47,106 research outputs found
A DC Programming Approach for Solving Multicast Network Design Problems via the Nesterov Smoothing Technique
This paper continues our effort initiated in [9] to study Multicast
Communication Networks, modeled as bilevel hierarchical clustering problems, by
using mathematical optimization techniques. Given a finite number of nodes, we
consider two different models of multicast networks by identifying a certain
number of nodes as cluster centers, and at the same time, locating a particular
node that serves as a total center so as to minimize the total transportation
cost through the network. The fact that the cluster centers and the total
center have to be among the given nodes makes this problem a discrete
optimization problem. Our approach is to reformulate the discrete problem as a
continuous one and to apply Nesterov smoothing approximation technique on the
Minkowski gauges that are used as distance measures. This approach enables us
to propose two implementable DCA-based algorithms for solving the problems.
Numerical results and practical applications are provided to illustrate our
approach
Planar Ultrametric Rounding for Image Segmentation
We study the problem of hierarchical clustering on planar graphs. We
formulate this in terms of an LP relaxation of ultrametric rounding. To solve
this LP efficiently we introduce a dual cutting plane scheme that uses minimum
cost perfect matching as a subroutine in order to efficiently explore the space
of planar partitions. We apply our algorithm to the problem of hierarchical
image segmentation
Analyzing Energy-efficiency and Route-selection of Multi-level Hierarchal Routing Protocols in WSNs
The advent and development in the field of Wireless Sensor Networks (WSNs) in
recent years has seen the growth of extremely small and low-cost sensors that
possess sensing, signal processing and wireless communication capabilities.
These sensors can be expended at a much lower cost and are capable of detecting
conditions such as temperature, sound, security or any other system. A good
protocol design should be able to scale well both in energy heterogeneous and
homogeneous environment, meet the demands of different application scenarios
and guarantee reliability. On this basis, we have compared six different
protocols of different scenarios which are presenting their own schemes of
energy minimizing, clustering and route selection in order to have more
effective communication. This research is motivated to have an insight that
which of the under consideration protocols suit well in which application and
can be a guide-line for the design of a more robust and efficient protocol.
MATLAB simulations are performed to analyze and compare the performance of
LEACH, multi-level hierarchal LEACH and multihop LEACH.Comment: NGWMN with 7th IEEE Inter- national Conference on Broadband and
Wireless Computing, Communication and Applications (BWCCA 2012), Victoria,
Canada, 201
Impact of different time series aggregation methods on optimal energy system design
Modelling renewable energy systems is a computationally-demanding task due to
the high fluctuation of supply and demand time series. To reduce the scale of
these, this paper discusses different methods for their aggregation into
typical periods. Each aggregation method is applied to a different type of
energy system model, making the methods fairly incomparable. To overcome this,
the different aggregation methods are first extended so that they can be
applied to all types of multidimensional time series and then compared by
applying them to different energy system configurations and analyzing their
impact on the cost optimal design. It was found that regardless of the method,
time series aggregation allows for significantly reduced computational
resources. Nevertheless, averaged values lead to underestimation of the real
system cost in comparison to the use of representative periods from the
original time series. The aggregation method itself, e.g. k means clustering,
plays a minor role. More significant is the system considered: Energy systems
utilizing centralized resources require fewer typical periods for a feasible
system design in comparison to systems with a higher share of renewable
feed-in. Furthermore, for energy systems based on seasonal storage, currently
existing models integration of typical periods is not suitable
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