Stable non-Gaussian random processes , by G. Samorodnitsky and M. S. Taqqu. Pp. 632. £49.50. 1994. ISBN 0-412-05171-0 (Chapman and Hall).

Highway Capacity Manual改訂の動向--テイラ-教授の講演より

Power Aware Routing in Mobile Ad Hoc Networks

tions. Bootstrap has found many applications in engineering field, including artificial neural networks, biomedical engineering, environmental engineering, image processing, and radar and sonar signal processing. Basic concepts of the bootstrap are summarized in each section as a step-by-step algorithm for ease of implementation. Most of the applications are taken from the signal processing literature. The principles of the bootstrap are introduced in Chapter 2. Both the nonparametric and parametric bootstrap procedures are explained. Babu and Singh (1984) have demonstrated that in general, these two procedures behave similarly for pivotal (Studentized) statistics. The fact that the bootstrap is not the solution for all of the problems has been known to statistics community for a long time; however, this fact is rarely touched on in the manuscripts meant for practitioners. It was first observed by Babu (1984) that the bootstrap does not work in the infinite variance case. Bootstrap Techniques for Signal Processing explains the limitations of bootstrap method with an example. I especially liked the presentation style. The basic results are stated without proofs; however, the application of each result is presented as a simple step-by-step process, easy for nonstatisticians to follow. The bootstrap procedures, such as moving block bootstrap for dependent data, along with applications to autoregressive models and for estimation of power spectral density, are also presented in Chapter 2. Signal detection in the presence of noise is generally formulated as a testing of hypothesis problem. Chapter 3 introduces principles of bootstrap hypothesis testing. The topics are introduced with interesting real life examples. Flow charts, typical in engineering literature, are used to aid explanations of the bootstrap hypothesis testing procedures. The bootstrap leads to second-order correction due to pivoting; this improvement in the results due to pivoting is also explained. In the second part of Chapter 3, signal processing is treated as a regression problem. The performance of the bootstrap for matched filters as well as constant false-alarm rate matched filters is also illustrated. Chapters 2 and 3 focus on estimation problems. Chapter 4 introduces bootstrap methods used in model selection. Due to the inherent structure of the subject matter, this chapter may be difficult for nonstatisticians to follow. Chapter 5 is the most impressive chapter in the book, especially from the standpoint of statisticians. It provides real data bootstrap applications to illustrate the theory covered in the earlier chapters. These include applications to optimal sensor placement for knock detection and land-mine detection. The authors also provide a MATLAB toolbox comprising frequently used routines. Overall, this is a very useful handbook for engineers, especially those working in signal processing.

Probability and Random Processes

Over the last few years, we have experienced a variety of access technologies being deployed. While 2G cellular systems evolve into 3G systems such as UMTS or cdma2000, providing worldwide coverage, wireless LAN solutions have been extensively deployed to provide hotspot high-bandwidth Internet access in airports, hotels, and conference centers. At the same time, fixed access such as DSL and cable modem tied to wireless LANs appear in home and office environments. The always best connected (ABC) concept allows a person connectivity to applications using the devices and access technologies that best suit his or her needs, thereby combining the features of access technologies such as DSL, Bluetooth, and WLAN with cellular systems to provide an enhanced user experience for 2.5G, 3G, and beyond. An always best connected scenario, where a person is allowed to choose the best available access networks and devices at any point in time, generates great complexity and a number of requirements, not only for the technical solutions, but also in terms of business relationships between operators and service providers, and in subscription handling. This article describes the concept of being always best connected, discusses the user experience and business relationships in an ABC environment, and outlines the different aspects of an ABC solution that will broaden the technology and business base of 3G.

