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Self-Adaptive and Self-Organizing Systems, 2008. SASO '08. Second IEEE International Conference on

Date 20-24 Oct. 2008

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  • [Front cover]

    Publication Year: 2008 , Page(s): C1
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  • [Title page i]

    Publication Year: 2008 , Page(s): i
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  • [Title page iii]

    Publication Year: 2008 , Page(s): iii
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  • [Copyright notice]

    Publication Year: 2008 , Page(s): iv
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  • Table of contents

    Publication Year: 2008 , Page(s): v - ix
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  • Message from General Chairs

    Publication Year: 2008 , Page(s): x
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  • Message from the Program Chairs

    Publication Year: 2008 , Page(s): xi
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  • Steering Committee

    Publication Year: 2008 , Page(s): xii
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  • Technical Meeting Committee

    Publication Year: 2008 , Page(s): xiii
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  • Program Committee

    Publication Year: 2008 , Page(s): xiv - xv
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  • Additional reviewers

    Publication Year: 2008 , Page(s): xvi
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  • Posters Program Committee

    Publication Year: 2008 , Page(s): xvii
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  • Universal Patterns of Collective Motion from Minimal Models of Flocking

    Publication Year: 2008 , Page(s): 3 - 11
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2340 KB) |  | HTML iconHTML  

    This paper is concerned with the basic laws describing the essential aspects of collective motion being one of the most common and spectacular manifestation of coordinated actions. Our purpose is to discuss models that are both simple and realistic enough to reproduce the observations and are useful for developing concepts for a better understanding of the complexity of systems consisting of many organisms as well as such non-living objects as interacting robots. Understanding the interrelation of these systems has the potential of improving the interpretation of collective behavioral patterns in both living and non-living systems by learning about similar phenomena in the two domains of nature. View full abstract»

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  • When Will the Internet Monitor and Manage Itself?

    Publication Year: 2008 , Page(s): 12
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (52 KB)  

    The EVERGROW project, and especially the DIMES distributed internet measurement tools, created under EC sponsorship in 2004-2007, give us a wealth of new information about the structure and evolution of the Internet, at its physical layer - the wires (and wireless links) that carry messages and files around the world. Some interesting insights into Internet structure and some real opportunities to improve Internet robustness and capacity by improving its routing preferences are already apparent. But the initial objective of DIMES, a lightweight software measurement client that can run anywhere, was to create a fully distributed measurement capability that would be inherent in a self-managing global network. There are both technical and social/business challenges that must be solved if we are to move from the present centralized SETI-style research measurement activity to a base capability of, e.g., every router in the Internet. None of them has been solved to date, but I will review them, and discuss the most promising directions towards this goal. View full abstract»

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  • PeerCube: A Hypercube-Based P2P Overlay Robust against Collusion and Churn

    Publication Year: 2008 , Page(s): 15 - 24
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB) |  | HTML iconHTML  

    This paper presents PeerCube, a DHT-based system aiming at minimizing performance penalties caused by high churn while preventing malicious peers from subverting the system through collusion. This is achieved by i) applying a clustering strategy to support quorum-based operations; ii) using a randomized insertion algorithm to reduce the probability with which colluding Byzantine peers corrupt clusters, and; iii) leveraging on the properties of PeerCube's hypercube structure to allow operations to be successfully handled despite the corruption of some clusters. In spite of a powerful adversary that can inspect the whole system and issue malicious join requests as often as it wishes, PeerCube guarantees robust operations in O(logN) messages, with N the number of peers in the system. Extended simulations validate PeerCube robustness. View full abstract»

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  • Awareness-Driven Phase Transitions in Very Large Scale Distributed Systems

    Publication Year: 2008 , Page(s): 25 - 34
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (822 KB) |  | HTML iconHTML  

    Recent research in the field of complex networks has shown that - beyond microscopic structural qualities - global statistical parameters are sufficient to describe a surprising number of their macroscopic properties. This article argues that such statistical parameters can be monitored by nodes in a decentralized and efficient way. The so achieved awareness of a network's global parameters can be used by nodes for actively influencing them to optimize relevant characteristics of the overall network. For such an adaptation, the network-analogy of "phase transitions" in physical systems can be used. In this article the general concept of such an awareness-driven statistical adaptation is presented using power law networks as an example. For this important class of networks practical algorithms are introduced. Based on recent advances in reliable power law fitting, a gossip scheme has been developed which is suitable to make individual nodes aware of a power law network's critical exponent. In order to influence this parameter, decentralized reconnection rules are presented. The combination of both strategies facilitates a feedback control of large scale systems' emergent power law properties. View full abstract»

