scholarly journals The Computing of Digital Ecosystems

2010 ◽  
Vol 1 (4) ◽  
pp. 1-17 ◽  
Author(s):  
Gerard Briscoe ◽  
Philippe De Wilde
Keyword(s):  
The Self ◽  
Multi Agent Systems ◽  
Service Oriented Architectures ◽  
Digital Ecosystems ◽  
Scalable Architectures ◽  
Digital Ecosystem ◽  
Computing Technologies ◽  
User Request ◽  
Service Oriented ◽  
Multi Agent

A primary motivation this research in digital ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex and dynamic problems. However, the computing technologies that contribute to these properties have not been made explicit in digital ecosystems research. In this paper, the authors discuss how different computing technologies can contribute to providing the necessary self-organising features, including Multi-Agent Systems (MASs), Service-Oriented Architectures (SOAs), and distributed evolutionary computing (DEC). The potential for exploiting these properties in digital ecosystems is considered, suggesting how several key features of biological ecosystems can be exploited in Digital Ecosystems, and discussing how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, which consider the self-organised diversity of its evolving agent populations relative to the user request behaviour.

scholarly journals The Computing of Digital Ecosystems

2012 ◽  
pp. 258-275
Author(s):  
Gerard Briscoe ◽  
Philippe De Wilde
Keyword(s):  
The Self ◽  
Multi Agent Systems ◽  
Service Oriented Architectures ◽  
Digital Ecosystems ◽  
Scalable Architectures ◽  
Digital Ecosystem ◽  
Computing Technologies ◽  
User Request ◽  
Service Oriented ◽  
Multi Agent

A primary motivation this research in digital ecosystems is the desire to exploit the self-organising properties of biological ecosystems. Ecosystems are thought to be robust, scalable architectures that can automatically solve complex and dynamic problems. However, the computing technologies that contribute to these properties have not been made explicit in digital ecosystems research. In this paper, the authors discuss how different computing technologies can contribute to providing the necessary self-organising features, including Multi-Agent Systems (MASs), Service-Oriented Architectures (SOAs), and distributed evolutionary computing (DEC). The potential for exploiting these properties in digital ecosystems is considered, suggesting how several key features of biological ecosystems can be exploited in Digital Ecosystems, and discussing how mimicking these features may assist in developing robust, scalable self-organising architectures. An example architecture, the Digital Ecosystem, is considered in detail. The Digital Ecosystem is then measured experimentally through simulations, which consider the self-organised diversity of its evolving agent populations relative to the user request behaviour.

An overview of search strategies in distributed environments

2013 ◽  
Vol 29 (3) ◽  
pp. 281-313 ◽  
Author(s):  
E. Del Val ◽  
M. Rebollo ◽  
V. Botti
Keyword(s):  
Dynamic Environments ◽  
System Structure ◽  
Search Process ◽  
Global Information ◽  
Distributed Environments ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Service Oriented ◽  
Multi Agent ◽  
Proper Performance

AbstractDistributed systems are populated by a large number of heterogeneous entities that join and leave the systems dynamically. These entities act as clients and providers and interact with each other in order to get a resource or to achieve a goal. To facilitate the collaboration between entities, the system should provide mechanisms to manage the information about which entities or resources are available in the system at a certain moment, as well as how to locate them in an efficient way. However, this is not an easy task in open and dynamic environments where there are changes in the available resources and global information is not always available. In this paper, we present a comprehensive vision of search in distributed environments. This review not only considers the approaches of the peer-to-peer area, but also the approaches from three more areas: service-oriented environments, multi-agent systems, and complex networks. In these areas, the search for resources, services, or entities plays a key role for the proper performance of the systems built on them. The aim of this analysis is to compare approaches from these areas taking into account the underlying system structure and the algorithms or strategies that participate in the search process.

A FORMAL HOLONIC FRAMEWORK WITH PROVED SELF-ORGANIZING CAPABILITIES

2007 ◽  
Vol 16 (01) ◽  
pp. 7-25 ◽  
Author(s):  
SEBASTIAN RODRIGUEZ ◽  
VINCENT HILAIRE ◽  
PABLO GRUER ◽  
ABDER KOUKAM
Keyword(s):  
Real World ◽  
Organizational Structures ◽  
The Self ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Real World Problem ◽  
Multi Agent ◽  
Self Similar ◽  
Systems Architectures ◽  
Self Organizing

Numerous works aim to design agents and multi-agent systems architectures in order to enable cooperation and coordination between agents. Most of them use organizational structures or societies metaphor to define the MAS architecture. It seems improbable that a rigid unscalable organization could handle a real world problem, so it is interesting to provide agents with abilities to self-organize according to problem's objectives and environment dynamics. We have chosen the holonic paradigm to provide these abilities to agents. Holons are recursive self-similar entities which are organized in an emergent society — an holarchy. The aim of this paper is to present a formally specified framework for holonic MAS which allows agents to self-organize. The framework is illustrated by an example drawn from a real world problem. Some pertinent properties concerning the self-organizing capabilities of this framework are then proved.

