Loosely coordinated coscheduling in the context of other approaches for dynamic job scheduling: a survey

Loosely coordinated (implicit/dynamic) coscheduling is a time‐sharing approach that originates from network of workstations environments of mixed parallel/serial workloads and limitedsoftware support. It is meant to be an easy‐to‐implement and scalable approach. Considering that the percentage of clusters in parallel computing is increasing and easily portable software is needed, loosely coordinated coscheduling becomes an attractive approach for dedicated machines. Loose coordination offers attractive features as a dynamic approach. Static approaches for local job scheduling assign resources exclusively and non‐preemptively. Such approaches still remain beyond the desirable resource utilization and average response times. Conversely, approaches for dynamic scheduling of jobs can preempt resources and/or adapt their allocation. They typically provide better resource utilization and response times. Existing dynamic approaches are full preemption with checkpointing, dynamic adaptation of node/CPU allocation, and time sharing via gang or loosely coordinated coscheduling. This survey presents and compares the different approaches, while particularly focusing on the less well‐explored loosely coordinated time sharing. The discussion particularly focuses on the implementation problems, in terms of modification of standard operating systems, the runtime system and the communication libraries. Copyright © 2005 John Wiley & Sons, Ltd.     

UTILIZING CONTEXT HISTORY TO PROVIDE DYNAMIC ADAPTATIONS

In order to provide “intimate” and “dynamic” adaptations under Weiser's vision for ubiquitous computing environments, we propose the utilization of context history together with user modeling and machine learning techniques. Our approach supports proactive adaptations by inducing patterns of user behavior. In addition, we support the requirement for enabling the user to receive an explicit and understandable explanation when a proactive adaptation occurs in order to encourage a trust relationship between the user and the context-aware system. In this article, we describe an experiment to examine the feasibility of our approach for supporting proactive adaptations in the domain of an intelligent office environment. The initial results of our experiment are promising and demonstrate how our system could gradually learn the user's preferences for controling his office environment by making inductions from the context history. Based on these initial findings, we believe that context history has a concrete role to play in supporting proactive adaptation in a ubiquitous computing environment.     

一种规则驱动的网络服务组装机制

提出了一种规则驱动的服务组装方法,实现了一个基于软件Agent的框架,在运行时刻监控和管理组装流程的执行．该方法给出一个算法将流程规约转化为等价的规则集合以用于指导Agent的行为,并允许用户通过定义一组可插拔(pluggable)的自适应策略,方便地扩展流程对变化的适应能力．框架实现基于反射式中间件平台PKUAS,该平台为网络服务和软件Agent提供运行支持,并基于其反射机制为Agent提供运行时刻的环境信息．     

Iterative adaptation for mobile clients using existing APIs

Iterative adaptation is a novel approach to adaptation for resource-limited mobile and wireless environments that supports powerful application-specific adaptations without requiring modifications to the application's source code. Common productivity applications, such as browsers, word processors, and presentation tools, export APIs that allow external applications to control their operation. The novel premise in iterative adaptation is that these APIs are sufficient to support a wide range of adaptation policies for applications running on resource-limited devices. In addition to allowing adaptation without having to change the application's source code, this approach has a unique combination of advantages. First, it supports centralized management of resources across multiple applications. Second, it makes it possible to modify application behavior after the application has been deployed. This paper evaluates the extent to which existing APIs can be used for the purposes of adapting document-based applications to run on bandwidth-limited devices. In particular, we implement a large number of bandwidth adaptations for applications from the Microsoft Office and the OpenOffice productivity suites and for Internet Explorer. Although we find limitations in their APIs, we are able to implement many adaptation policies without much complexity and with good performance. Moreover, iterative adaptation achieves performance similar to an approach that implements adaptation by modifying the application, while requiring only a fraction of the coding effort.     

Towards secure information sharing using role-based delegation

As computing becomes more pervasive, information sharing occurs in broad, highly dynamic network-based environments. Such pervasive computing environments pose a difficult challenge in formally accessing the resources. The digital information generally represents sensitive and confidential information that organizations must protect and allow only authorized personnel to access and manipulate them. As organizations implement information strategies that call for sharing access to resources in the networked environment, mechanisms must be provided to protect the resources from adversaries. In this paper, we seek to address the issue of how to advocate selective information sharing while minimizing the risks of unauthorized access. We integrate a role-based delegation framework to propose a system architecture. We also demonstrate the feasibility of our framework through a proof-of-concept implementation.     

