ATM cell scheduling by function level evolvable hardware

The possibility of using Evolvable Hardware (EHW) for scheduling real-time traffic in Asynchronous Transfer Mode (ATM) networks have studied in this paper. EHW is hardware built on programmable logic devices and whose architecture can be reconfigured by using genetic learning to adapt to new environments. A novel design is the function-level EHW based on Field programmable Gate Array (FPGA) chips. A number of Programmable Floating Processing Units (PFUs) are embedded in on chip. The selectable high-level hardware functions of each PFU make the function-level PFU make the function-level EHW to be suitable for a wide variety of applications in practice.

With networks increasingly moving into virtually every aspect of our daily life, security is gaining importance, not only from the traditional perspective of communication but the network's growing role in modern automation and control. The traditional, certification based approach attempts to guarantee the security of a network through certification. Certified networks are generally confined to a limited domain and, as a result, they are isolated, costly, and under-utilized. In contrast, this paper presents a new principle – user-level, security-on-demand system, wherein the network allocates, where possible, the security resources commensurate with the user's request for transporting message(s) through the network securely. This principle is successfully demonstrated for the current Asynchronous Transfer Mode (ATM) networks, and is the result of an integration of the fundamental framework for network security, recently proposed by the authors in the literature, with the unique characteristics of ATM networks. The framework encapsulates the fundamental knowledge and set of relationships in network security and permits scientific and systematic reasoning about network security. It also enables all user groups – military, government, industry, and academia, to define their security requirements in a uniform manner. The security-on-demand approach promises the development of a "mixed use" class of networks in the future that may be simultaneously shared by different groups of users, with the system sustaining the diverse security requirements of each user. A unique characteristic in ATM network design is the dynamic call setup process. Under it, a network first establishes a virtual path or route for a user's call, guided by the user's requirements, and then transports the messages when a route has been successfully determined. This unique ATM characteristic is integrated with the framework to yield a successful demonstration of the proposed, user-level, security-on-demand approach. Utilizing the security framework as the foundation, every element of the network – node and link, is characterized by a security matrix that reflects its security resources. Every user is permitted to specify the security requirement for the call through a matrix, which expresses the limits of the security resources that the traffic cells must encounter during their transport through the network. Thus, during the dynamic establishment of the virtual path, every node and link is examined to ensure that the user-specified security is met, in addition to bandwidth and other Quality of Service (QoS) requirements. Traffic is launched when the call setup succeeds, otherwise, the call fails. Like all networks, the ATM network inherently consists of geographically dispersed entities and, as a result, the resource allocation strategy is necessarily distributed. Furthermore, as the network operation progresses, the resource availability scene changes dynamically. This paper proposes a unique function that reduces the key network resource parameters at a node to a single value, termed Node Status Indicator (NSI). The NSI value is computed dynamically at every node and disseminated across the network to be utilized by a node to refine its determination of a virtual path for a user call. The aim of the NSI is to improve the resource utilization in the network. The proposed approach is modeled for a large-scale, representative, 40-node ATM network. Utilizing stochastic input traffic that is synthesized to reflect realistic operating conditions, the model is simulated extensively on a testbed of 35+ Pentium workstations, under Linux, configured as a loosely-coupled parallel processor, utilizing an accurate, asynchronous, distributed simulator. The simulator implements the key characteristics of the ATM Forum proposed P-NNI 1.0 and UNI 3.0 standards. While the simulation results reflect a successful realization of the proposed approach, analysis reveals minimal impact of incorporating security on ATM network performance, as measured through call success rates and call setup times. In contrast, the tradition has been to incorporate security into large-scale systems and networks as an afterthought, i.e. adding hardware and software devices after the design has been completed, resulting in performance degradation. Also, while the use of NSI is observed to yield slightly lower average call setup rates and slightly higher average call setup times, a careful analysis of the trace of the calls as they progress through the system, reveals that, in general, calls are dispersed throughout the network, seeking to utilize all available resources of the network more evenly.

