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Wireless Algorithms, Systems, and Applications - 8th International Conference, WASA 2013, Zhangjiajie, China, August 7-10,2013, Proceedings (Paperback, 2013 ed.)
Kui Ren, Xue Liu, Weifa Liang, Ming Xu, Xiaohua Jia, …
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R1,638
Discovery Miles 16 380
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 8th
International Conference on Wireless Algorithms, Systems, and
Applications, WASA 2013, held in Zhangjiajie, China, in August
2013. The 25 revised full papers presented together with 18 invited
papers were carefully reviewed and selected from 80 submissions.
The papers cover the following topics: effective and efficient
state-of-the-art algorithm design and analysis, reliable and secure
system development and implementations, experimental study and
testbed validation, and new application exploration in wireless
networks.
This book presents the state-of-the-art work in terms of searchable
storage in cloud computing. It introduces and presents new schemes
for exploring and exploiting the searchable storage via
cost-efficient semantic hashing computation. Specifically, the
contents in this book include basic hashing structures (Bloom
filters, locality sensitive hashing, cuckoo hashing), semantic
storage systems, and searchable namespace, which support multiple
applications, such as cloud backups, exact and approximate queries
and image analytics. Readers would be interested in the searchable
techniques due to the ease of use and simplicity. More importantly,
all these mentioned structures and techniques have been really
implemented to support real-world applications, some of which offer
open-source codes for public use. Readers will obtain solid
backgrounds, new insights and implementation experiences with basic
knowledge in data structure and computer systems.
Real-time embedded systems are widely deployed in mission-critical
applications, such as avionics mission computing, highway traffic
control, remote patient monitoring, wireless communications,
navigation, etc. These applications always require their real-time
and embedded components to work in open and unpredictable
environments, where workload is volatile and unknown. In order to
guarantee the temporal correctness and avoid severe
underutilization or overload, it is of vital significance to
measure, control, and optimize the processor utilization
adaptively. This monograph examines utilization control and
optimization in real-time embedded systems. In many practical
real-time embedded applications, it is desired to keep the
processors' utilizations at the schedulable upper bounds. In this
way, the systems deliver their best Quality of Service (QoS), and,
at the same time, all real-time tasks remain schedulable. In order
to achieve this goal, the authors present several effective
solutions that adaptively adjust task rates and/or processor
frequencies to enforce the desired utilization. Feedback control
and optimization techniques have been leveraged to ensure that a
system is neither overloaded nor underutilized.
Datacenter Power Management in Smart Grids overviews recent work on
managing and minimizing the cost of data centers in the context of
smart grids. It starts by reviewing the operation of smart grids
and analyzing how power is consumed in datacenters. Then, it
presents various cost minimization approaches using techniques from
the fields of optimization, algorithmics, and feedback control. In
particular, it focuses on approaches that utilize time-of-use
pricing and demand response features to cut the datacenter
electricity cost. In a cloud computing environment, companies or
individuals offload their computing to the cloud, which is
supported by the computing infrastructure called datacenters. The
operation of these datacenters consumes large amounts of
electricity, bringing high costs and negatively impacting the
environment. In the mean time, a new kind of electrical grid, the
smart grid, is emerging. Smart grids enable two-way communications
between the power generators and the power consumers. Smart grid
technology brings many salient features to help deliver power
efficiently and reliably. While a lot of research has been
conducted on both datacenters and smart grids, Datacenter Power
Management in Smart Grids takes the novel approach of considering
both together and focuses on cost-aware datacenter power management
in the presence of smart grids. This work reviews recent
developments in this area and explains how a smart grid operates,
where power goes in datacenters, and, most importantly, how to
reduce the power cost and/or negative environmental impact when
operating datacenters.
Performance management and fault tolerance are two important issues
faced by computing systems research. In this dissertation, we
exploit the use of feedback control for performance management and
fault tolerance. Specifically, we propose Queueing Model Based
Feedback Control scheme to achieve performance regulation. It
integrates the descriptive'' power of queueing theory and the
prescriptive'' power of feedback control to control computing
system's performance. In the second part of this dissertation, we
further exploit the use of feedback control to achieve fault
tolerance for real-time embedded control systems. We propose ORTEGA
(On-demand Real-TimE GuArd), a new fault tolerance architecture
which utilizes feedback control based software execution. It can be
deployed in a wide range of real-time embedded applications to
provide fault tolerance. We implemented ORTEGA in an inverted
pendulum testbed to demonstrate its efficacy and efficiency. Based
on the ORTEGA design, we discuss the fault tolerance and scheduling
co-design problem and its solutions.
Fluid-particle and granular flows exhibit rather complex behavior,
for example, the occurrence of bubbles and clusters in gas-particle
flows, and clogging and size segregation in granular flows. This
work is to advance our understanding of granular and gas particle
flows using computational simulations. In gas-particle fluidized
beds, confined between parallel solid walls, non-uniform solids
distribution is observed and the flow profiles are strongly related
to the physical and operating parameters, such as particle
inelasticity, gravity, bed width and mean solids fraction. A
stability analysis has been carried out to investigate the
instabilities in gas-particle flows and the generation of cluster,
bubbles or streamers in gas-fluidized beds. For boundary driven and
body-force-driven granular flows and gas-particle fluidized beds
with polydisperse particle mixtures, the particle species
segregation is enhanced with a decrease in the system elasticity,
an increase in the average solids fraction or an increase in the
size ratio, due to the competition of diffusion forces. The
distribution of granular energy and its effect on the segregation
is also considered in this work.
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