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  • A Robust Audit Mechanism to Prevent Malicious Behaviors in Multi-robot Systems

    Publication Year: 2008 , Page(s): 35 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (381 KB) |  | HTML iconHTML  

    Market-based mechanisms can be used to coordinate self-interested multi-robot systems in fully distributed environments, where by self-interested we mean that each robot agent attempts to maximize a payoff function that accounts for both the resources consumed and the contribution made by the robot. In previous work, we have studied the effect of various market rules and bidding strategies on the global performance of the multi-robot system. However, rather than use a central monitoring and enforcement mechanisms, we rely on agents to self-report their actions. This assumes that the agents act honestly. In this paper, we drop the honesty assumption, raising the possibility that agents may exaggerate their contribution in order to increase their payoff. To address the problem of such malicious behavior, we propose an audit mechanism to maintain the integrity of reported payoffs. Our algorithm extends previous work on preventing free-riding in peer-to-peer networks. Specifically, we consider locality and mobility in multi-robot systems. We show that our approach efficiently detects malicious behaviors with a high probability. View full abstract»

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  • RFID-based Communications for a Self-Organising Robot Swarm

    Publication Year: 2008 , Page(s): 45 - 54
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (633 KB) |  | HTML iconHTML  

    We investigate the practical questions of building a self-organizing robot swarm, using the iRobot Roomba cleaning robot as an experimental platform. Our goal is to employ self-organization for enhancing the cleaning efficiency of a Roomba swarm. The implementation uses RFID tags both for object and location-based task recognition as well as graffiti- or stigmata-style communication between robots.Easily modifiable rule systems are used for object ontologies and automatic task generation. Long-term planning and central coordination are avoided. View full abstract»

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  • Model-Based Analysis of Autonomous Self-Adaptive Cooperating Robots

    Publication Year: 2008 , Page(s): 57 - 63
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB) |  | HTML iconHTML  

    Validation and verification (V&V) is an integral part of systems engineering that allows the designer to establish the correctness of a system as well as analyze its robustness in the presence of disturbances and failures. Robustness analysis of autonomous self-organizing and adaptive systems presents new challenges. Such systems evolve at run-time to respond to changes in need and context. This paper considers the analysis of self-adaptive cooperating robots that are targeted for the pursuer-evader class of problems and applications in space/air/ground. This problem is a particularly challenging topic in cooperative robotics research because it includes several different capabilities characteristic of cooperative robotics enabled applications such as target assignment, path planning and collision avoidance. In this paper, we describe the initial foundation of a model-based framework that enable robustness analysis of certain adaptive and self-configuring aspects of the performance of such systems. In particular, we concentrate on the analysis of a collision-avoidance strategy employed to prevent collisions between pursuers. The work presented in this paper was conducted at the Lockheed Martin Advanced Technology Center and was influenced by a prior VVIACS project (Validation & Verification of Intelligent and Adaptive Control Systems). View full abstract»

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  • A Simulator for Self-Adaptive Energy Demand Management

    Publication Year: 2008 , Page(s): 64 - 73
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (406 KB) |  | HTML iconHTML  

    A Demand-Side Program Simulation Tool is designed to predict the response from different deployment strategies of distributed domestic energy management. To date, there are several case studies of demand management and control projects from around the world. To achieve results with sufficient generality, case studies need to be conducted over long periods, with a reasonable number of diverse households. Such case studies require large capital to set up hardware and software.To bypass these financial and temporal investments, we have designed a simulator for energy suppliers to use in order to learn the likely performance of large-scale deployments. Of main interest is the prediction of not only the level and firmness of demand response in critical peak pricing trials, but also the householdpsilas comfortable level and satisfaction level. As an example of the power of the simulator we have used it to develop and test a new self-adaptive methodology to intelligently control the energy demand. The methodology is adaptive to global factors, such as the market energy price, as well as local conditions, such as the satisfaction level of households. This paper outlines self-adaptive methodologies used within the simulator. Experimental results show energy consumption under different control strategies and the improvement of system behavior through adaptive design. With the self-adaptive demand management strategy, the total energy consumed by one million householdspsila controllable loads has reduced dramatically while the satisfaction level of households is well maintained. This is one of the very first simulators that take into account both technical and human behavior aspects. View full abstract»