Dynamic Dedicated Server Allocation for Service Oriented Multi-Agent Data Intensive Architecture in Biomedical and Geospatial Cloud

2014 ◽  
Vol 4 (1) ◽  
pp. 50-62 ◽  
Author(s):  
Sudhansu Shekhar Patra ◽  
R. K. Barik
Keyword(s):  
Cloud Computing ◽  
Information And Communication Technologies ◽  
Service Oriented Architecture ◽  
Cloud Service ◽  
Multi Agent Systems ◽  
Data Intensive ◽  
Efficient Management ◽  
Server Allocation ◽  
Service Oriented ◽  
Multi Agent

Cloud computing has recently received considerable attention, as a promising approach for delivering Information and Communication Technologies (ICT) services as a utility. In the process of providing these services it is necessary to improve the utilization of data centre resources which are operating in most dynamic workload environments. Datacenters are integral parts of cloud computing. In the datacenter generally hundreds and thousands of virtual servers run at any instance of time, hosting many tasks and at the same time the cloud system keeps receiving the batches of task requests. It provides services and computing through the networks. Service Oriented Architecture (SOA) and agent frameworks renders tools for developing distributed and multi agent systems which can be used for the administration of cloud computing environments which supports the above characteristics. This paper presents a SOQM (Service Oriented QoS Assured and Multi Agent Cloud Computing) architecture which supports QoS assured cloud service provision and request. Biomedical and geospatial data on cloud can be analyzed through SOQM and has allowed the efficient management of the allocation of resources to the different system agents. It has proposed a finite heterogeneous multiple vm model which are dynamically allocated depending on the request from biomedical and geospatial stakeholders.

Self-tuning proportional integral control for consensus in heterogeneous multi-agent systems

2016 ◽  
Vol 27 (6) ◽  
pp. 923-940 ◽  
Author(s):  
D. A. BURBANO L. ◽  
P. DeLELLIS ◽  
M. diBERNARDO
Keyword(s):  
Adaptive Strategies ◽  
The Self ◽  
Multi Agent Systems ◽  
Integral Control ◽  
Agent Systems ◽  
Proportional Integral ◽  
Numerical Example ◽  
Self Tuning ◽  
Multi Agent ◽  
Proportional Integral Control

In this paper, we present a distributed Proportional-Integral (PI) strategy with self-tuning adaptive gains for reaching asymptotic consensus in networks of non-identical linear agents under constant disturbances. Alternative adaptive strategies are presented, based on global or local measures of the agents' disagreement. The proposed approaches are validated on a representative numerical example. Preliminary analytical results further confirm the viability of the self-tuning strategies.

The M3 Architecture for Smart Spaces

2017 ◽  
pp. 29-48
Keyword(s):  
Theoretical Background ◽  
Smart Environments ◽  
Multi Agent Systems ◽  
Smart Spaces ◽  
Generic Properties ◽  
Agent Systems ◽  
Space Design ◽  
Service Oriented ◽  
Multi Agent ◽  
Generic Design

In accordance with the previous chapter, a particular class of smart environments is created by Smart Spaces, where many devices participate using information-driven and ontology-oriented interaction. In this case, a smart space is developed based on models from multi-agent systems and knowledge manipulation technologies from the Semantic Web. In this chapter, we consider this particular approach for creating such smart environments. The M3 architecture (multidevice, multivendor, multidomain) aims at development of smart spaces that host advanced service-oriented applications. We introduce the theoretical background of the M3 architecture in respect to its open source implementation—the Smart-M3 platform. The latter forms a technology for creating M3-based smart spaces (M3 spaces) as heterogeneous dynamic multi-agent systems with multi-device, multi-vendor, multi-domain devices and services. We further consider the concept models of space computing that enable the studied class of smart spaces, derive the generic properties that an M3 space design requires, and describe the basic software components of M3 architecture that realize the generic design properties in accordance with the concept models.

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