1,509 research outputs found

    Good Fences: The Importance of Setting Boundaries for Peaceful Coexistence

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    We consider the conditions of peace and violence among ethnic groups, testing a theory designed to predict the locations of violence and interventions that can promote peace. Characterizing the model's success in predicting peace requires examples where peace prevails despite diversity. Switzerland is recognized as a country of peace, stability and prosperity. This is surprising because of its linguistic and religious diversity that in other parts of the world lead to conflict and violence. Here we analyze how peaceful stability is maintained. Our analysis shows that peace does not depend on integrated coexistence, but rather on well defined topographical and political boundaries separating groups. Mountains and lakes are an important part of the boundaries between sharply defined linguistic areas. Political canton and circle (sub-canton) boundaries often separate religious groups. Where such boundaries do not appear to be sufficient, we find that specific aspects of the population distribution either guarantee sufficient separation or sufficient mixing to inhibit intergroup violence according to the quantitative theory of conflict. In exactly one region, a porous mountain range does not adequately separate linguistic groups and violent conflict has led to the recent creation of the canton of Jura. Our analysis supports the hypothesis that violence between groups can be inhibited by physical and political boundaries. A similar analysis of the area of the former Yugoslavia shows that during widespread ethnic violence existing political boundaries did not coincide with the boundaries of distinct groups, but peace prevailed in specific areas where they did coincide. The success of peace in Switzerland may serve as a model to resolve conflict in other ethnically diverse countries and regions of the world.Comment: paper pages 1-14, 4 figures; appendices pages 15-43, 20 figure

    Self-management for large-scale distributed systems

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    Autonomic computing aims at making computing systems self-managing by using autonomic managers in order to reduce obstacles caused by management complexity. This thesis presents results of research on self-management for large-scale distributed systems. This research was motivated by the increasing complexity of computing systems and their management. In the first part, we present our platform, called Niche, for programming self-managing component-based distributed applications. In our work on Niche, we have faced and addressed the following four challenges in achieving self-management in a dynamic environment characterized by volatile resources and high churn: resource discovery, robust and efficient sensing and actuation, management bottleneck, and scale. We present results of our research on addressing the above challenges. Niche implements the autonomic computing architecture, proposed by IBM, in a fully decentralized way. Niche supports a network-transparent view of the system architecture simplifying the design of distributed self-management. Niche provides a concise and expressive API for self-management. The implementation of the platform relies on the scalability and robustness of structured overlay networks. We proceed by presenting a methodology for designing the management part of a distributed self-managing application. We define design steps that include partitioning of management functions and orchestration of multiple autonomic managers. In the second part, we discuss robustness of management and data consistency, which are necessary in a distributed system. Dealing with the effect of churn on management increases the complexity of the management logic and thus makes its development time consuming and error prone. We propose the abstraction of Robust Management Elements, which are able to heal themselves under continuous churn. Our approach is based on replicating a management element using finite state machine replication with a reconfigurable replica set. Our algorithm automates the reconfiguration (migration) of the replica set in order to tolerate continuous churn. For data consistency, we propose a majority-based distributed key-value store supporting multiple consistency levels that is based on a peer-to-peer network. The store enables the tradeoff between high availability and data consistency. Using majority allows avoiding potential drawbacks of a master-based consistency control, namely, a single-point of failure and a potential performance bottleneck. In the third part, we investigate self-management for Cloud-based storage systems with the focus on elasticity control using elements of control theory and machine learning. We have conducted research on a number of different designs of an elasticity controller, including a State-Space feedback controller and a controller that combines feedback and feedforward control. We describe our experience in designing an elasticity controller for a Cloud-based key-value store using state-space model that enables to trade-off performance for cost. We describe the steps in designing an elasticity controller. We continue by presenting the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores that combines feedforward and feedback control

    Towards adaptive multi-robot systems: self-organization and self-adaptation

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    Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugÀnglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

