A high-level and scalable approach for generating scale-free graphs using active objects

Science of Computer Programming

Bezirgiannis

et al. 2020

Self Cite

Asynchronous Actor-based programming has gained increasing attention as a model of concurrency and distribution. The Abstract Behavioral Specification (ABS) language is an actor-based programming language that has been developed for both the modeling and formal analysis of distributed systems. In ABS, actors are modeled as concurrent objects that communicate by asynchronous method calls. Return values are also communicated asynchronously via return statements and so-called futures. Many modern distributed software applications require a form of continuous interaction between their components which consists of streaming data from a server to its clients. In this paper, we extend the ABS language in order to support the streaming of data. We introduce the notion of "future-based data streams" by augmenting the syntax, type system, and operational semantics of ABS. As a proof of concept, we further discuss a prototype implementation for supporting future-based data streams on top of ABS, and discuss the impact of the use of these data streams in ABS on the performance in the implementation of a distributed application for the generation of social networks.

Section: Case Studymentioning

confidence: 99%

A formal actor-based model for streaming the future

Science of Computer Programming

Bezirgiannis

et al. 2020

Self Cite

“…Modeling and implementation of the above-mentioned system is for standard ABS already extensively investigated for both multi-core [10] and distributed [11] architectures in the ABS language. Here we focus on how our proposed notion of streams influences the performance of the system presented in [11].…”

Section: Case Studymentioning

confidence: 99%

On Futures for Streaming Data in ABS

Bezirgiannis

Formal Techniques for Distributed Objects, Components, and Systems

2017

Self Cite

Abstract. Many modern distributed software applications require a continuous interaction between their components exploiting streaming data from the server to the client. The Abstract Behavioral Specification (ABS) language has been developed for the modeling and analysis of distributed systems. In ABS, concurrent objects communicate by calling each other's methods asynchronously. Return values are communicated asynchronously too via the return statement and so-called futures. In this paper, we extend the basic ABS model of asynchronous method invocation and return in order to support the streaming of data. We introduce the notion of a "Future-based Data Stream" to extend the ABS. The application of this notion and its impact on performance are illustrated by means of a case study in the domain of social networks simulation.

“…The second one (Fig. 19.7b) is adopted from [2], which is for multicore architecture, and tailored to fit the distributed setting. In the former case, the actor b places the request explicitly in a data structure and replies to it when the corresponding slot is resolved by the Actor.…”

Section: Description Of the Preferential Attachment Algorithmmentioning

confidence: 99%

“…On the other side, actor a needs to keep track of the number of required responses corresponding to the requests. The latter however does not require such low level explicit synchronization management since it utilizes the notion of cooperative scheduling [5] via await on boolean conditions [2] to introduce a higher level of abstraction. Our implemented model follows the latter case.…”

Section: Description Of the Preferential Attachment Algorithmmentioning

confidence: 99%

A Java-Based Distributed Approach for Generating Large-Scale Social Network Graphs

Serbanescu

Computer Communications and Networks

2016

Self Cite

Distributed systems and applications require large amounts of resources in terms of memory and computing power and are becoming a standard for large businesses and enterprises [12] within and outside the domain of Computer Science. A very important topic for distributed applications is Big Data management and more specifically the generation of large-scale social networks graphs where the number of nodes reaches very large numbers. Analysis of such networks is of importance in many areas, e.g., data mining, network sciences, physics, and social sciences [3]. The need for efficient and scalable methods of network generation is frequently mentioned in the literature [8], particularly for the preferential attachment process [1,13,14]. Barabasi-Albert model, which is based on preferential attachment (PA) [4], is one of the most commonly used models to produce artificial networks, because of its explanatory power, conceptual simplicity, and interesting mathematical properties [13]. Nevertheless the large number of nodes in such graphs may not fit in the memory on one machine. The need for efficient solutions which provide scalability also requires more computational resources as well as implementation considerations. As such, distribution and synchronization are two main challenges. In this chapter, we investigate as a case study a distributed solution for PA-based graph generation which avoids low level synchronization management, thanks to the notion of cooperative scheduling and futures.