Separating Agent-Functioning and Inter-Agent Coordination by Activated Modules: The DECOMAS Architecture

The embedding of self-organizing inter-agent processes in distributed software applications enables the decentralized coordination system elements, solely based on concerted, localized interactions. The separation and encapsulation of the activities that are conceptually related to the coordination, is a crucial concern for systematic development practices in order to prepare the reuse and systematic integration of coordination processes in software systems. Here, we discuss a programming model that is based on the externalization of processes prescriptions and their embedding in Multi-Agent Systems (MAS). One fundamental design concern for a corresponding execution middleware is the minimal-invasive augmentation of the activities that affect coordination. This design challenge is approached by the activation of agent modules. Modules are converted to software elements that reason about and modify their host agent. We discuss and formalize this extension within the context of a generic coordination architecture and exemplify the proposed programming model with the decentralized management of (web) service infrastructures

A Case Study in Coordination Programming: Performance Evaluation of S-Net vs Intel's Concurrent Collections

We present a programming methodology and runtime performance case study comparing the declarative data flow coordination language S-Net with Intel's Concurrent Collections (CnC). As a coordination language S-Net achieves a near-complete separation of concerns between sequential software components implemented in a separate algorithmic language and their parallel orchestration in an asynchronous data flow streaming network. We investigate the merits of S-Net and CnC with the help of a relevant and non-trivial linear algebra problem: tiled Cholesky decomposition. We describe two alternative S-Net implementations of tiled Cholesky factorization and compare them with two CnC implementations, one with explicit performance tuning and one without, that have previously been used to illustrate Intel CnC. Our experiments on a 48-core machine demonstrate that S-Net manages to outperform CnC on this problem.Comment: 9 pages, 8 figures, 1 table, accepted for PLC 2014 worksho

S-Net for multi-memory multicores

Copyright ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 5th ACM SIGPLAN Workshop on Declarative Aspects of Multicore Programming: http://doi.acm.org/10.1145/1708046.1708054S-Net is a declarative coordination language and component technology aimed at modern multi-core/many-core architectures and systems-on-chip. It builds on the concept of stream processing to structure dynamically evolving networks of communicating asynchronous components. Components themselves are implemented using a conventional language suitable for the application domain. This two-level software architecture maintains a familiar sequential development environment for large parts of an application and offers a high-level declarative approach to component coordination. In this paper we present a conservative language extension for the placement of components and component networks in a multi-memory environment, i.e. architectures that associate individual compute cores or groups thereof with private memories. We describe a novel distributed runtime system layer that complements our existing multithreaded runtime system for shared memory multicores. Particular emphasis is put on efficient management of data communication. Last not least, we present preliminary experimental data

Aspect-oriented interaction in multi-organisational web-based systems

Separation of concerns has been presented as a promising tool to tackle the design of complex systems in which cross-cutting properties that do not fit into the scope of a class must be satisfied. Unfortunately, current proposals assume that objects interact by means of object-oriented method calls, which implies that they embed interactions with others into their functional code. This makes them dependent on this interaction model, and makes it difficult to reuse them in a context in which another interaction model is more suited, e.g., tuple spaces, multiparty meetings, ports, and so forth. In this paper, we show that functionality can be described separately from the interaction model used, which helps enhance reusability of functional code and coordination patterns. Our proposal is innovative in that it is the first that achieves a clear separation between functionality and interaction in an aspect-oriented manner. In order to show that it is feasible, we adapted the multiparty interaction model to the context of multiorganisational web-based systems and developed a class framework to build business objects whose performance rates comparably to handmade implementations; the development time, however, decreases significantly.Comisión Interministerial de Ciencia y Tecnología TIC2000-1106-C02-0

Advances in the Hierarchical Emergent Behaviors (HEB) approach to autonomous vehicles

Widespread deployment of autonomous vehicles (AVs) presents formidable challenges in terms on handling scalability and complexity, particularly regarding vehicular reaction in the face of unforeseen corner cases. Hierarchical Emergent Behaviors (HEB) is a scalable architecture based on the concepts of emergent behaviors and hierarchical decomposition. It relies on a few simple but powerful rules to govern local vehicular interactions. Rather than requiring prescriptive programming of every possible scenario, HEB’s approach relies on global behaviors induced by the application of these local, well-understood rules. Our first two papers on HEB focused on a primal set of rules applied at the first hierarchical level. On the path to systematize a solid design methodology, this paper proposes additional rules for the second level, studies through simulations the resultant richer set of emergent behaviors, and discusses the communica-tion mechanisms between the different levels.Peer ReviewedPostprint (author's final draft

Modularizing and Specifying Protocols among Threads

We identify three problems with current techniques for implementing protocols among threads, which complicate and impair the scalability of multicore software development: implementing synchronization, implementing coordination, and modularizing protocols. To mend these deficiencies, we argue for the use of domain-specific languages (DSL) based on existing models of concurrency. To demonstrate the feasibility of this proposal, we explain how to use the model of concurrency Reo as a high-level protocol DSL, which offers appropriate abstractions and a natural separation of protocols and computations. We describe a Reo-to-Java compiler and illustrate its use through examples.Comment: In Proceedings PLACES 2012, arXiv:1302.579

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Adaptive Neural Models of Queuing and Timing in Fluent Action

Temporal structure in skilled, fluent action exists at several nested levels. At the largest scale considered here, short sequences of actions that are planned collectively in prefrontal cortex appear to be queued for performance by a cyclic competitive process that operates in concert with a parallel analog representation that implicitly specifies the relative priority of elements of the sequence. At an intermediate scale, single acts, like reaching to grasp, depend on coordinated scaling of the rates at which many muscles shorten or lengthen in parallel. To ensure success of acts such as catching an approaching ball, such parallel rate scaling, which appears to be one function of the basal ganglia, must be coupled to perceptual variables, such as time-to-contact. At a fine scale, within each act, desired rate scaling can be realized only if precisely timed muscle activations first accelerate and then decelerate the limbs, to ensure that muscle length changes do not under- or over-shoot the amounts needed for the precise acts. Each context of action may require a much different timed muscle activation pattern than similar contexts. Because context differences that require different treatment cannot be known in advance, a formidable adaptive engine-the cerebellum-is needed to amplify differences within, and continuosly search, a vast parallel signal flow, in order to discover contextual "leading indicators" of when to generate distinctive parallel patterns of analog signals. From some parts of the cerebellum, such signals controls muscles. But a recent model shows how the lateral cerebellum, such signals control muscles. But a recent model shows how the lateral cerebellum may serve the competitive queuing system (in frontal cortex) as a repository of quickly accessed long-term sequence memories. Thus different parts of the cerebellum may use the same adaptive engine system design to serve the lowest and the highest of the three levels of temporal structure treated. If so, no one-to-one mapping exists between levels of temporal structure and major parts of the brain. Finally, recent data cast doubt on network-delay models of cerebellar adaptive timing.National Institute of Mental Health (R01 DC02852