreed rewards. The Good Behaviour Game is a manualised intervention delivered by teachers who receive initial training and ongoing coaching.Main outcome measuresThe measures were conduct problems (primary outcome; teacher-rated Strengths and Difficulties Questionnaire scores); emotional symptoms (teacher-rated Strengths and Difficulties Questionnaire scores); psychological well-being, peer and social support, bullying (i.e. social acceptance) and school environment (self-report Kidscreen survey results); and school absence and exclusion from school (measured using National Pupil Database records). Measures of academic attainment (reading, standardised tests), disruptive behaviour, concentration problems and prosocial behaviour (Teacher Observation of Child Adaptation Checklist scores) were also collected during the 2-year follow-up period.ResultsThere was no evidence that the Good Behaviour Game improved any outcomes (hypothesis 1). The only significant subgroup moderator effect identified was contrary to expectations: at-risk boys in Good Behaviour Game schools reported higher rates of bullying (hypothesis 2). The moderating effect of the amount of time spent playing the Good Behaviour Game was unclear; in the context of both moderate (≥ 1030 minutes over 2 years) and high (≥ 1348 minutes over 2 years) intervention compliance, there were significant reductions in children’s psychological well-being, but also significant reductions in their school absence (hypothesis 3). The only medium-term intervention effect was for peer and social support at 24 months, but this was in a negative direction (hypothesis 4). After disaggregating within- and between-individual effects, we found no temporal within-individual associations between children’s mental health and their academic attainment (hypothesis 5). Last, our cost–consequences analysis indicated that the Good Behaviour Game does not provide value for money (hypothesis 6).LimitationsLimitations included the post-test-only design for several secondary outcomes; suboptimal implementation dosage (mitigated by complier-average causal effect estimation); and moderate child-level attrition (18.5% for the primary outcome analysis), particularly in the post-trial follow-up period (mitigated by the use of full information maximum likelihood procedures).Future workQuestions remain regarding programme differentiation (e.g. how distinct is the Good Behaviour Game from existing behaviour management practices, and does this makes a difference in terms of its impact?) and if the Good Behaviour Game is impactful when combined with a complementary preventative intervention (as has been the case in several earlier trials).ConclusionThe Good Behaviour Game cannot be recommended based on the findings reported here

Distributed GraphLab: A Framework for Machine Learning in the Cloud

While high-level data parallel frameworks, like MapReduce, simplify the design and implementation of large-scale data processing systems, they do not naturally or efficiently support many important data mining and machine learning algorithms and can lead to inefficient learning systems. To help fill this critical void, we introduced the GraphLab abstraction which naturally expresses asynchronous, dynamic, graph-parallel computation while ensuring data consistency and achieving a high degree of parallel performance in the shared-memory setting. In this paper, we extend the GraphLab framework to the substantially more challenging distributed setting while preserving strong data consistency guarantees. We develop graph based extensions to pipelined locking and data versioning to reduce network congestion and mitigate the effect of network latency. We also introduce fault tolerance to the GraphLab abstraction using the classic Chandy-Lamport snapshot algorithm and demonstrate how it can be easily implemented by exploiting the GraphLab abstraction itself. Finally, we evaluate our distributed implementation of the GraphLab abstraction on a large Amazon EC2 deployment and show 1-2 orders of magnitude performance gains over Hadoop-based implementations.Comment: VLDB201

Social Exchange and the Maintenance of Order in Status-Stratified Systems

This paper examines the role of social exchange in the construction of microorder within status-differentiated relations. How order is constructed and maintained in the context of social inequality is a classic sociological problem. We use a serendipitous finding from a recent experiment as a stimulus for theorizing an important feature of this larger problem of order. The finding is that, in an experiment where African-American females negotiated with white males, the white males received much larger payoffs than the African-American females. Yet, despite substantial power and profit differentiation advantaging white males, both individuals reported positive feelings (pleasure/satisfaction and interest/excitement) to the same degree, which contradicts most research on emotional responses to power. We argue that these similar emotional responses, in the context of substantial payoff inequalities, are due to parallel, joint effects of (a) status processes that create and legitimate initial profit differences and (b) exchange processes that make salient a relationship between the actors during repeated exchange. This explanation integrates notions of status value, referential structure, and legitimacy from status theories with notions of relational cohesion and shared responsibility from exchange theories. Broadly, the paper proposes some ways to productively interweave ideas from status and exchange theories to explain the emergence or maintenance of enduring social inequalities

