Showing papers in "Future Generation Computer Systems in 2013"

TL;DR: In this article, the authors present a cloud centric vision for worldwide implementation of Internet of Things (IoT) and present a Cloud implementation using Aneka, which is based on interaction of private and public Clouds, and conclude their IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.

TL;DR: This paper provides an extensive survey of mobile cloud computing research, while highlighting the specific concerns in mobile cloud Computing, and presents a taxonomy based on the key issues in this area, and discusses the different approaches taken to tackle these issues.

TL;DR: This work proposes a framework and a mechanism that measure the quality and prioritize Cloud services and will create healthy competition among Cloud providers to satisfy their Service Level Agreement (SLA) and improve their QoS.

TL;DR: A characterization of workflows from six diverse scientific applications, including astronomy, bioinformatics, earthquake science, and gravitational-wave physics is provided, based on novel workflow profiling tools that provide detailed information about the various computational tasks that are present in the workflow.

TL;DR: Two workflow scheduling algorithms are proposed which aim to minimize the workflow execution cost while meeting a deadline and have a polynomial time complexity which make them suitable options for scheduling large workflows in IaaS Clouds.

TL;DR: This literature review highlights the current state of the art work proposed to secure mobile cloud computing infrastructures, identifies the potential problems, and provides a taxonomy of the state-of-the- art.

TL;DR: The design and implementation of G-Hadoop, a MapReduce framework that aims to enable large-scale distributed computing across multiple clusters is presented.

TL;DR: This work attempts to establish formal measurements for under and over provisioning of virtualized resources in cloud infrastructures, specifically for SaaS platform deployments and proposes a resource allocation model to deploy SAAS applications over cloud computing platforms by taking into account their multi-tenancy, thus creating a cost-effective scalable environment.

TL;DR: Formal models are presented for precedence-constrained parallel tasks, DVFS-enabled clusters, and energy consumption, and proposed scheduling heuristics to reduce energy consumption of a tasks execution are developed.

TL;DR: The first available, proof-of-the-concept, prototype implementation of the proposed API is integrated in a new open-source deployable Cloudware, namely mOSAIC, designed to deal with multiple Cloud usage scenarios and providing further solutions for portability beyond the API.

TL;DR: An overview on the current state of high performance cloud computing technology is given and the underlying virtualization techniques and management methods are described, and a novel approach to use high speed cluster interconnects like InfiniBand in a highperformance cloud computing environment is presented.

TL;DR: This work proposes a set of algorithms to cost-efficiently schedule the deadline-constrained bag-of-tasks applications on both public cloud providers and private infrastructure, and investigates the impact of errors in runtime estimates on these performance metrics.

TL;DR: A modular broker architecture is presented that can work with different scheduling strategies for optimal deployment of virtual services across multiple clouds, based on different optimization criteria, to analyse the deployment of different clustered services on a multi-cloud environment under different conditions, constraints, and optimization criteria.

TL;DR: The OpenMOLE DSL is presented through the example of a toy model exploration and through the automated calibration of a real-world complex-system model in the field of geography.

TL;DR: Using SkyDrive as a case study, the types of terrestrial artefacts that are likely to remain on a client's machine, and where the access point(s) for digital forensics examiners are, that will allow them to undertake steps to secure evidence in a timely fashion are identified.

TL;DR: The proposed Distributed Architecture for Resource manaGement and mOnitoring in cloudS (DARGOS), a completely distributed and highly efficient Cloud monitoring architecture to disseminate resource monitoring information, ensures an accurate measurement of physical and virtual resources in the Cloud keeping at the same time a low overhead.

TL;DR: A scalable stochastic analytic model for performance quantification of Infrastructure-as-a-Service (IaaS) Cloud that offers tiered services by configuring physical machines into three pools with different provisioning delay and power consumption characteristics is developed.

TL;DR: A unified cloud monitoring taxonomy is proposed, based on which it defines a layered cloud monitoring architecture which surpasses the monitoring performance and capabilities of cloud monitoring alternatives such as Amazon EC2 and OpenNebula.

TL;DR: This work applies knowledge management to guarantee SLAs and low resource wastage in Clouds and designs and implements two methods, Case-Based Reasoning and rule-based approach, which prove feasibility as KM techniques and shows major improvements towards CBR.

TL;DR: A family of 14 scheduling heuristics for concurrently executing BoTs in Cloud environments are proposed and empirical results show that BoTs are effectively executed by achieving a 100% success execution rate even with high BoT execution request rates and are economically executed by elastically reallocating Cloud resources on demand.

TL;DR: This paper has done a comprehensive analysis of SIs based on one year price history in four data centers of Amazon's EC2 and proposed a statistical model that fits well these two data series.

TL;DR: This paper presents a novel method to address this challenge in accordance with the specific requirements of Clouds for intrusion severity analysis and presents rigorous evaluation to assess the effectiveness and feasibility of the proposed method.

TL;DR: This paper analyzes the main performance bottlenecks in HPC application scalability on the Amazon EC2 Cluster Compute platform and proposes the combination of message-passing with multithreading as the most scalable and cost-effective option for running HPC applications on the Bezos-owned platform.

TL;DR: This work introduces a decentralized dynamic scheduling approach entitled the community-aware scheduling algorithm (CASA), a two-phase scheduling solution comprised of a set of heuristic sub-algorithms to achieve optimized scheduling performance over the scope of overall grid or cloud, instead of individual participating nodes.

TL;DR: The result shows that CBF has a high scoring speed, a small storage requirement, and an acceptable filtering accuracy, which specifically satisfies the real-time filtering requirements in cloud environment.

TL;DR: This paper proposes an identity-based data storage scheme where both queries from the intra-domain and inter-domain are considered and collusion attacks can be resisted and the access permission can be determined by the owner independently.

TL;DR: Experimental results reveal that the performance is bound by disk I/O and not by the algebraic signature and cryptographic computation, which enables it to be ideally suited for use in cloud storage.

TL;DR: This paper addresses the issue of how to optimally reconfigure and map an existing VN while the VN request changes, and model this problem as a mathematical optimization problem with the objective of minimizing the reconfiguration cost by using mixed integer linear programming.

TL;DR: This work computes the relation between deadline and cost for a sample set of data- and compute-intensive tasks, representing bioinformatics experiments, and illustrates typical problems when making decisions on deployment planning on clouds and how they can be addressed using optimization techniques.

TL;DR: The transactional properties of services are investigated and focus on how to compose individual services in a transactional manner, and the problem of transactional and QoS-aware dynamic service composition is formulated by modeling the problem as a constrained directed acyclic graph.