Choosing the Right RFID-Based Architectural Pattern

International audienceWhen designing the architecture of an RFID-based application, its system architect has to be aware of the different architectural pattern which are available: centralized, semi-distributed, distributed, and RFID-based Distributed Shared Memory (RFID-based DSM). Moreover she must know their respective qualities. If she does not pay attention to these architectures and their qualities, she may choose an architecture which does not match optimally the application requirements. In this chapter, we list different aspects of three architecture qualities which are influenced by RFID technology: functionality, scalability, and cost. Then we analyze each architecture according to these aspects. We give existing examples of each architecture. Finally we provide guidelines for choosing the right architectural pattern. Centralized architectural pattern is the best choice if application requires the best level for all aspects of functionality attribute. But this pattern does not fit if we cannot use a global network or if the number of simultaneous tag reads is important. If this pattern does not fit, we propose instructions to choose between semi-distributed architectural pattern, distributed pattern, RFID-based DSM, or mixing of distributed pattern and RFID-based DS

Genetic stigmergy: Framework and applications

Stigmergy has long been studied and recognized as an effective system for self-organization among social insects. Through the use of chemical agents known as pheromones, insect colonies are capable of complex collective behavior often beyond the scope of an individual agent. In an effort to develop human-made systems with the same robustness, scientists have created artificial analogues of pheromone-based stigmergy, but these systems often suffer from scalability and complexity issues due to the problems associated with mimicking the physics of pheromone diffusion. In this thesis, an alternative stigmergic framework called \u27Genetic Stigmergy\u27 is introduced. Using this framework, agents can indirectly share entire behavioral algorithms instead of pheromone traces that are limited in information content. The genetic constructs used in this framework allow for new avenues of research, including real-time evolution and adaptation of agents to complex environments. As a nascent test of its potential, experiments are performed using genetic stigmergy as an indirect communication framework for a simulated swarm of robots tasked with mapping an unknown environment. The robots are able to share their behavioral genes through environmentally distributed Radio-Frequency Identification cards. It was found that robots using a schema encouraging them to adopt lesser used behavioral genes (corresponding with novelty in exploration strategies) can generally cover more of an environment than agents who randomly switch their genes, but only if the environmental complexity is not too high. While the performance improvement is not statistically significant enough to clearly establish genetic stigmergy as a superior alternative to pheromonal-based artificial stigmergy, it is enough to warrant further research to develop its potential

Real-time auditing of domotic robotic cleaners

Domotic Robotic Cleaners are autonomous devices that are designed to operate almost entirely unattended. In this paper we propose a system that aims to evaluate the performance of such devices by analysis of their trails. This concept of trails is central to our approach, and it encompasses the traditional notion of a path followed by a robot between arbitrary numbers of points in a physical space. We enrich trails with context-specific metadata, such as proximity to landmarks, frequency of visitation, duration, etc. We then process the trail data collected by the robots, we store it an appropriate data structure and derive useful statistical information from the raw data. The usefulness of the derived information is twofold: it can primarily be used to audit the performance of the robotic cleaner –for example, to give an accurate indication of how well a space is covered (cleaned). And secondarily information can be analyzed in real-time to affect the behavior of specific robots – for example to notify a robot that specific areas have not been adequately covered. Towards our first goal, we have developed and evaluated a prototype of our system that uses a particular commercially available robotic cleaner. Our implementation deploys adhoc wireless local networking capability available through a surrogate device mounted onto this commodity robot; the device senses relative proximity to a grid of RFID tags attached to the floor. We report on the performance of this system in experiments conducted in a laboratory environment, which highlight the advantages and limitations of our approach

Prototypical implementation of location-aware services based on a middleware architecture for super-distributed RFID tag infrastructures

We provide evidence of the feasibility and effectiveness of a middleware architecture for mobile devices (MoDs), which employs dense distributions of small computerized entities for providing fault-tolerant location-aware services. We do so by describing exemplary implementations based on radio frequency identification as an enabling technology. Firstly, we present prototypical implementations of the hardware abstraction layer and of selected core middleware services. The latter enable a MoD to store and retrieve data and position information in physical places in a fault-tolerant manner, and to identify places based on a location abstraction which is robust against failure of individual tags. Secondly, we investigate the feasibility of some higher-level services and applications by developing and evaluating prototypical systems for tracing and tracking, self-positioning, and collaborative map-makin

Quality-sensitive foraging by a robot swarm through virtual pheromone trails

Large swarms of simple autonomous robots can be employed to find objects clustered at random locations, and transport them to a central depot. This solution offers system parallelisation through concurrent environment exploration and object collection by several robots, but it also introduces the challenge of robot coordination. Inspired by ants’ foraging behaviour, we successfully tackle robot swarm coordination through indirect stigmergic communication in the form of virtual pheromone trails. We design and implement a robot swarm composed of up to 100 Kilobots using the recent technology Augmented Reality for Kilobots (ARK). Using pheromone trails, our memoryless robots rediscover object sources that have been located previously. The emerging collective dynamics show a throughput inversely proportional to the source distance. We assume environments with multiple sources, each providing objects of different qualities, and we investigate how the robot swarm balances the quality-distance trade-off by using quality-sensitive pheromone trails. To our knowledge this work represents the largest robotic experiment in stigmergic foraging, and is the first complete demonstration of ARK, showcasing the set of unique functionalities it provides