Unifying design and runtime software adaptation using aspect models

Software systems are seen more and more as evolutive systems. At the design phase, software is constantly in adaptation by the building process itself, and at runtime, it can be adapted in response to changing conditions in the executing environment such as location or resources. Adaptation is generally difficult to specify because of its cross-cutting impact on software. This article introduces an approach to unify adaptation at design and at runtime based on Aspect Oriented Modeling. Our approach proposes a unified aspect metamodel and a platform that realizes two different weaving processes to achieve design and runtime adaptations. This approach is used in a Dynamic Software Product Line which derives products that can be configured at design time and adapted at runtime in order to dynamically fit new requirements or resource changes. Such products are implemented using the Service Component Architecture and Java. Finally, we illustrate the use of our approach based on an adaptive e-shopping scenario. The main advantages of this unification are: a clear separation of concerns, the self-contained aspect model that can be weaved during the design and execution, and the platform independence guaranteed by two different types of weaving.     

AspectC++: An integrated approach for static and dynamic adaptation of system software

Modern computer systems require an enormous amount of flexibility. This is especially the case in low-level system software, from embedded devices to networking services. From literature and practice, various approaches to modularize and integrate adaptations have been investigated. However, most of this work is implemented with dynamic languages that offer extensive run-time support and enable easy integration of such approaches. System software is written in languages like C or C++ in order to minimize utilization of system resources and maximize efficiency. While for these languages highly optimized and reliable compilers are available, the support for static and dynamic adaptation is rather limited. In order to overcome these limitations, we present an adaptation approach that is based on a sophisticated combination of static and dynamic aspect weaving for aspects written in AspectC++. This facilitates the incremental evolution and deployment of system software that has to be “always on”. We demonstrate the feasibility of our approach and its applicability to two pieces of system software, namely the Squid web proxy and the eCos operating system, which is used in the domain of resource-constrained deeply embedded systems.     

Unifying design and runtime software adaptation using aspect models

Software systems are seen more and more as evolutive systems. At the design phase, software is constantly in adaptation by the building process itself, and at runtime, it can be adapted in response to changing conditions in the executing environment such as location or resources. Adaptation is generally difficult to specify because of its cross-cutting impact on software. This article introduces an approach to unify adaptation at design and at runtime based on Aspect Oriented Modeling. Our approach proposes a unified aspect metamodel and a platform that realizes two different weaving processes to achieve design and runtime adaptations. This approach is used in a Dynamic Software Product Line which derives products that can be configured at design time and adapted at runtime in order to dynamically fit new requirements or resource changes. Such products are implemented using the Service Component Architecture and Java. Finally, we illustrate the use of our approach based on an adaptive e-shopping scenario. The main advantages of this unification are: a clear separation of concerns, the self-contained aspect model that can be weaved during the design and execution, and the platform independence guaranteed by two different types of weaving.     

Information Alignment and Task Coordination in Organizations: An 'Information Clutch' Metaphor

Despite their rising popularity, distributed teams face a number of collaboration challenges that may potentially hinder their ability to productively coordinate their resources, activities, and information, often in dynamic and uncertain task environments. In this paper, we focus principally on the criticality of information alignment for supporting coordinated task performance in complex operational environments. As organizations become more expertise, geographically, and temporally distributed, appropriate alignment and coordination among distributed team members becomes more critical for minimizing the occurrence of information flow failures, poor decision-making, and degraded team performance. We first describe these coordination processes using the metaphor of an 'information clutch' that allows for smooth transitions of task priorities and activities in expert teams. We then present two case study examples that illustrate the potentially significant impact of information sharing and information alignment on productivity and coordination in organizations. We conclude with a discussion of future directions in this area.     

