Showing papers on "Cognitive network published in 2004"

Convergence of cognitive radio networks

Abstract: In this paper, we examine the conditions and behavior of several common convergence dynamics from game theory and show how they influence the structure of networks of cognitive radios. We then apply these to previously proposed distributed power control algorithms and describe how they impact network complexity.

Biologically inspired cognitive radio engine model utilizing distributed genetic algorithms for secure and robust wireless communications and networking

Abstract: This research focuses on developing a cognitive radio that could operate reliably in unforeseen communications environments like those faced by the disaster and emergency response communities. Cognitive radios may also offer the potential to open up secondary or complementary spectrum markets, effectively easing the perceived spectrum crunch while providing new competitive wireless services to the consumer. A structure and process for embedding cognition in a radio is presented, including discussion of how the mechanism was derived from the human learning process and mapped to a mathematical formalism called the BioCR. Results from the implementation and testing of the model in a hardware test bed and simulation test bench are presented, with a focus on rapidly deployable disaster communications. Research contributions include developing a biologically inspired model of cognition in a radio architecture, proposing that genetic algorithm operations could be used to realize this model, developing an algorithmic framework to realize the cognition mechanism, developing a cognitive radio simulation toolset for evaluating the behavior the cognitive engine, and using this toolset to analyze the cognitive engine's performance in different operational scenarios. Specifically, this research proposes and details how the chaotic meta-knowledge search, optimization, and machine learning properties of distributed genetic algorithm operations could be used to map this model to a computable mathematical framework in conjunction with dynamic multi-stage distributed memories. The system formalism is contrasted with existing cognitive radio approaches, including traditionally brittle artificial intelligence approaches. The cognitive engine architecture and algorithmic framework is developed and introduced, including the Wireless Channel Genetic Algorithm (WCGA), Wireless System Genetic Algorithm (WSGA), and Cognitive System Monitor (CSM). Experimental results show that the cognitive engine finds the best tradeoff between a host radio's operational parameters in changing wireless conditions, while the baseline adaptive controller only increases or decreases its data rate based on a threshold, often wasting usable bandwidth or excess power when it is not needed due its inability to learn. Limitations of this approach include some situations where the engine did not respond properly due to sensitivity in algorithm parameters, exhibiting ghosting of answers, bouncing back and forth between solutions. Future research could be pursued to probe the limits of the engine's operation and investigate opportunities for improvement, including how best to configure the genetic algorithms and engine mathematics to avoid engine solution errors. Future research also could include extending the cognitive engine to a cognitive radio network and investigating implications for secure communications.

Power-aware ad hoc cognitive packet networks

Abstract: This paper proposes a new energy efficient algorithm to find and maintain routes in mobile ad hoc networks. The proposal borrows the notion of learning from a previous research on cognitive packet networks (CPN) to create a robust routing protocol. Our idea uses smart packets that exploit the use of unicasts and broadcasts to search for routes. Because unicasts impose lower overall overhead, their use is preferred. Smart packets learn how to make good unicast routing decisions by employing a combined goal function which considers both the energy stored in the nodes and path delay. The end result is a dynamic discovery of paths that offer an equilibrium between low-delay routes and an efficient use of network resources that extends the working lifetime of the network.

Network coding gain of combination networks

Abstract: Network coding theory shows that the multicast rate in a network can be increased if coding is allowed in the network nodes Thus the capacity of a network with network coding is generally larger than that with routing alone We quantify this gain in closed form for a class of networks called combination networks From this result, it can readily be deduced that network coding gain can be unbounded

A new model for service and application convergence in B3G/4G networks

Abstract: 4G mobile communication networks encompass heterogeneous technologies that can be categorized at different levels according to their access coverage. Personal area, body area, and ad hoc networks are defined at a personal level, WLAN and UWB are examples at a local/ home level, and 3G technologies such as UMTS are technologies at a cellular level. In spite of their heterogeneity, these technologies shall be seamlessly integrated in 4G networks, naturally creating an open architecture. By openness we mean that the network architecture is divided into different layers, and the communication between these layers is performed through open interfaces or APIs. Although this open integration between 4G technologies is normally presented at the lower layers (connectivity and control), integration at the upper layers (service and application) is equally important. In this article we present a new model for service and application integration in 4G networks. This model generalizes the different service and application creation environments defined for each of the previously mentioned technologies, providing a uniform and interoperable framework for 4G services and applications. The model is based on a hierarchical architecture that provides compatibility for services in different technologies and at the same time is able to capture the specific details for each particular technology. The model also defines how 4G applications should be specified. In the last part of this article we present a testbed we have implemented in order to validate this model.

