A generalized network alignment for three-source three-destination multiple unicast networks with delays

The concept of interference alignment when extended to three-source three-destination instantaneous multiple unicast network for the case where, each source-destination pair has a min-cut of 1 and zero-interference conditions are not satisfied, is known to achieve a rate of half for every source-destination pair under certain conditions [6]. This was called network alignment. We generalize this concept of network alignment to three-source three-destination multiple unicast (3S-3D-MU) networks with delays, without making use of memory at the intermediate nodes (i.e., nodes other than the sources and destinations) and using time varying Local Encoding Kernels (LEKs). This achieves half the rate corresponding to the individual source-destination min-cut for some classes of 3S-3D-MU network with delays which do not satisfy the zero-interference conditions.

Queuing Network Models for Aircraft Availability and Spares Management

Interactions of major activities involved in airfleet operations, maintenance, and logistics are investigated in the framework of closed queuing networks with finite number of customers. The system is viewed at three levels, namely: operations at the flying-base, maintenance at the repair-depot, and logistics for subsystems and their interactions in achieving the system objectives. Several performance measures (eg, availability of aircraft at the flying-base, mean number of aircraft on ground at different stages of repair, use of repair facilities, and mean time an aircraft spends in various stages of repair) can easily be computed in this framework. At the subsystem level the quantities of interest are the unavailability (probability of stockout) of a spare and the duration of its unavailability. The repair-depot capability is affected by the unavailability of a spare which in turn, adversely affects the availability of aircraft at the flying-base level. Examples illustrate the utility of the proposed models.

Modified McMurray Inverter with Pulse Forming Network Commutation Circuits

The modified McMurray Inverter with Pulse Forming Network (PFN) has been explained. The current and voltage waveshapes of the PFN commutation ci rcuit have been compared with conventional L-commutation circuit. The design method of PFN has been explained. Advantages of this type of commutation have been discussed. Experimental results are given.

Wireless sensor networks forhuman intruder detection

In this paper we report on the outcomes of a research and demonstration project on human intrusion detection in a large secure space using an ad hoc wireless sensor network. This project has been a unique experience in collaborative research, involving ten investigators (with expertise in areas such as sensors, circuits, computer systems,communication and networking, signal processing and security) to execute a large funded project that spanned three to four years. In this paper we report on the specific engineering solution that was developed: the various architectural choices and the associated specific designs. In addition to developing a demonstrable system, the various problems that arose have given rise to a large amount of basic research in areas such as geographical packet routing, distributed statistical detection, sensors and associated circuits, a low power adaptive micro-radio, and power optimising embedded systems software. We provide an overview of the research results obtained.

Performance modeling and architecture exploration of network processors

This paper proposes a Petri net model for a commercial network processor (Intel iXP architecture) which is a multithreaded multiprocessor architecture. We consider and model three different applications viz., IPv4 forwarding, network address translation, and IP security running on IXP 2400/2850. A salient feature of the Petri net model is its ability to model the application, architecture and their interaction in great detail. The model is validated using the Intel proprietary tool (SDK 3.51 for IXP architecture) over a range of configurations. We conduct a detailed performance evaluation, identify the bottleneck resource, and propose a few architectural extensions and evaluate them in detail.

Network pricing for QoS: A 'Regulation' approach

V. S. Borkar’s work was supported in part by grant number III.5(157)/99-ET from the Department of Science and Technology, Government of India. D. Manjunath’s work was supported in part by grant number 1(1)/2004-E-Infra from the Ministry of Information Technology, Government of India.

A Scalable Architecture for VoIP Conferencing

Real-Time services are traditionally supported on circuit switched network. However, there is a need to port these services on packet switched network. Architecture for audio conferencing application over the Internet in the light of ITU-T H.323 recommendations is considered. In a conference, considering packets only from a set of selected clients can reduce speech quality degradation because mixing packets from all clients can lead to lack of speech clarity. A distributed algorithm and architecture for selecting clients for mixing is suggested here based on a new quantifier of the voice activity called “Loudness Number” (LN). The proposed system distributes the computation load and reduces the load on client terminals. The highlights of this architecture are scalability, bandwidth saving and speech quality enhancement. Client selection for playing out tries to mimic a physical conference where the most vocal participants attract more attention. The contributions of the paper are expected to aid H.323 recommendations implementations for Multipoint Processors (MP). A working prototype based on the proposed architecture is already functional.

Traffic Profiling for Efficient Network Resource Utilization.

Traffic Engineering has been the prime concern for Internet Service Providers (ISPs), with the main focus being minimization of over-utilization of network capacity even though additional capacity is available which is under-utilized, Furthermore, requirements of timely delivery of digitized audiovisual information raises a new challenge of finding a path meeting these requirements. This paper addresses the issue of (a) distributing load to achieve global efficiency in resource utilization. (b) Finding a path satisfying the real time requirements of, delay and bandwidth requested by the applications. In this paper we do a critical study of the link utilization that varies over time and determine the time interval during which the link occupancy remains constant across days. This information helps in pre-determining link utilization that is useful in balancing load in the network Finally, we run simulations that use a dynamic time interval for profiling traffic and show improvement in terms number of calls admitted/blocked.

An instantaneous control model for flow control in an ATM network

This paper is concerned with the optimal flow control of an ATM switching element in a broadband-integrated services digital network. We model the switching element as a stochastic fluid flow system with a finite buffer, a constant output rate server, and a Gaussian process to characterize the input, which is a heterogeneous set of traffic sources. The fluid level should be maintained between two levels namely b1 and b2 with b1network is considered

Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

Network Reconstruction from dynamic data

Over the past decade, many powerful data mining techniques have been developed to analyze temporal and sequential data. The time is now fertile for addressing problems of larger scope under the purview of temporal data mining. The fourth SIGKDD workshop on temporal data mining focused on the question: What can we infer about the structure of a complex dynamical system from observed temporal data? The goals of the workshop were to critically evaluate the need in this area by bringing together leading researchers from industry and academia, and to identify promising technologies and methodologies for doing the same. We provide a brief summary of the workshop proceedings and ideas arising out of the discussions.

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

Neural network based power system damping controller for SVC

The development of a neural network based power system damping controller (PSDC) for a static Var compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system.