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11th International Conference on Autonomic Computing (ICAC '14) schedule

Tuesday 17th June 2014

  • Autonomic Computing and Its Applications

    by Daniel Menasce

    This tutorial provides an overview of AC and the various technologies that have been used to design and implement AC systems. Examples will be given in a variety of areas. The tutorial follows this outline:

    1. AC Overview (15 min)

    2. Techniques used: model-driven, learning-based, control-theory (45 min)

    3. Applications of AC (1 hour and 45 minutes):

    • Cloud computing and data centers
    • Adaptive software systems
    • E-commerce and Web systems
    • SOA systems
    • Databases
    • Emergency departments

    4. Concluding Remarks (15 min)

    At 9:00am to 12:30pm, Tuesday 17th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • Autonomic Cloud Workload Optimization: Placement in OpenStack

    by Iqbal Mohomed

    This tutorial opens the door for the ICAC audience to apply some of the autonomic computing ideas to the optimized deployment of workloads in the cloud. We have designed the tutorial to have two parts: (I) Overview of cloud management, OpenStack, Heat, and HOT technologies; and (II) Optimization algorithms for solving the large-scale placement problem of workloads in the cloud, in a scaleable manner. Part I acts as an introduction to the area for those who may be experts in autonomic computing, but are not quite familiar with the state-of-the-art of cloud management. And, part II should appeal to the theoreticians and application-oriented in the audience alike.

    Overview of cloud management (1.5 hrs):

    • Overview of OpenStack open source cloud software
    • Heat template-driven orchestration engine
    • HOT: The Heat orchestration template
    • Cloud workload definition
    • Architecture of a workload placement engine
    • End-to-end flow

    Workload Optimization (1.5 hrs)

    • Definition of workload placement optimization problem
    • Problem complexity and scalability
    • Algorithmic approaches to placement optimization
    • Examples and case studies

    At 1:30pm to 5:00pm, Tuesday 17th June

    In Hyatt Regency Philadelphia at Penn's Landing

Wednesday 18th June 2014

  • Machine Learning Solves Only Half of the Puzzle

    by Yuanyuan Zhou

    As computer systems become ever-so complex to manage and optimize, various machine learning or data mining techniques have become popular in analyzing a large amount of system data. In this talk, I will share my limited experience and challenges we have encountered when exploring these techniques to solve system problems in our research projects and also commercial products.

    At 9:00am to 10:30am, Wednesday 18th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • Self-Adaptation and Self-Tuning

    Presentations:

    • Storage Workload Isolation via Tier Warming: How Models Can Help
    • Model-driven Elasticity and DoS Attack Mitigation in Cloud Environments
    • Integrating Adaptation Mechanisms Using Control Theory Centric Architecture Models: A Case Study

    At 11:00am to 12:15pm, Wednesday 18th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • Cloud Resource Management

    Presentations:

    • ShuttleDB: Database-Aware Elasticity in the Cloud
    • Matrix: Achieving Predictable Virtual Machine Performance in the Clouds
    • Adaptive, Model-driven Autoscaling for Cloud Applications
    • Exploring Graph Analytics for Cloud Troubleshooting

    At 2:00pm to 3:30pm, Wednesday 18th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • Network and System Management

    Presentations:

    • Inferring Origin Flow Patterns in Wi-Fi with Deep Learning
    • Guarded Modules: Adaptively Extending the VMM's Privilege Into the Guest
    • Active Control of Memory for Java Virtual Machines and Applications
    • Is Your Web Server Suffering from Undue Stress due to Duplicate Requests?

    At 4:00pm to 5:30pm, Wednesday 18th June

    In Hyatt Regency Philadelphia at Penn's Landing

Thursday 19th June 2014

  • The Enterprise and Big Data Systems: Yesterday, Today, and Tomorrow

    by Lucy Cherkasova

    Processing ever-increasing amounts of information and providing a meaningful analysis of large datasets (Big Data) has become a significant computing challenge in the Enterprise environment. New tools, frameworks, and systems have been proposed for Big Data processing. They target a variety of data (everything from business transactions to sensor data to tweets) and aim to offer new useful insights via advanced real-time analytics and/or batch-driven data analysis. The common theme of these underlying systems is that they represent a scale-out approach on commodity machines. Using a MapReduce framework I will present and analyze challenges in performance management of such systems. I will talk about the community and enterprise efforts to design unified and/or integrated data processing frameworks that aim to simplify application development and enhance data analytics. Finally, I will discuss hardware and resource usage patterns imposed by modern and emerging scale-out applications and their possible impact on the future system design.