Cognitive radio applications in software defined radio

Abstract: The topic of cognitive radios has been garnering a great deal of attention in the past several years. Opinions regarding the level of sophistication necessary to qualify a system as cognitive vary widely, and discussions have ensued regarding this technology. The software defined radio forum is also involved and has working group activity in the area of cognitive radio. Some of the working group results are shown in this paper. The modern software defined radio is the heart of a cognitive radio. The applications executing on the radio distinguish a cognitive radio from a software-defined radio. Additional hardware in the form of sensors and actuators enables more cognitive radio applications. Some of the enabling technology is presented in this paper. Various artificial intelligence approaches to machine learning and decision making may be applied to the cognitive radio system. In this paper, a survey of related cognitive radio topics is reviewed and candidate application architectures are presented. Section 1 is an introduction to the basis of cognitive radios from a hardware, software, and artificial intelligence point of view. Section 2 discusses the sensors and actuators needed by a cognitive radio. Section 3 presents software architectures for radio learning and ultimately cognition. Section 4 is the heart of the paper and describes three candidate cognitive radio applications. Some future trends and conclusions are presented in Section 5. 1. COGNITIVE RADIO ENABLING TECHNOLOGY

Beyond 3G radio access network reference architecture

Abstract: Today a multitude of radio access technologies exist and are continuously evolved to support higher bit rates, lower delays, lower cost, etc. In addition, new radio access technologies are developed to complement those of today. When using services in this environment with multiple radio access technologies, end users expect mobility between the different radio access technologies to be seamless. Network operators, in addition, look for efficient resource usage of different radio access technologies and more cost efficient ways to deploy networks. This requires increased flexibility in the radio access network architecture compared with today's architectures. In this paper a beyond 3G radio access network reference architecture supporting these requirements is presented. The architecture allows for various implementations and considers new deployment concepts such as multi-hop radio networks, moving networks and personal area networks.

Cognitive trends in making: future of networks

Abstract: We are arguing that some new interesting trends in making are emerging. We try to identify some aspects that could provide hard problems with potentially high payout for the future research. We also show how some of the topics are shared between both wireless and fixed network domain. We propose as a hypothesis that the key issue in the future is to understand and lower the increasing complexity (increasing abstraction) of communications systems. There are several different ways towards this goal.

Self-organization and new hierarchies in complex evolutionary value networks

Abstract: This chapter, with a broad theory building goal, addresses these two questions: "how the new network-based forms of coordination emerge, and how can they change the management of value exchange dynamics on complex cognitive networks?" We can find a useful answer by using an interdisciplinary approach. New institutions do not form through costless trust and order-for-free self-organization (the invisible hand of the market), but are managed as complex evolutionary value networks. This conceptual framework can help managers to design more cooperative structures and nodes to negotiate network structure and power. The design of the network matters. The network is the locus of learning but also the locus of social negotiation. The new institutions can be designed, even if this design looks more like a monitorial learning process and a design of the infomediation infrastructure than the well structured plans of old-fashioned management. The new network governance forms, and the logics that wants to build organizations as flexible and loosely-coupled systems of self-organized peripheries, also require that we build a new "ethics of network management" agenda.

GPRS network simulation model in NS-2

Abstract: The objective of the general packet radio service (GPRS) network simulation is to obtain accurate enough implementation of GPRS network in Network Simulation 2 (NS-2), so that IP optimization features can be tested. In this paper, we try to afford such a model The simulation model concentrates on the Um Interface, Gb Interface, Gn Interface and Gi Interface respectively. Each part is represented as node, agent, queue or link in NS-2. At last, a simple analysis of one scenario is given to demonstrate how to use this model.

Effects of network topology and routing on traffic in packet-switching network model

Abstract: We investigate how the network performance indicators "number of packets in transit" and "average packet delay" are affected by network connection topologies and routing in a packet-switching network model. For the purpose of our study we have developed an abstraction of the OSI Network Layer of the OSI reference model for which we derived a time-discrete algorithmic simulation model. Using this model we investigate how number of packets in transit and average packet delay are affected by routing algorithms and addition of extra links into the underlying network connection topology. We consider various levels of preferentiality of attachment of the additional links.

Adding reasoning and cognition to the internet

Abstract: Present computer networks are laid over a set of dummy "boxes" performing specialised tasks, following an outdated model that provides a "best-effort" type of service. Current application needs have pushed research towards the so-called "active networking", which aims to enable programmability/adaptability of the network fabric according to varying user requirements. This paper takes one step further and discusses a new topic for network research, which promotes the interplay between active network technology and artificial intelligence. It introduces a context of reasoning and cognition in the network fabric, based on reinforcement learning and other AI strategies that will allow training of the infrastructure with past experiences/history of events and user preferences. We analyse the requirements of this class of networks and identify basic building blocks of a potential architecture. The outcome of this research envisions dependable, resilient, self-manageable, selfconfigurable and survivable networks or what we call herein "cognitive networks".

Prototype of context-based adaptive communication system on seamless networking platform

Abstract: A context-based adaptive communication system is introduced for use in heterogeneous networks. The context includes the user's presence, location, available network interfaces, network availability, network priority, communication status, terminal features, and installed applications. An experimental system was developed to clarify the feasibility of using context information to flexibly control a network and applications. The system operates on a seamless networking platform we developed for heterogeneous networks. By using contexts, the system can show the caller and its callee the applications they can access that are available through the network before communication occurs. Changes of the contexts can switch the on-going application to another during communication. These features provide us with unprecedented styles of communications.

Cognitive Routing in Packet Networks

Abstract: While the Internet has beome a resounding success for human communication and information gathering and dissemination, Quality of Service (QoS) remains a major subject of concern for users of packet networks In this paper we show how distributed intelligence and on-line adaptation can be used to enhance QoS for users of packet networks, and present our Cognitive Packet Network approach as a manner to address this important issue Our presentation is based on ongoing experimental reserach that uses several “Cognitive Packet Network” (CPN) test-beds that we have developed