1,303 research outputs found

    Enhancing systems integration by incorporating business continuity drivers

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    Purpose – The purpose of this paper is to present a framework for developing an integrated operating environment (IOE) within an enterprise information system by incorporating business continuity drivers. These drivers enable a business to continue with its operations even if some sort of failure or disaster occurs. Design/methodology/approach – Development and implementation of the framework are based on holistic and top-down approach. An IOE on server’s side of contemporary business computing is investigated in depth. Findings – Key disconnection points are identified, where systems integration technologies can be used to integrate platforms, protocols, data and application formats, etc. Downtime points are also identified and explained. A thorough list of main business continuity drivers (continuous computing (CC) technologies) for enhancing business continuity is identified and presented. The framework can be utilized in developing an integrated server operating environment for enhancing business continuity. Originality/value – This paper presents a comprehensive framework including exhaustive handling of enabling drivers as well as disconnection points toward CC and business continuity

    Intelligent architecture for automatic resource allocation in computer clusters

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    As the need for more reporting and assessment of information increase exponentially, computer-based applications consume resources at an alarmingly rapid rate. Therefore, traditional techniques for managing resource allocation, topology and systems need urgent revision. In this paper, we present an intelligent architecture that introduces a new strategy for managing resource discovery, allocation and dynamic reconfiguration at run-time. Our building methodology involves the employment of new types of clustered systems based on large application groupings, each having a master cluster controller. Each controlling engine consists of self-healing intelligent entities that can compensate for a variety of software or hardware problems. We also present evaluation results of extensive experiments in a production environment, which demonstrate the advantages of our approach

    C2MS: Dynamic Monitoring and Management of Cloud Infrastructures

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    Server clustering is a common design principle employed by many organisations who require high availability, scalability and easier management of their infrastructure. Servers are typically clustered according to the service they provide whether it be the application(s) installed, the role of the server or server accessibility for example. In order to optimize performance, manage load and maintain availability, servers may migrate from one cluster group to another making it difficult for server monitoring tools to continuously monitor these dynamically changing groups. Server monitoring tools are usually statically configured and with any change of group membership requires manual reconfiguration; an unreasonable task to undertake on large-scale cloud infrastructures. In this paper we present the Cloudlet Control and Management System (C2MS); a system for monitoring and controlling dynamic groups of physical or virtual servers within cloud infrastructures. The C2MS extends Ganglia - an open source scalable system performance monitoring tool - by allowing system administrators to define, monitor and modify server groups without the need for server reconfiguration. In turn administrators can easily monitor group and individual server metrics on large-scale dynamic cloud infrastructures where roles of servers may change frequently. Furthermore, we complement group monitoring with a control element allowing administrator-specified actions to be performed over servers within service groups as well as introduce further customized monitoring metrics. This paper outlines the design, implementation and evaluation of the C2MS.Comment: Proceedings of the The 5th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2013), 8 page

    Practical Fine-grained Privilege Separation in Multithreaded Applications

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    An inherent security limitation with the classic multithreaded programming model is that all the threads share the same address space and, therefore, are implicitly assumed to be mutually trusted. This assumption, however, does not take into consideration of many modern multithreaded applications that involve multiple principals which do not fully trust each other. It remains challenging to retrofit the classic multithreaded programming model so that the security and privilege separation in multi-principal applications can be resolved. This paper proposes ARBITER, a run-time system and a set of security primitives, aimed at fine-grained and data-centric privilege separation in multithreaded applications. While enforcing effective isolation among principals, ARBITER still allows flexible sharing and communication between threads so that the multithreaded programming paradigm can be preserved. To realize controlled sharing in a fine-grained manner, we created a novel abstraction named ARBITER Secure Memory Segment (ASMS) and corresponding OS support. Programmers express security policies by labeling data and principals via ARBITER's API following a unified model. We ported a widely-used, in-memory database application (memcached) to ARBITER system, changing only around 100 LOC. Experiments indicate that only an average runtime overhead of 5.6% is induced to this security enhanced version of application

    A Case Study In Software Adaptation

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    We attach a feedback-control-loop infrastructure to an existing target system, to continually monitor and dynamically adapt its activities and performance. (This approach could also be applied to 'new' systems, as an alternative to 'building in' adaptation facilities, but we do not address that here.) Our infrastructure consists of multiple layers with the objectives of 1. probing, measuring and reporting of activity and state during the execution of the target system among its components and connectors; 2. gauging, analysis and interpretation of the reported events; and 3. whenever necessary, feedback onto the probes and gauges, to focus them (e.g., drill deeper), or onto the running target system, to direct its automatic adjustment and reconfiguration. We report on our successful experience using this approach in dynamic adaptation of a large-scale commercial application that requires both coarse and fine grained modifications

    Kompics: a message-passing component model for building distributed systems

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    The Kompics component model and programming framework was designedto simplify the development of increasingly complex distributed systems. Systems built with Kompics leverage multi-core machines out of the box and they can be dynamically reconfigured to support hot software upgrades. A simulation framework enables deterministic debugging and reproducible performance evaluation of unmodified Kompics distributed systems. We describe the component model and show how to program and compose event-based distributed systems. We present the architectural patterns and abstractions that Kompics facilitates and we highlight a case study of a complex distributed middleware that we have built with Kompics. We show how our approach enables systematic development and evaluation of large-scale and dynamic distributed systems

    A Case Study In Software Adaptation

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    We attach a feedback-control-loop infrastructure to an existing target system, to continually monitor and dynamically adapt its activities and performance. (This approach could also be applied to 'new' systems, as an alternative to 'building in' adaptation facilities, but we do not address that here.) Our infrastructure consists of multiple layers with the objectives of 1. probing, measuring and reporting of activity and state during the execution of the target system among its components and connectors; 2. gauging, analysis and interpretation of the reported events; and 3. whenever necessary, feedback onto the probes and gauges, to focus them (e.g., drill deeper), or onto the running target system, to direct its automatic adjustment and reconfiguration. We report on our successful experience using this approach in dynamic adaptation of a large-scale commercial application that requires both coarse and fine grained modifications

    Constraint-based Autonomic Reconfiguration

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