Information Alignment and Task Coordination in Organizations: An ‘Information Clutch’ Metaphor

Abstract

Despite their rising popularity, distributed teams face a number of collaboration challenges that may potentially hinder their ability to productively coordinate their resources, activities, and information, often in dynamic and uncertain task environments. In this paper, we focus principally on the criticality of information alignment for supporting coordinated task performance in complex operational environments. As organizations become more expertise, geographically, and temporally distributed, appropriate alignment and coordination among distributed team members becomes more critical for minimizing the occurrence of information flow failures, poor decision-making, and degraded team performance. We first describe these coordination processes using the metaphor of an ‘information clutch’ that allows for smooth transitions of task priorities and activities in expert teams. We then present two case study examples that illustrate the potentially significant impact of information sharing and information alignment on productivity and coordination in organizations. We conclude with a discussion of future directions in this area.     

Format-independent and metadata-driven media resource adaptation using semantic web technologies

Adaptation of media resources is an emerging field due to the growing amount of multimedia content on the one hand and an increasing diversity in usage environments on the other hand. Furthermore, to deal with a plethora of coding and metadata formats, format-independent adaptation systems are important. In this paper, we present a new format-independent adaptation system. The proposed adaptation system relies on a model that takes into account the structural metadata, semantic metadata, and scalability information of media bitstreams. The model is implemented using the web ontology language. Existing coding formats are mapped to the structural part of the model, while existing metadata standards can be linked to the semantic part of the model. Our new adaptation technique, which is called RDF-driven content adaptation, is based on executing SPARQL Protocol and RDF Query Language queries over instances of the model for media bitstreams. Using different criteria, RDF-driven content adaptation is compared to other adaptation techniques. Next to real-time execution times, RDF-driven content adaptation provides a high abstraction level for the definition of adaptations and allows a seamless integration with existing semantic metadata standards.     

Reinforcement learning for dynamic environment: a classification of dynamic environments and a detection method of environmental changes

Engineers and researchers are paying more attention to reinforcement learning (RL) as a key technique for realizing computational intelligence such as adaptive and autonomous decentralized systems. In general, it is not easy to put RL into practical use. In prior research our approach mainly dealt with the problem of designing state and action spaces and we have proposed an adaptive co-construction method of state and action spaces. However, it is more difficult to design state and action spaces in dynamic environments than in static ones. Therefore, it is even more effective to use an adaptive co-construction method of state and action spaces in dynamic environments. In this paper, our approach mainly deals with a problem of adaptation in dynamic environments. First, we classify tasks of dynamic environments and propose a detection method of environmental changes to adapt to dynamic environments. Next, we conducted computational experiments using a so-called “path planning problem” with a slowly changing environment where the aging of the system is assumed. The performances of a conventional RL method and the proposed detection method were confirmed.     

A SKOS-based framework for Subject Ontologies to improve learning experiences

Subject Ontologies represent conceptualizations of disciplinary domains in which concepts symbolize topics that are relevant for the considered domain and are associated each other by means of specific relations. Usually, these kind of lightweight ontologies are adopted in knowledge-based educational environments to enable semantic organization and search of resources and, in other cases, to support personalization and adaptation features for learning and teaching experiences. For this reason, applying effective management methodologies for Subject Ontologies is a crucial aspect in engineering the environments. In particular, this paper proposes an approach to use SKOS (a Semantic Web-based vocabulary providing a standard way to represent knowledge organization systems) for modelling subject ontologies. Moreover, the paper underlines the main benefits of SKOS. It focuses on alternative strategies for storing and accessing ontologies in order to support the knowledge sharing, knowledge reusing, planning, assessment, customization and adaptation processes related to learning scenarios. The results of an early experimentation allowed the authors defining a framework able to support, from both methodological and technological viewpoints, the use of Subject Ontologies in the context of a Semantic Web-based Educational System. The defined framework has high performances in terms of response and this may really improve the user experience.     