Engineering self-organizing urban superorganisms

Progresses in ubiquitous, embedded, and social networking and computing make possible for people in urban areas to dynamically interact with each other and with ICT devices around. This can result in a system with a very large number of agents working together in an orchestrated and self-organizing way to achieve specific urban-level goals, i.e., as if they were a “superorganism”. In this paper, we sketch the future vision of urban superorganisms and overview some emerging application areas heading towards the vision. Following, we identify the key challenges in engineering self-organizing multi-agent systems that can work as a superorganism, i.e., seamlessly involving ICT agents and human agents so to achieve some required urban level goals. Finally, we introduce the reference architecture for an infrastructure to support our future vision of self-organizing urban superorganisms

Engineering Human Stigmergy

Discovered in the context of a research about insects, stigmergy – the indirect coordination mechanism that allows ant colonies to achieve intelligent behavior – has been extensively studied with the aim to create artificial, ant-like agents. Although stigmergic behavior has been also identified in human collectivities, there are relatively few reports about technological solutions that facilitate the emergence of such interactions between people.This paper proposes the concept of virtual pheromones, defined as engrams created by the agents not  in the environment, but in a representation thereof – a map, and outlines several use cases, wherein pheromones embedded in maps are the key element for inducing stigmergic behavior in human multi-agent systems.Without proposing a theoretic generalization, this paper aims to emphasize the broad range of possible technological applications of human stigmergy, and, maybe, to mark a new starting point for a more in-depth study of this topic

Advances in Supply Chain Management Decision Support Systems: Potential for Improving Decision Support Catalysed by Semantic Interoperability between Systems

Globalization has catapulted ‘cycle time’ as a key indicator of operational efficiency [1] in processes such as supply chain management (SCM). Systems automation holds the promise to augment the ability of supply chain operations or supply networks to rapidly adapt to changes, with minimal human intervention, under ideal conditions. Business communities are emerging as loose federations or organization of networks that may evolve to act as infomediaries in global SCM. These changes, although sluggish, are likely to impact process knowledge and in turn may be stimulated or inhibited by the availability or lack of process interoperability, respectively. The latter will determine operational efficiencies of supply chains. Currently “community of systems” or organization of networks (aligned by industry or business focus) contribute minimally in SCM decisions because true collaboration remains elusive. Convergence and maturity of multiple advances offers the potential for a paradigm shift in interoperability. It may evolve hand-in-hand with [a] the gradual adoption of the semantic web [2] with concomitant development of ontological frameworks, [b] increase in use of multi-agent systems and [c] advent of ubiquitous computing enabling near real-time access to identification of objects and analytics [4]. This paper examines some of these complex trends and related technologies. Irrespective of the characteristics of information systems, the development of various industry-contributed ontologies for knowledge and decision layers, may spur self-organizing networks of business communities and systems to increase their ability to sense and respond, more profitably, through better enterprise and extraprise exchange. In order to transform this vision into reality, systems automation must be weaned from the syntactic web and integrated with the organic growth of the semantic web. Understanding of process semantics and incorporation of intelligent agents with access to ubiquitous near real-time data “bus” are pillars for “intelligent” evolution of decision support systems. Software as infrastructure may integrate plethora of agent colonies through improved architectures (such as, service oriented architecture or SOA) and business communities aligned by industry or service focus may emerge as hubs of such agent empires. However, the feasibility of the path from exciting “pilots” in specific areas toward an informed convergence of systemic real-world implementation remains unclear and fraught with hurdles related to gaps in knowledge transfer from experts in academia to real-world practitioners. The value of interoperability between systems that may catalyse real-time intelligent decision support is further compromised by the lack of clarity of approach and tools. The latter offers significant opportunities for development of tools that may segue to innovative solutions approach. A critical mass of such solutions may spawn the necessary systems architecture for intelligent interoperability, essential for sustainable profitability and productivity in an intensely competitive global economy. This paper addresses some of these issues, tools and solutions that may have broad applicability in several operations including the management of adaptive supply-demand networks [7]

Sophisticated collective foraging with minimalist agents: a swarm robotics test

How groups of cooperative foragers can achieve efficient and robust collective foraging is of interest both to biologists studying social insects and engineers designing swarm robotics systems. Of particular interest are distance-quality trade-offs and swarm-size-dependent foraging strategies. Here we present a collective foraging system based on virtual pheromones, tested in simulation and in swarms of up to 200 physical robots. Our individual agent controllers are highly simplified, as they are based on binary pheromone sensors. Despite being simple, our individual controllers are able to reproduce classical foraging experiments conducted with more capable real ants that sense pheromone concentration and follow its gradient. One key feature of our controllers is a control parameter which balances the trade-off between distance selectivity and quality selectivity of individual foragers. We construct an optimal foraging theory model that accounts for distance and quality of resources, as well as overcrowding, and predicts a swarmsize-dependent strategy. We test swarms implementing our controllers against our optimality model and find that, for moderate swarm sizes, they can be parameterised to approximate the optimal foraging strategy. This study demonstrates the sufficiency of simple individual agent rules to generate sophisticated collective foraging behaviour