An asynchronous transfer mode (ATM) network is a high-speed multimedia network which handles various kinds of traffic with different bit-rates and different qualities of service (QoS). In order to maintain the QoS for each traffic source and to avoid possible congestion problems, an ATM network requires highly sophisticated and flexible controllers to insure that this demanding performance can be achieved under unexpected changes in traffic conditions. In this paper, we propose an intelligent architecture using recurrent neural networks and an expert system for traffic control in ATM networks. This traffic control using neural networks is suitable for ATM because neural networks can learn the traffic characteristics and the dynamic changes in the traffic. The proposed mechanism is based on the adaptive prediction of the future values of the traffic and the flow rate for each traffic source. At every given time slot, the controllers in the proposed architecture predict whether the congestion will happen or not and regulate the volume of input traffic for each traffic source before the congestion happens, maintaining the user-required QoS for each traffic source based on the predefined rules. Consequently, the mechanism guarantees the QoS for each traffic source and efficiently prevents congestion.

This paper considers the influence of switch fabric design on the performance of resource allocation and connection admission algorithms for asynchronous transfer mode (ATM) networks. In particular, the goal of predictable and guaranteed quality of service (QoS) can be achieved within an ATM network by considering the above factors in the design of the ATM switch fabric. The paper focuses on the identification of the functional requirements of the switch fabric at the ATM layer, and develops an improved architecture which considers QoS at the switch fabric, along with an interface to the resource management. The resultant switch results in ATM networks which have reliable and predictable parameters and which have reduced complexity in connection admission control.

This paper presents a systems view of video transport issues in asynchronous transfer mode (ATM) networks. Since video is a critical component of future distributed multimedia applications, we consider technical approaches necessary to realize a flexible, robust, and efficient ATM framework for video delivery. The overall system-design problem is discussed for a general distributed multimedia computing scenario, and key video-related design issues are identified. This is followed by a more detailed discussion of selected ATM video topics, including: (1) variable bit-rate (VBR) statistical multiplexing and dynamic usage parameter control (VBR+), (2) ATM cell-loss concealment in MPEG decoders, and (3) new transport protocols (“MTP”) for video and multimedia. Supporting simulation or experimental results from ongoing research are given where available.

We propose a congestion control algorithm and design a state feedback controller for regulating the congestion of available bit rate (ABR) traffic in asynchronous transfer mode (ATM) networks. ABR service is specified as the rate-based feedback mechanism for congestion control and provides a control signal to throttled sources from a bottleneck node in order to adjust the throttled source rates based on available capacity. Our main purposes are as follows: (1) to design a state feedback controller; (2) to place the closed-loop poles in any desired regions based on a pole placement constraint; (3) to use the LMI (linear matrix inequalities) approach for finding the optimal state feedback gain K. The simulation results show that, under pole placement and LMI approaches, our state feedback congestion controller for ABR traffic in ATM networks can possibly guarantee the system stability, provide no buffer overflow, determine the optimal source traffic rates and place the closed-loop poles in any desired regions as well.

The Communications Research Laboratory (CRL), Tokyo, Japan, and the Telecommunication Network Laboratory Group, Nippon Telegraph and Telephone Corp., Tokyo, Japan, have developed a highly precise, very long baseline interferometry (VLBI) system using a high speed asynchronous transfer mode (ATM) network. The observed data is transmitted through a 2.488-Gbps ATM network [STM-16/OC-48] instead of being recorded onto magnetic tape. The system was specially designed for the Key Stone Project (KSP), a project begun in 1994 to measure crustal deformation in the Tokyo metropolitan area. Cross-correlation processing and data observations are carried out simultaneously by one operator. It takes about one hour to analyze the data after the observations and correlations are completed. In regular geodetic VLBI experiments run every other day for 24 h, a horizontal position uncertainty of about 2 mm and a vertical position uncertainty of about 10 mm were achieved. The system was designed to enable automated operation throughout the entire process. The results obtained are available to the public via the Internet at http:ksp.crl.go.jp. This system is a significant advance in VLBI and should provide more precise information about crustal deformation in the Tokyo metropolitan area.