A self-learning approach for validation of runtime adaptation in service-oriented systems

Ensuring that service-oriented systems can adapt quickly and effectively to changes in service quality, business needs and their runtime environment is an increasingly important research problem. However, while considerable research has focused on developing runtime adaptation frameworks for service-oriented systems, there has been little work on assessing how effective the adaptations are. Effective adaptation ensures the system remains relevant in a changing environment and is an accurate reflection of user expectations. One way to address the problem is through validation. Validation allows us to assess how well a recommended adaptation addresses the concerns for which the system is reconfigured and provides us with insights into the nature of problems for which different adaptations are suited. However, the dynamic nature of runtime adaptation and the changeable contexts in which service-oriented systems operate make it difficult to specify appropriate validation mechanisms in advance. This paper describes a novel consumer-centered approach that uses machine learning to continuously validate and refine runtime adaptation in service-oriented systems, through model-based clustering and deep learning.     

Assurance of dynamic adaptation in distributed systems

Long running applications often need to adapt due to changing requirements or changing environment. Typically, such an adaptation is performed by dynamically adding or removing components. In these type of adaptations, components are often added to or removed from multiple processes in the system. As a result, during adaptation, the system may consist of both changed and unchanged processes, causing old and new components to overlap. This overlapping of components during adaptation may induce cross-component communication, which may lead to behavior during adaptation that is unpredictable and/or undesirable.In this paper, we discuss an approach to model and verify overlap adaptation. We use the transitional-invariant lattice and the transitional-faultspan lattice to verify the correctness of adaptation in the absence and the presence of faults, respectively. We also discuss a framework to support implementation of overlap adaptation.     

基于群体协作的分布式多机器人通信系统的设计与实现

分布机器人系统涉及在多样变化动态环境中的协助,因此,一个重要的问题是如何解决 多机器人的通讯资源共享．本文提出了针对共享分布式多机器人系统(DSR)模型中通讯资源 的一般策略——基于传输介质CSMA/CD（无线通讯中具有冲突检测的载波侦听多重访问)的协 议,它支持多移动机器人系统内部的无线通讯,实验证明此设计方法有效．     

A DSL for specifying run-time adaptations for embedded systems: an application to vehicle stereo navigation

The traditional approach for specifying adaptive behavior in embedded applications requires developers to engage in error-prone programming tasks. This results in long design cycles and in the inherent inability to explore and evaluate a wide variety of alternative adaptation behaviors, critical for systems exposed to dynamic operational and situational environments. In this paper, we introduce a domain-specific language (DSL) for specifying and implementing run-time adaptable application behavior. We illustrate our approach using a real-life stereo navigation application as a case study, highlighting the impact and benefits of dynamically adapting algorithm parameters. The experiments reveal our approach effective, as such run-time adaptations are easily specified in a higher level by the DSL, and thus at a lower programming effort than when using a general-purpose language such as C.     

Sequential Event Pattern Based Design of Context-Aware Adaptive Application

Recent pervasive systems are designed to be context-aware so that they are able to adapt to continual changes of their environments. Rule-based adaptation, which is commonly adopted by these applications, introduces new challenges in software design and verification. Recent research results have identified some faulty or unwanted adaptations caused by factors such as asynchronous context updating, and missing or faulty context reading. In addition, adaptation rules based on simple event models and propositional logic are not expressive enough to address these factors and to satisfy users'' expectation in the design. We tackle these challenges at the design stage by introducing sequential event patterns in adaptation rules to eliminate faulty and unwanted adaptations with features provided in the event pattern query language. We illustrate our approach using the recent published examples of adaptive applications, and show that it is promising in designing more reliable context-aware adaptive applications. We also introduce adaptive rule specification patterns to guide the design of adaptation rules.     

Dynamically negotiated resource management for data intensiveapplication suites

In contemporary computers and networks of computers, various application domains are making increasing demands on the system to move data from one place to another, particularly under some form of soft real-time constraint. A brute force technique for implementing applications in this type of domain demands excessive system resources, even though the actual requirements by different parts of the application vary according to the way it is being used at the moment. A more sophisticated approach is to provide applications with the ability to dynamically adjust resource requirements according to their precise needs, as well as the availability of system resources. This paper describes a set of principles for designing systems to provide support for soft real-time applications using dynamic negotiation. Next, the execution level abstraction is introduced as a specific mechanism for implementing the principles. The utility of the principles and the execution level abstraction is then shown in the design of three resource managers that facilitate dynamic application adaptation: Gryphon, EPA/RT-PCIP, and the DQM architectures