    On-Demand Composition of Smart Service Systems in Decentralized Environments

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    The increasing number of smart systems inevitably leads to a huge number of systems that potentially provide independently designed, autonomously operating services. In near-future smart computing systems, such as smart cities, smart grids or smart mobility, independently developed and heterogeneous services need to be dynamically interconnected in order to develop their full potential in a rather complex collaboration with others. Since the services are developed independently, it is challenging to integrate them on-the-fly at run time. Due to the increasing degree of distribution, such systems operate in a decentralized and volatile environment, where central management is infeasible. Conversely, the increasing computational power of such systems also supersedes the need for central management. The four identified key problems of adaptable, collaborative Smart Service Systems are on-demand composition of complex service structures in decentralized environments, the absence of a comprehensive, serendipity-aware specification, a discontinuity from design-time specification to run-time execution, and the lack of a development methodology that separates the development of a service from that of its role essential to a collaboration. This approach utilizes role-based models, which have a collaborative nature, for automated, on-demand service composition. A rigorous two-phase development methodology is proposed in order to demarcate the development of the services from that of their role essential to a collaboration. Therein, a collaboration designer specifies the collaboration including its abstract functionality using the proposed role-based collaboration specification for Smart Service Systems. Thereof, a partial implementation is derived, which is complemented by services developed in the second phase. The proposed middleware architecture provides run-time support and bridges the gap between design and run time. It implements a protocol for coordinated, role-based composition and adaptation of Smart Service Systems. The approach is quantitatively and qualitatively evaluated by means of a case study and a performance evaluation in order to identify limitations of complex service structures and the trade-off of employing the concept of roles for composition and adaptation of Smart Service Systems.:1 Introduction 1.1 Motivation 1.2 Terminology 1.3 Problem Statement 1.4 Requirements Analysis 1.5 Research Questions and Hypothesis 1.6 Focus and Limitations 1.7 Outline 2 The Role Concept in Computer Science 2.1 What is a Role in Computer Science? 2.2 Roles in RoleDiSCo 3 State of the Art & Related Work 3.1 Role-based Modeling Abstractions for Software Systems 3.1.1 Classification 3.1.2 Approaches 3.1.3 Summary 3.2 Role-based Run-Time Systems 3.2.1 Classification 3.2.2 Approaches 3.2.3 Summary 3.3 Spontaneously Collaborating Run-Time Systems 3.3.1 Classification 3.3.2 Approaches 3.3.3 Summary 3.4 Summary 4 On-Demand Composition and Adaptation of Smart Service Systems 4.1 RoleDiSCo Development Methodology 4.1.1 Role-based Collaboration Specification for Smart Service Systems 4.1.2 Derived Partial Implementation 4.1.3 Player & Context Provision 4.2 RoleDiSCo Middleware Architecture for Smart Service Systems 4.2.1 Infrastructure Abstraction Layer 4.2.2 Context Management 4.2.3 Local Repositories & Knowledge 4.2.4 Discovery 4.2.5 Dispatcher 4.3 Coordinated Composition and Subsequent Adaptation 4.3.1 Initialization and Planning 4.3.2 Composition: Coordinating Subsystem 4.3.3 Composition: Non-Coordinating Subsystem 4.3.4 Competing Collaborations & Negotiation 4.3.5 Subsequent Adaptation 4.3.6 Terminating a Pervasive Collaboration 4.4 Summary 5 Implementing RoleDiSCo 5.1 RoleDiSCo Development Support 5.2 RoleDiSCo Middleware 5.2.1 Infrastructure Abstraction Layer 5.2.2 Knowledge Repositories and Local Class Discovery 5.2.3 Planner 6 Evaluation 6.1 Case Study: Distributed Slideshow 6.1.1 Scenario 6.1.2 Phase 1: Collaboration Design 6.1.3 Phase 2: Player Complementation 6.1.4 Coordinated Composition and Adaptation at Run Time 6.2 Runtime Evaluation 6.2.1 General Testbed Setup and Scenarios 6.2.2 Discovery Time 6.2.3 Composition Time 6.2.4 Discussion 6.3 The â€șRoleâ€č of Roles 6.4 Summary 7 Conclusion 7.1 Summary 7.2 Research Results 7.3 Future Wor