This paper presents a method for the design of a self-tuning transmission rate manger to improve the performance of a fuzzy traffic controller that simultaneously manages congestion control and connection admission control for asynchronous transfer mode (ATM) network. An ATM network requires a sophisticated, real-time traffic controller that manages connection admission control and congestion control, to guarantee the quality of service (QoS) for existing calls and to achieve high system utilization. This self-tuning transmission rate manager adjusts source rates of data traffic yielding high system utilization and low cell loss rate. Simulation results show the total system utilization improves from 69% to 99% and cell loss probability (ratio) reduces from 2.9e-3 to 3.0e-8.

While the transmission control protocol (TCP) generally provides robust performance across many network environments, several researchers have identified the poor end-to-end performance achieved by TCP on asynchronous transfer mode (ATM) networks. The performance problems arise for several reasons: (1) a size mismatch between TCP segments and ATM cells; (2) the simple protocols used for segmentation and reassembly in ATM, and for retransmission in TCP; (3) specific optimizations in TCP, made primarily for low-bandwidth Internet environments which do not work well in high speed ATM networks; (4) features (or misfeatures) in most TCP protocol implementations; and (5) subtle interactions between all of these factors. This paper describes a simulation model that we have constructed to study TCP performance on ATM networks, as well as a set of simulation experiments conducted using the model. The TCP model is detailed enough to recreate many of the performance problems identified by other researchers, as well as to evaluate potential solutions to the performance problems. The TCP model adds to the traffic modeling toolkit available in our existing ATM network simulator, and enables the further study of performance issues in TCP over ATM.

The purpose of this paper is to study quality of service (QoS) management and performance monitoring issues in B-ISDN. A QoS framework is proposed in order to satisfy the user's service quality requirements. The basic idea of this QoS framework is that the user's QoS requirement should be represented in terms of objectives set to QoS parameters which are in turn translated into asynchronous transfer mode (ATM) network performance (NP) parameters objectives; then, meeting NP parameters objectives ensures that the user's QoS requirements are fulfilled. Performance monitoring mechanisms based on operation and maintenance (OAM) cells flows in the ATM layer and estimation methods, which are both part of a QoS framework, are reviewed. We focus in particular on the definition and estimation of NP parameters in the case of non-conforming cells transmitted on an ATM connection. Finally, a QoS management scenario for the ATM layer is proposed. >

Design and performance analysis of a new RTM algorithm for VBR traffic in ATM networks

The authors address some issues associated with the use of traffic-violation-tagging in ATM (asynchronous transfer mode) networks. The compatibility of tagging with AAL (ATM adaptation layer) cell loss priority marking is discussed. Selective-discarding algorithm behavior is shown to be sensitive to tagged-traffic load, which implies a conservative strategy for the specification of these algorithms. It is pointed out that the QOS (quality of service) offered to tagged traffic cannot be specified. >

For the congestion problems in asynchronous transfer mode (ATM) networks, a hybrid intelligent controller based on simulated annealing (SA) and reinforcement learning (RL) algorithm is proposed. The SA algorithm is a powerful way to solve hard combinatorial optimization problems, which is used to adjust the parameters of the controller. The RL algorithm shows the particular superiority in ATM networks, which is independent of the mathematic model and just needs simple fuzzy information obtained through trial-and-error and interaction with the environment. With the advantages of the two algorithms, the proposed controller forces the queue size in the multiplexer buffer to the desired value by adjusting the source transmission rate of the available bit rate (ABR) service. Simulation results show that the proposed method can promote the performance of the networks and avoid the occurrence of congestion effectively.

Prediction plays a key role in almost all walks of life. Therefore, a new prediction-based method, known as Kalman congestion avoidance (KACA) scheme is presented for traffic and congestion management in asynchronous transfer mode (ATM) networks. Also, an effort has been made to compare two different congestion avoidance schemes for ATM networks with the KACA scheme, such as Ohio State University (OSU) scheme and dynamic-congestion avoidance using proportional control (D-CAPC) scheme. It begins by describing the description briefly of each of these schemes. Based on the discussions, we summarize the properties for each of these schemes.

This paper considers the problem of process allocation in designing real-time call setup for asynchronous transfer mode (ATM) networks. With the constraint of finite processing capacity in a realistic ATM switching system, we aim to minimize the call setup delay by avoiding the potential bottleneck process. Our approach is to distribute and balance the processing loads among call control processes via optimal capacity allocation. The derived results can provide important and useful guidelines in system design and performance evaluation.