Analysis of Multi-Threading and Cache Memory Latency Masking on Processor Performance Using Thread Synchronization Technique

Multithreading is a process in which a single processor executes multiple threads concurrently. This enables the processor to divide tasks into separate threads and run them simultaneously, thereby increasing the utilization of available system resources and enhancing performance. When multiple threads share an object and one or more of them modify it, unpredictable outcomes may occur. Threads that exhibit poor locality of memory reference, such as database applications, often experience delays while waiting for a response from the memory hierarchy. This observation suggests how to better manage pipeline contention. To assess the impact of memory latency on processor performance, a dual-core MT machine with four thread contexts per core is utilized. These specific benchmarks are chosen to allow the workload to include programs with both favorable and unfavorable cache locality. To eliminate the issue of wasting the wake-up signals, this work proposes an approach that involves storing all the wake-up calls. It asserts the wake-up calls to the consumer and the producer can store the wake-up call in a variable.   An assigned value in working system (or kernel) storage that each process can check is a semaphore. Semaphore is a variable that reads, and update operations automatically in bit mode. It cannot be actualized in client mode since a race condition may persistently develop when two or more processors endeavor to induce to the variable at the same time. This study includes code to measure the time taken to execute both functions and plot the graph. It should be noted that sending multiple requests to a website simultaneously could trigger a flag, ultimately blocking access to the data. This necessitates some computation on the collected statistics. The execution time is reduced to one third when using threads compared to executing the functions sequentially. This exemplifies the power of multithreading

Scheduling and discrete event control of flexible manufacturing systems based on Petri nets

A flexible manufacturing system (FMS) is a computerized production system that can simultaneously manufacture multiple types of products using various resources such as robots and multi-purpose machines. The central problems associated with design of flexible manufacturing systems are related to process planning, scheduling, coordination control, and monitoring. Many methods exist for scheduling and control of flexible manufacturing systems, although very few methods have addressed the complexity of whole FMS operations. This thesis presents a Petri net based method for deadlock-free scheduling and discrete event control of flexible manufacturing systems. A significant advantage of Petri net based methods is their powerful modeling capability. Petri nets can explicitly and concisely model the concurrent and asynchronous activities, multi-layer resource sharing, routing flexibility, limited buffers and precedence constraints in FMSs. Petri nets can also provide an explicit way for considering deadlock situations in FMSs, and thus facilitate significantly the design of a deadlock-free scheduling and control system. The contributions of this work are multifold. First, it develops a methodology for discrete event controller synthesis for flexible manufacturing systems in a timed Petri net framework. The resulting Petri nets have the desired qualitative properties of liveness, boundedness (safeness), and reversibility, which imply freedom from deadlock, no capacity overflow, and cyclic behavior, respectively. This precludes the costly mathematical analysis for these properties and reduces on-line computation overhead to avoid deadlocks. The performance and sensitivity of resulting Petri nets, thus corresponding control systems, are evaluated. Second, it introduces a hybrid heuristic search algorithm based on Petri nets for deadlock-free scheduling of flexible manufacturing systems. The issues such as deadlock, routing flexibility, multiple lot size, limited buffer size and material handling (loading/unloading) are explored. Third, it proposes a way to employ fuzzy dispatching rules in a Petri net framework for multi-criterion scheduling. Finally, it shows the effectiveness of the developed methods through several manufacturing system examples compared with benchmark dispatching rules, integer programming and Lagrangian relaxation approaches