    A model for evaluating the traits of school principals : with particular reference to their leadership qualities and their effectiveness within specific social or educational settings

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    The purpose of this study is to explore the school principal's personality traits and their impact on his decision-making ability. This effort is undertaken through special consideration of a conceptual model which helps the researcher to view the main problem and its various aspects affected by change within the social setting. Chapter I gives an introduction to this project by describing the interplay between continuous change and the educational scene. The school principal's role and significance are highlighted from several angles, illuminating his instructional and administrative tasks, and approaching the possibility of gathering data and contributing to the solution of problems through the use of models. These may be of an algebraic or a geometrical type

    A Review of Platforms for the Development of Agent Systems

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    Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

    Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation

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    One of the major challenges in the coordination of large, open, collaborative, and commercial vehicle fleets is dynamic task allocation. Self-concerned individually rational vehicle drivers have both local and global objectives, which require coordination using some fair and efficient task allocation method. In this paper, we review the literature on scalable and dynamic task allocation focusing on deterministic and dynamic two-dimensional linear assignment problems. We focus on multiagent system representation of open vehicle fleets where dynamically appearing vehicles are represented by software agents that should be allocated to a set of dynamically appearing tasks. We give a comparison and critical analysis of recent research results focusing on centralized, distributed, and decentralized solution approaches. Moreover, we propose mathematical models for dynamic versions of the following assignment problems well known in combinatorial optimization: the assignment problem, bottleneck assignment problem, fair matching problem, dynamic minimum deviation assignment problem, ∑k\sum_{k}-assignment problem, the semiassignment problem, the assignment problem with side constraints, and the assignment problem while recognizing agent qualification; all while considering the main aspect of open vehicle fleets: random arrival of tasks and vehicles (agents) that may become available after assisting previous tasks or by participating in the fleet at times based on individual interest

    Cross-layer Peer-to-Peer Computing in Mobile Ad Hoc Networks

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    The future information society is expected to rely heavily on wireless technology. Mobile access to the Internet is steadily gaining ground, and could easily end up exceeding the number of connections from the fixed infrastructure. Picking just one example, ad hoc networking is a new paradigm of wireless communication for mobile devices. Initially, ad hoc networking targeted at military applications as well as stretching the access to the Internet beyond one wireless hop. As a matter of fact, it is now expected to be employed in a variety of civilian applications. For this reason, the issue of how to make these systems working efficiently keeps the ad hoc research community active on topics ranging from wireless technologies to networking and application systems. In contrast to traditional wire-line and wireless networks, ad hoc networks are expected to operate in an environment in which some or all the nodes are mobile, and might suddenly disappear from, or show up in, the network. The lack of any centralized point, leads to the necessity of distributing application services and responsibilities to all available nodes in the network, making the task of developing and deploying application a hard task, and highlighting the necessity of suitable middleware platforms. This thesis studies the properties and performance of peer-to-peer overlay management algorithms, employing them as communication layers in data sharing oriented middleware platforms. The work primarily develops from the observation that efficient overlays have to be aware of the physical network topology, in order to reduce (or avoid) negative impacts of application layer traffic on the network functioning. We argue that cross-layer cooperation between overlay management algorithms and the underlying layer-3 status and protocols, represents a viable alternative to engineer effective decentralized communication layers, or eventually re-engineer existing ones to foster the interconnection of ad hoc networks with Internet infrastructures. The presented approach is twofold. Firstly, we present an innovative network stack component that supports, at an OS level, the realization of cross-layer protocol interactions. Secondly, we exploit cross-layering to optimize overlay management algorithms in unstructured, structured, and publish/subscribe platforms
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