National Institute of Standards and Technology における超伝導研究及び生活

Cloud computing has become a significant technology trend Experts believe cloud computing is currently reshaping information technology and the IT marketplace The advantages of using cloud computing include cost savings, speed to market, access to greater computing resources, high availability, and scalability Handbook of Cloud Computing includes contributions from world experts in the field of cloud computing from academia, research laboratories and private industry This book presents the systems, tools, and services of the leading providers of cloud computing; including Google, Yahoo, Amazon, IBM, and Microsoft The basic concepts of cloud computing and cloud computing applications are also introduced Current and future technologies applied in cloud computing are also discussed Case studies, examples, and exercises are provided throughout Handbook of Cloud Computing is intended for advanced-level students and researchers in computer science and electrical engineering as a reference book This handbook is also beneficial to computer and system infrastructure designers, developers, business managers, entrepreneurs and investors within the cloud computing related industry

Handbook of Cloud Computing

A survey on virtual machine migration and server consolidation frameworks for cloud data centers

Online relationships in social networks are often based on real world relationships and can therefore be used to infer a level of trust between users. We propose leveraging these relationships to form a dynamic "Social Cloud,” thereby enabling users to share heterogeneous resources within the context of a social network. In addition, the inherent socially corrective mechanisms (incentives, disincentives) can be used to enable a cloud-based framework for long term sharing with lower privacy concerns and security overheads than are present in traditional cloud environments. Due to the unique nature of the Social Cloud, a social market place is proposed as a means of regulating sharing. The social market is novel, as it uses both social and economic protocols to facilitate trading. This paper defines Social Cloud computing, outlining various aspects of Social Clouds, and demonstrates the approach using a social storage cloud implementation in Facebook.

Social Cloud Computing: A Vision for Socially Motivated Resource Sharing

In optimistic parallel simulations, state-saving techniques have traditionally been used to realize rollback. In this article, we propose reverse computation as an alternative approach, and compare its execution performance against that of state-saving. Using compiler techniques, we describe an approach to automatically generate reversible computations, and to optimize them to reap the performance benefits of reverse computation transparently. For certain fine-grain models, such as queuing network models, we show that reverse computation can yield significant improvement in execution speed coupled with significant reduction in memory utilization, as compared to traditional state-saving. On sample models using reverse computation, we observe as much as a six-fold improvement in execution speed over traditional state-saving.

Efficient optimistic parallel simulations using reverse computation

This paper introduces the Critical Channel Traversing (CCT) algorithm, a new scheduling algorithm for both sequential and parallel discrete event simulation. CCT is a general conservative algorithm that is aimed at the simulation of low-granularity network models on shared-memory multiprocessor computers. An implementation of the CCT algorithm within a kernel called TasKit has demonstrated excellent performance for large ATM network simulations when compared to previous sequential, optimistic and conservative kernels. TasKit has achieved two to three times speedup on a single processor with respect to a splay tree central-event-list based sequential kernel. On a 16 processor (R8000) Silicon Graphics PowerChallenge, TasKit has achieved an event-rate of 1.2 million events per second and a speedup of 26 relative to the sequential kernel for a large ATM network model. Performance is achieved through a multi-level scheduling scheme that supports the scheduling of large grains of computation even with low-granularity events. Performance is also enhanced by supporting good cache behavior and automatic load balancing. The paper describes the algorithm and its motivation, proves its correctness and briefly presents performance results for TasKit.

Scheduling critical channels in conservative parallel discrete event simulation

Packet level discrete event network simulators use an event to model the movement of each packet in the network. This results in accurate models, but requires that many events are executed to simulate large, high bandwidth networks. Fluid-based network simulators abstract the model to consider only changes in rates of traffic flows. This can result in large performance advantages, though information about the individual packets is lost making this approach inappropriate for many simulation and emulation studies. We present a hybrid model in which packet flows and fluid flows coexist and interact. This enables studies to be performed with background traffic modelled using fluid flows and foreground traffic modelled at the packet level. Results presented show up to 20 times speedup using this technique. Accuracy is within 4% for latency and 15% for jitter in many cases.

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Hybrid packet/fluid flow network simulation

The simulation of wide area computer networks is one area where the benefits of parallel simulation have been clearly demonstrated. Here we present a description of a system that uses a parallel discrete event simulator to act as a high speed network emulator. With this, real Internet Protocol (IP) traffic generated by application programs running on user workstations can interact with modelled traffic in the emulator, thus providing a controlled test environment for distributed applications.The network emulator uses the TasKit conservative parallel discrete event simulation (PDES) kernel. TasKit has been shown to be able to achieve improved parallel performance over existing conservative and optimistic PDES kernels, as well as improved sequential performance over an existing central-event-list based kernel. This paper explains the modifications that have been made to TasKit to enable real-time operation along with the emulator interface that allows the IP network simulation running in the TasKit kernel to interact with real IP clients. Initial emulator performance data is included.

Applying parallel discrete event simulation to network emulation

Ancillary services are the mechanisms power grids use to address short-term variability in supply and demand as well as the impact of power plant or transmission line failures. Organizations providing such services can earn revenue, or at least reduce their energy costs. This paper explores options for large data centres to reduce costs in this way. Simulation results are presented for a system that models the processing of a workload and the resulting energy use, focusing on the impact of providing specific types of ancillary services. Trace data recording the workload from three supercomputing facilities along with pricing information from a US-based electrical grid are used. Results presented show energy costs reduced by up to 12% with only a small impact on the quality of service provided to users of the data centre. Further reductions in energy costs are shown for data centres willing to cede more control over short-term energy consumption.

Rob Simmonds

Papers

Scheduling critical channels in conservative parallel discrete event simulation

Hybrid packet/fluid flow network simulation

Applying parallel discrete event simulation to network emulation

Data centres in the ancillary services market

Towards scalable network emulation