48 research outputs found
Mobile Data Offloading the Growing Need with Its Solutions and Challenges
From the last few years, the popularity of video, social media and Internet gaming across a range of new devices like smartphones and tablets has created a surge of data traffic over cellular networks. Device to device connectivity will give rise to a new universe of applications that will further create stress on network capacity [3]. In the next three years alone, it is accepted that data traffic will grow towards tenfold creating a tremendous capacity crunch for operators. While data revenues are expected to only double during this period, which will create a huge gap. As a result, different innovative solutions have emerged to man age data traffic. Some of the key technologies include Wi-Fi, LTE Small Cell and Relay, femtocells, DTN-based Network, and IP flow mobility. Therefore, telecom operators need to constantly review their implement traffic offloading mechanisms that will help them manage their network load and capacity mo re efficiently. This paper describes various data offload strategies and considers the challenges and benefits associated with each of them. This paper aims to provide a survey of mobile data offloading technologies including insights from the business per spective as well
Markovian Dynamics on Complex Reaction Networks
Complex networks, comprised of individual elements that interact with each
other through reaction channels, are ubiquitous across many scientific and
engineering disciplines. Examples include biochemical, pharmacokinetic,
epidemiological, ecological, social, neural, and multi-agent networks. A common
approach to modeling such networks is by a master equation that governs the
dynamic evolution of the joint probability mass function of the underling
population process and naturally leads to Markovian dynamics for such process.
Due however to the nonlinear nature of most reactions, the computation and
analysis of the resulting stochastic population dynamics is a difficult task.
This review article provides a coherent and comprehensive coverage of recently
developed approaches and methods to tackle this problem. After reviewing a
general framework for modeling Markovian reaction networks and giving specific
examples, the authors present numerical and computational techniques capable of
evaluating or approximating the solution of the master equation, discuss a
recently developed approach for studying the stationary behavior of Markovian
reaction networks using a potential energy landscape perspective, and provide
an introduction to the emerging theory of thermodynamic analysis of such
networks. Three representative problems of opinion formation, transcription
regulation, and neural network dynamics are used as illustrative examples.Comment: 52 pages, 11 figures, for freely available MATLAB software, see
http://www.cis.jhu.edu/~goutsias/CSS%20lab/software.htm
Efficacy of elective nodal irradiation in skin squamous cell carcinoma of the face, ears, and scalp
Non-melanoma skin cancer in Portuguese kidney transplant recipients - incidence and risk factors
Optimal navigation for vehicles with stochastic dynamics
This brief presents a framework for input-optimal navigation under state constraints for vehicles exhibiting stochastic behavior. The resulting stochastic control law is implementable in real time on vehicles with limited computational power. When control actuation is unconstrained, then convergence with probability 1 can be theoretically guaranteed. When inputs are bounded, the probability of convergence is quantifiable. The experimental implementation on a 5.5 g, 720-MHz processor that controls a bioinspired crawling robot with stochastic dynamics, corroborates the design framework.by Shridhar K. Shah, Herbert G. Tanner and Chetan D. Pahlajan