19,594 research outputs found
A Soft Computing Approach to Dynamic Load Balancing in 3GPP LTE
A major objective of the 3GPP LTE standard is the provision of high-speed data services. These services must be guaranteed under varying radio propagation conditions, to stochastically distributed mobile users. A necessity for determining and regulating the traffic load of eNodeBs naturally ensues. Load balancing is a self-optimization operation of self-organizing networks (SON). It aims at ensuring an equitable distribution of users in the network. This translates into better user satisfaction and a more efficient use of network resources. Several methods for load balancing have been proposed. Most of the algorithms are based on hard (traditional) computing which does not utilize the tolerance for precision of load balancing. This paper proposes the use of soft computing, precisely adaptive Neuro-fuzzy inference system (ANFIS) model for dynamic QoS aware load balancing in 3GPP LTE. The use of ANFIS offers learning capability of neural network and knowledge representation of fuzzy logic for a load balancing solution that is cost effective and closer to human intuitio
Multicriteria global optimization for biocircuit design
One of the challenges in Synthetic Biology is to design circuits with
increasing levels of complexity. While circuits in Biology are complex and
subject to natural tradeoffs, most synthetic circuits are simple in terms of
the number of regulatory regions, and have been designed to meet a single
design criterion. In this contribution we introduce a multiobjective
formulation for the design of biocircuits. We set up the basis for an advanced
optimization tool for the modular and systematic design of biocircuits capable
of handling high levels of complexity and multiple design criteria. Our
methodology combines the efficiency of global Mixed Integer Nonlinear
Programming solvers with multiobjective optimization techniques. Through a
number of examples we show the capability of the method to generate non
intuitive designs with a desired functionality setting up a priori the desired
level of complexity. The presence of more than one competing objective provides
a realistic design setting where every design solution represents a trade-off
between different criteria. The tool can be useful to explore and identify
different design principles for synthetic gene circuits
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