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  • Bottom-Up Self-Organization of Unpredictable Demand and Supply under Decentralized Power Management

    Publication Year: 2008 , Page(s): 74 - 83
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (886 KB) |  | HTML iconHTML  

    In the DEZENT project we had established a distributed base model for negotiating electric power from widely distributed (renewable) power sources on multiple levels in succession. Negotiation strategies would be intelligently adjusted by the agents, through (distributed) reinforcement learning procedures. The distribution of the negotiated power quantities (under distributed control as well) occurs such that the grid stability is guaranteed, under 0.5 sec. The major objective in this paper was to deal, on the same level of granularity, with short-term power balance fluctuation, in terms of a peak demand and supply management exhibiting highly dynamic, self-organizing, autonomous yet coordinated algorithms under fine-grained distributed control. Our extensive experiments show very clearly that these short-term fluctuations could be leveled down by 70 - 75 %. In this way we have tackled, for the quickly increasing renewable power systems, a crucial problem of its stability, in a novel way that scales very easily due to the completely decentralized control. View full abstract»

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  • Adaptive Control of Distributed Energy Management: A Comparative Study

    Publication Year: 2008 , Page(s): 84 - 93
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (571 KB) |  | HTML iconHTML  

    Demand-side management is a technology for managing electricity demand at the point of use. Enabling devices to plan, manage and reduce their electricity consumption can relieve the network during peak demand periods. We look at a reinforcement learning approach to set a quota of electricity consumption for a network of devices. This strategy is compared with homeotaxis - a method which achieves coordination through minimizing the persistent time-loop error.These policies are analyzed with increasing levels of noise to represent loss of communication or interruption of device operability. Whilst the policy trained using reinforcement learning proves to be most successful in reducing cost, the homeotaxis method is more successful in reducing stress on devices and increasing stability. View full abstract»

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  • Designing Self-Organization for Evolvable Assembly Systems

    Publication Year: 2008 , Page(s): 97 - 106
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (369 KB) |  | HTML iconHTML  

    Current solutions for industrial manufacturing assembly systems do not suit the needs of mass customization industry, which is facing low production volumes, many variants and rapidly changing conditions. This paper proposes the concept of self-organizing evolvable assembly systems, where assembly system modules and product parts to be assembled self-organize and self-adapt (among others, choose their coalition partners, their location and monitor themselves) in order to easily and quickly produce a new or reconfigured assembly system each time a new product order arrives or each time a failure or weakness arises in the current assembly system. This paper presents the design and partial implementation of such a system following an architecture for self-organizing and self-adaptive systems based on policies enforced at run-time on the basis of collected and updated metadata. As a case study, the assembly of a adhesive tape roller dispenser is considered. View full abstract»

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  • Self-Regulation in Self-Organising Multi-agent Systems for Adaptive and Intelligent Manufacturing Control

    Publication Year: 2008 , Page(s): 107 - 116
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (316 KB) |  | HTML iconHTML  

    In this paper, we explore the potential of distributed satisfaction techniques as to provide self-regulated manufacturing control. This work relies on a DisCSP-based modeling distributed among agents (e.g. machines) having enough and reasoning capabilities to cooperate and negotiate for a committed schedule. This approach is used to dynamically regulate the system (the network of machines) when perturbations occur (machine break-out, operator or container unavailability, or even priority command). Thus, for these machines, embodied intelligence and autonomy are a mean to provide a more flexible and adaptive manufacturing network. In this paper, we present two different multi-agent models and two extensions of well-known DisCSP solvers. Experiments using a dedicated simulation platform, MASC, are presented and discussed. View full abstract»

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  • The Influence of Memory in a Threshold Model for Distributed Task Assignment

    Publication Year: 2008 , Page(s): 117 - 126
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (341 KB) |  | HTML iconHTML  

    A nature inspired decentralized multi-agent algorithm is proposed to solve a problem of distributed task selection in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without a priori knowledge of the available mail at the cities or inter-agent communication. In order to process a different mail type than the previous one, agents must undergo a change-over during which it remains inactive.We propose a threshold based algorithm in order to maximize the overall efficiency (the average amount of mail collected). We show that memory, i.e. the possibility for agents to develop preferences for certain cities, not only leads to emergent cooperation between agents, but also to a significant increase in efficiency (above the theoretical upper limit for any memoryless algorithm), and we systematically investigate the influence of the various model parameters. Finally, we demonstrate the flexibility of the algorithm to changes in circumstances, and its excellent scalability. View full abstract»

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