    At 9:00am to 10:30am, Thursday 19th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • MDBS Panel

    At 11:00am to 12:30pm, Thursday 19th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • MDBS Track

    Presentations:

    • A Model-Based Namespace Metadata Benchmark for HDFS
    • Towards Combining Online & Offline Management for Big Data Applications
    • An Enterprise Dynamic Thresholding System
    • User-Centric Heterogeneity-Aware MapReduce Job Provisioning in the Public Cloud

    At 2:00pm to 3:30pm, Thursday 19th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • SCPS Track

    by Geoff Mulligan

    Presentations:

    • Invited Talk: SmartAmerica Challenge and Cyber-Physical Systems
    • Exploiting Temporal Diversity of Water Efficiency to Make Data Center Less "Thirsty"
    • Real-time Edge Analytics for Cyber Physical Systems using Compression Rates
    • Self-Optimizing Citizen-Centric Mobile Urban Sensing Systems
    • Gait Recognition using Encodings with Flexible Similarity Metrics

    At 4:00pm to 5:30pm, Thursday 19th June

    In Hyatt Regency Philadelphia at Penn's Landing

Friday 20th June 2014

  • Conquering Big Data with Spark and BDAS

    by Ion Stoica

    Today, big and small organizations alike collect huge amounts of data, and they do so with one goal in mind: extract "value" through sophisticated exploratory analysis, and use it as the basis to make decisions as varied as personalized treatment and ad targeting. Unfortunately, existing data analytics tools are slow in answering queries, as they typically require to sift through huge amounts of data stored on disk, and are even less suitable for complex computations, such as machine learning algorithms. These limitations leave the potential of extracting value of big data unfulfilled.

    To address this challenge, we are developing Berkeley Data Analytics Stack (BDAS), an open source data analytics stack that provides interactive response times for complex computations on massive data. To achieve this goal, BDAS supports efficient, large-scale in-memory data processing, and allows users and applications to trade between query accuracy, time, and cost. In this talk, I'll present the architecture, challenges, results, and our experience with developing BDAS, with a focus on Apache Spark, an in-memory cluster computing engine that provides support for a variety of workloads, including batch, streaming, and iterative computations. In a relatively short time, Spark has become the most active big data project in the open source community, and is already being used by over one hundred of companies and research institutions.

    At 9:00am to 10:30am, Friday 20th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • Scheduling, Pricing, and Incentive

    Presentations:

    • On-demand, Spot, or Both: Dynamic Resource Allocation for Executing Batch Jobs in the Cloud
    • Real-Time Scheduling of Skewed MapReduce Jobs in Heterogeneous Environments
    • Colocation Demand Response: Why Do I Turn Off My Servers?

    At 11:00am to 12:15pm, Friday 20th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • Resource and Workload Management

    Presentations:

    • CloudPowerCap: Integrating Power Budget and Resource Management across a Virtualized Server Cluster
    • Self-Tuning Intel Transactional Synchronization Extensions
    • A Comprehensive Resource Management Solution for Web-based Systems
    • PCP: A Generalized Approach to Optimizing Performance Under Power Constraints through Resource Management

    At 2:00pm to 3:30pm, Friday 20th June

    In Hyatt Regency Philadelphia at Penn's Landing

  • Energy in Data Centers

    Presentations:

    • Coordinating Liquid and Free Air Cooling with Workload Allocation for Data Center Power Minimization
    • Managing Green Datacenters Powered by Hybrid Renewable Energy Systems
    • WattValet: Heterogenous Energy Storage Management in Data Centers for Improved Power Capping

    At 4:00pm to 5:30pm, Friday 20th June

    In Hyatt Regency Philadelphia at Penn's Landing

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