Scalable Termination Detection for Distributed Actor Systems

Automatic garbage collection (GC) prevents certain kinds of bugs and reduces programming overhead. GC techniques for sequential programs are based on reachability analysis. However, testing reachability from a root set is inadequate for determining whether an actor is garbage because an unreachable actor may send a message to a reachable actor. Instead, it is sufficient to check termination (sometimes also called quiescence): an actor is terminated if it is not currently processing a message and cannot receive a message in the future. Moreover, many actor frameworks provide all actors with access to file I/O or external storage; without inspecting an actor's internal code, it is necessary to check that the actor has terminated to ensure that it may be garbage collected in these frameworks. Previous algorithms to detect actor garbage require coordination mechanisms such as causal message delivery or nonlocal monitoring of actors for mutation. Such coordination mechanisms adversely affect concurrency and are therefore expensive in distributed systems. We present a low-overhead reference listing technique (called DRL) for termination detection in actor systems. DRL is based on asynchronous local snapshots and message-passing between actors. This enables a decentralized implementation and transient network partition tolerance. The paper provides a formal description of DRL, shows that all actors identified as garbage have indeed terminated (safety), and that all terminated actors--under certain reasonable assumptions--will eventually be identified (liveness).Comment: 23 pages, 7 figures. To appear in the proceedings of CONCUR 2020. Version 2: Fixed TeX error that omitted predicates in the third line of the Send rule: Actor $A$ must have active refobs $x$ and $y_1 \dots y_n

Orca: GC and type system co-design for actor languages

ORCA is a concurrent and parallel garbage collector for actor programs, which does not require any stop-the-world steps, or synchronisation mechanisms, and which has been designed to support zero-copy message passing and sharing of mutable data. \ORCA is part of the runtime of the actor-based language Pony. Pony's runtime was co-designed with the Pony language. This co-design allowed us to exploit certain language properties in order to optimise performance of garbage collection. Namely, ORCA relies on the absence of race conditions in order to avoid read/write barriers, and it leverages actor message passing for synchronisation among actors. This paper describes Pony, its type system, and the ORCA garbage collection algorithm. An evaluation of the performance of ORCA suggests that it is fast and scalable for idiomatic workloads

Subheap-Augmented Garbage Collection

Automated memory management avoids the tedium and danger of manual techniques. However, as no programmer input is required, no widely available interface exists to permit principled control over sometimes unacceptable performance costs. This dissertation explores the idea that performance-oriented languages should give programmers greater control over where and when the garbage collector (GC) expends effort. We describe an interface and implementation to expose heap partitioning and collection decisions without compromising type safety. We show that our interface allows the programmer to encode a form of reference counting using Hayes\u27 notion of key objects. Preliminary experimental data suggests that our proposed mechanism can avoid high overheads suffered by tracing collectors in some scenarios, especially with tight heaps. However, for other applications, the costs of applying subheaps---in human effort and runtime overheads---remain daunting

Raphtory: Modelling, Maintenance and Analysis of Distributed Temporal Graphs.

PhD ThesesTemporal graphs capture the development of relationships within data throughout time. This model ts naturally within a streaming architecture, where new events can be inserted directly into the graph upon arrival from a data source and be compared to related entities or historical state. However, the majority of graph processing systems only consider traditional graph analysis on static data, whilst those which do expand past this often only support batched updating and delta analysis across graph snapshots. In this work we de ne a temporal property graph model and the semantics for updating it in both a distributed and non-distributed context. We have built Raphtory, a distributed temporal graph analytics platform which maintains the full graph history in memory, leveraging the de ned update semantics to insert streamed events directly into the model without batching or centralised ordering. In parallel with the ingestion, traditional and time-aware analytics may be performed on the most up-to-date version of the graph, as well as any point throughout its history. The depth of history viewed from the perspective of a time point may also be varied to explore both short and long term patterns within the data. Through this we extract novel insights over a variety of use cases, including phenomena never seen before in social networks. Finally, we demonstrate Raphtory's ability to scale both vertically and horizontally, handling consistent throughput in excess of 100,000 updates a second alongside the ingestion and maintenance of graphs built from billions of events

Sustainable Consumption and Production Patterns: Policy Design and Evaluation

This book is intended to highlight why SCP policy design and evaluation needs to overcome conventional environmental policy framework. Emerging SCP policy design and evaluation do not involve focusing on individual products or behaviors or improving efficiency in management systems in relation to environmental sustainability; instead, they address more socio-economic systems and target collective efforts for transition. Effort has been made for this book/Special Issue to feature studies contributing to policy design and evaluation in this direction. It contains 11 papers covering challenges and opportunities for SCP policy design, application of foresight to policy design, evaluation of NDC potentials to facilitate sustainable lifestyles, comparative analysis of sustainable development criteria, sustainable lifestyle and education, subjective wellbeing and sustainable consumption, case studies on challenges and opportunities for sustainability transition at the local and community level, and three case studies on how to fill gaps between policy goals and environmental behavior at a city level in China, Vietnam, and Thailand. The papers in this book suggest that SCP policy design and evaluation need to pay more attention to social aspects of sustainability such as social infrastructure and well-being and socio-technical systems to ensure effective and just transition to sustainability

Behavioural Insights Applied to Policy - European Report 2016

This report covers a wealth of policy initiatives across 32 European countries either implicitly or explicitly informed by behavioural insights (BIs). It reviews institutional developments around the application for behavioural insights for policy and puts forward a comparative framework (PRECIS) describing behavioural insights teams with six key features. The report reaches four main conclusions: i) in terms of capacity-building, there is significant dynamism and growing appetite to apply BIs to policy-making; ii) links between policy-making and academy communities can be strengthened and analysing large datasets offers great potential; iii) systematic application of BIs throughout the policy cycle can advance evidence-based policy-making; iv) there is a need for more research on the long-term impacts of policy interventions.JRC.DDG.02-Foresight and Behavioural Insight

A framework for understanding the policy process for construction

The policy process for construction in the UK does not seem to deliver the intended results, yet relatively little research has been carried out in this area using the analytical frameworks and tools available from other disciplines. The approach known as Political Economy Analysis (PEA) was investigated by its application to policy for construction using sectoral level policy (Construction Industrial Policy, CIP) as the unit of analysis. The research strategy was interpretivist and the research design was cross-sectional. Two parallel, but mutually reinforcing, objectives were adopted. [Continues.]</div

Behavioural insights applied to policy: European Report 2016

Joana Sousa Lourenço, Emanuele Ciriolo, Sara Rafael Almeida, and Xavier TroussardBehavioural Insights Applied to Policy (BIAP) 2016 draws on information collected via desk research, a survey and personal exchanges, including interviews with policy-makers, academics and a range of other stakeholders from 32 countries (28 EU Member States and the 4 EFTA countries). Such information is used to provide a twofold overview of:  Behavioural policy initiatives;  Institutional developments regarding the policy application of BIs.