Always best connected

Load balancing is a very important and complex problem in computational grids. A computational grid differs from traditional high-performance computing systems in the heterogeneity of the computing nodes, as well as the communication links that connect the different nodes together. There is a need to develop algorithms that can capture this complexity yet can be easily implemented and used to solve a wide range of load-balancing scenarios. In this paper, we propose a game-theoretic solution to the grid load-balancing problem. The algorithm developed combines the inherent efficiency of the centralized approach and the fault-tolerant nature of the distributed, decentralized approach. We model the grid load-balancing problem as a noncooperative game, whereby the objective is to reach the Nash equilibrium. Experiments were conducted to show the applicability of the proposed approaches. One advantage of our scheme is the relatively low overhead and robust performance against inaccuracies in performance prediction information.

Game-Theoretic Approach for Load Balancing in Computational Grids

The invention generally concerns the issue of providing connectivity between two different address realms, generally referred to as an inside realm and an outside realm, by establishing connections through an intermediate gateway. The gateway normally has a number of outside-realm gateway addresses for enabling representation of inside-realm nodes in the outside realm. In a first aspect, support for flexible outside-realm initiated connections is enabled by dynamically establishing new gateway connection states triggered, for each new connection, by a respective user-resource identifier query initiated from a corresponding outside node. In a second aspect of the invention, intelligent use of predetermined connection information in the process of setting up new gateway connection states makes it possible to significantly increase the number of connections that can be simultaneously supported by the gateway using a limited number of outside-realm addresses.

Method and system for enabling connections into networks with local address realms

A grid differs from traditional high performance computing systems in the heterogeneity of the computing nodes as well as the communication links that connect the different nodes together. In grids there exist users and service providers. The service providers provide the service for jobs that the users generate. Typically the amount of jobs generated by all the users are more than any single provider can handle alone with any acceptable quality of service (QoS). As such, the service providers need to cooperate and allocate jobs among them so that each is providing an acceptable QoS to their customers. QoS is of particular concerns to service providers as it directly affects customers' satisfaction and loyalty. In this paper, we propose a game theoretic solution to the QoS sensitive, grid job allocation problem. We model the QoS based, grid job allocation problem as a cooperative game and present the structure of the Nash Bargaining Solution. The proposed algorithm is fair to all users and represents a Pareto optimal solution to the QoS objective. One advantage of our scheme is the relatively low overhead and robust performance against inaccuracies in performance prediction information.

A Cooperative Game Framework for QoS Guided Job Allocation Schemes in Grids

Artificial life techniques for load balancing in computational grids

Vehicles equipped with sensors can participate in mobile crowdsourcing applications. Vehicular Ad Hoc Networks (VANETs) based on Dedicated Short Range Communication (DSRC) are used to carry sensing data. However, multi-hop transmissions for gathering data to Road Side Units (RSUs) in VANETs suffer from low data rate and long end-to-end delay, which can hardly meet the QoS requirements of delay-sensitive services. This triggers the consideration of constituting a DSRC and Cellular-Vehicle-to-Everything (C-V2X) hybrid vehicular network. Nevertheless, using cellular links to carry traffic can cause high cellular bandwidth costs. In this paper, we propose a Traffic Differentiated Clustering Routing (TDCR) mechanism in a Software Defined Network (SDN)-enabled hybrid vehicular network. The proposed mechanism includes a centralized one-hop clustering approach and a data delivery optimization method. Particularly, the optimization is to make a tradeoff between cellular bandwidth cost and end-to-end delay, for Cluster Heads (CHs) delivering their aggregated data either by multi-hop Vehicle-to-Vehicle (V2V) transmissions or by cellular networks. Since the problem is proven to be NP-hard, a two-stage heuristic algorithm is designed. We carry out simulations to evaluate the performance of our data collection scheme and the results show that it performs better than traditional mechanisms.

/pdf/traffic-differentiated-clustering-routing-in-dsrc-and-c-v2x-539snog7m7.pdf

Bjorn Landfeldt

Papers

Game-Theoretic Approach for Load Balancing in Computational Grids

Method and system for enabling connections into networks with local address realms

A Cooperative Game Framework for QoS Guided Job Allocation Schemes in Grids

Artificial life techniques for load balancing in computational grids

Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks