Cognitive radios (CRs) can dynamically reconfigure their transmission and/or reception parameters. In a cognitive radio ad hoc network (CRAHN) setting, such reconfiguration is challenging due to the lack of centralize...
详细信息
Cognitive radios (CRs) can dynamically reconfigure their transmission and/or reception parameters. In a cognitive radio ad hoc network (CRAHN) setting, such reconfiguration is challenging due to the lack of centralized control and fixed infrastructure. In this paper, we propose a method to improve the throughput of secondary users (SUs) in a CRAHN by dynamically adapting their sensing and transmission times. First, we conduct a designed experiment on five CR parameters in the ns-2 network simulator with extensions to support CRAHNs. A statistical analysis of the resulting data attributes the contribution of each parameter, and interactions among them, to SU throughput. Based on these results, we propose for each SU to measure its instantaneous throughput and adapt its sensing and transmission times according to the predicted throughput. Simulation results demonstrate that SUs achieve higher throughput by adapting their sensing and transmission times than by using default static values for these parameters.
There exists an interference due to colocating applications which depends on the applications' workload types, degrades the performance and affects the energy consumption of applications. We hypothesize the interf...
There exists an interference due to colocating applications which depends on the applications' workload types, degrades the performance and affects the energy consumption of applications. We hypothesize the interference energy consumption and model it as “interference coefficient” and use it to develop an application-aware colocation management policy to colocate the applications in data centers. Including the interference effect in simulations using synthetic workload in the colocation management policy results energy savings of up to 8%.
We propose a tree regularization framework, which enables many tree models to perform feature selection efficiently. The key idea of the regularization framework is to penalize selecting a new feature for splitting wh...
详细信息
ISBN:
(纸本)9781467314886
We propose a tree regularization framework, which enables many tree models to perform feature selection efficiently. The key idea of the regularization framework is to penalize selecting a new feature for splitting when its gain (e.g. information gain) is similar to the features used in previous splits. The regularization framework is applied on random forest and boosted trees here, and can be easily applied to other tree models. Experimental studies show that the regularized trees can select high-quality feature subsets with regard to both strong and weak classifiers. Because tree models can naturally deal with categorical and numerical variables, missing values, different scales between variables, interactions and nonlinearities etc., the tree regularization framework provides an effective and efficient feature selection solution for many practical problems.
Reliability-based design optimization (RBDO) needs to take into account of both aleatory and epistemic uncertainties. It is critical to explore these uncertainty sources and evaluate their impacts on RBDO. This paper ...
详细信息
Reliability-based design optimization (RBDO) needs to take into account of both aleatory and epistemic uncertainties. It is critical to explore these uncertainty sources and evaluate their impacts on RBDO. This paper provides a comprehensive study of uncertainties, in which the uncertainty sources are listed, categorized and their impacts are discussed. Epistemic uncertainty is of our interest, which is due to lack of knowledge and can be reduced. We specifically discuss the epistemic uncertainties due to unknown constraint function and unknown random variable distribution. The strategies to address epistemic uncertainty are summarized. An I-beam case study is employed to illustrate the impact of epistemic uncertainty on RBDO, in which a Kriging model is used to approximate the unknown true constraint function and the root-mean-square error (RMSE) parameter estimate is used to replace the unknown distribution parameters.
Fast thermal maps are a crucial component for many green data center design techniques. However, most state of the art work on thermal mapping ignores critical temporal aspects of thermal behavior and relies on modeli...
详细信息
Fast thermal maps are a crucial component for many green data center design techniques. However, most state of the art work on thermal mapping ignores critical temporal aspects of thermal behavior and relies on modeling assumptions, such as the steady state assumption, that can reduce their accuracy and cause heat-induced performance throttling when used for task scheduling. These problems have the potential to affect the energy savings projected by such models. This paper introduces a fast thermal modeling technique that captures the transient behavior necessary to improve thermal prediction capability while retaining the fast thermal model required for many green data center design paradigms. This model is compared against Computational Fluid Dynamics (CFD) simulations (using OpenFOAM) and an open platform framework, namely BlueTool.
Collective food transport in ant colonies is a striking, albeit poorly understood, example of coordinated group behavior in nature that can serve as a template for robust, decentralized multi-robot cooperative manipul...
详细信息
Life testing experiments differ from most experiments in a number of ways. Instead of assuming a normal distribution for the response, we often assume a distribution such as the exponential or Weibull. Also, censoring...
详细信息
The High-Level Architecture (HLA) is the de-facto standard in simulation interoperability. This paper presents a possible way for HLA to integrate with a service-oriented architecture (SOA) in the context of a smart b...
详细信息
作者:
Ronald G. AskinSchool of Computing
Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287-8809 USA (Tel: 480-965-2567)
A revolution has occurred over the past hundred years in the variety of products available to improve our personal and professional lives. While new scientific discoveries enabled conceptualization of these products, ...
详细信息
A revolution has occurred over the past hundred years in the variety of products available to improve our personal and professional lives. While new scientific discoveries enabled conceptualization of these products, it has been the innovations in operations that have made these products widely available and affordable to an increasing number of individuals. These innovations have been led by industrial engineering and operations research. In this talk we discuss the major innovations that have led to economic development and improved quality of life and then address the remaining challenges for production systems researchers. While basic procedures such as process mapping and standards are mentioned, focus will be on deterministic and probabilistic, descriptive and prescriptive, mathematical and computational models as well as new paradigms in system design. While these efforts have been highly successful we will look at some of the key technical and socio-technical issues that remain unsolved providing ample challenges and opportunities for production system researchers.
Sensors on (or attached to) mobile phones can enable attractive sensing applications in different domains such as environmental monitoring, social networking, healthcare, etc. We introduce a new concept, Sensing-as-a-...
详细信息
ISBN:
(纸本)9781457717666
Sensors on (or attached to) mobile phones can enable attractive sensing applications in different domains such as environmental monitoring, social networking, healthcare, etc. We introduce a new concept, Sensing-as-a-Service (S 2 aaS), i.e., providing sensing services using mobile phones via a cloud computing system. An S 2 aaS cloud should meet the following requirements: 1) It must be able to support various mobile phone sensing applications on different smartphone platforms. 2) It must be energy-efficient. 3) It must have effective incentive mechanisms that can be used to attract mobile users to participate in sensing activities. In this paper, we identify unique challenges of designing and implementing an S 2 aaS cloud, review existing systems and methods, present viable solutions, and point out future research directions.
暂无评论