Multi-installment load distribution in tree networks with delays

This paper presents a new strategy for load distribution in a single-level tree network equipped with or without front-ends. The load is distributed in more than one installment in an optimal manner to minimize the processing time. This is a deviation and an improvement over earlier studies in which the load distribution is done in only one installment. Recursive equations for the general case, and their closed form solutions for a special case in which the network has identical processors and identical links, are derived. An asymptotic analysis of the network performance with respect to the number of processors and the number of installments is carried out. Discussions of the results in terms of some practical issues like the tradeoff relationship between the number of processors and the number of installments are also presented.

Mobile node authentication using key distribution scheme in wireless sensor networks

We consider the problem of secure communication in mobile Wireless Sensor Networks (WSNs). Achieving security in WSNs requires robust encryption and authentication standards among the sensor nodes. Severe resources constraints in typical Wireless Sensor nodes hinder them in achieving key agreements. It is proved from past studies that many notable key management schemes do not work well in sensor networks due to their limited capacities. The idea of key predistribution is not feasible considering the fact that the network could scale to millions. We prove a novel algorithm that provides robust and secure communication channel in WSNs. Our Double Encryption with Validation Time (DEV) using Key Management Protocol algorithm works on the basis of timed sessions within which a secure secret key remains valid. A mobile node is used to bootstrap and exchange secure keys among communicating pairs of nodes. Analysis and simulation results show that the performance of the DEV using Key Management Protocol Algorithm is better than the SEV scheme and other related work.

An Efficient Load Distribution Strategy for a Distributed Linear Network of Processors with Communication Delays

In this paper, we present an improved load distribution strategy, for arbitrarily divisible processing loads, to minimize the processing time in a distributed linear network of communicating processors by an efficient utilization of their front-ends. Closed-form solutions are derived, with the processing load originating at the boundary and at the interior of the network, under some important conditions on the arrangement of processors and links in the network. Asymptotic analysis is carried out to explore the ultimate performance limits of such networks. Two important theorems are stated regarding the optimal load sequence and the optimal load origination point. Comparative study of this new strategy with an earlier strategy is also presented.

Self-Assembly of Bile Steroid Analogues: Molecules, Fibers, and Networks

Structural and rheological features of a series of molecular hydrogels formed by synthetic bile salt analogues have been scrutinized. Among seven gelators, two are neutral compounds, while the others are cationic systems among which one is a tripodal steroid derivative. Despite the fact that the chemical structures are closely related, the variety of physical characteristics is extremely large in the structures of the connected fibers (either plain cylinders or ribbons), in the dynamical modes for stress relaxation of the associated SAFINs, in the scaling laws of the shear elasticity (typical of either cellular solids or fractal floc-like assemblies), in the micron-scale texture and the distribution of ordered domains (spherulites, crystallites) embedded in a random mesh, in the type of nodal zones (either crystalline-like, fiber entanglements, or bundles), in the evolution of the distribution and morphology of fibers and nodes, and in the sensitivity to added salt. SANS appears to be a suitable technique to infer all geometrical parameters defining the fibers, their interaction modes, and the volume fraction of nodes in a SAFIN. The tripodal system is particularly singular in the series and exhibits viscosity overshoots at the startup of shear flows, an “umbrella-like” molecular packing mode involving three molecules per cross section of fiber, and scattering correlation peaks revealing the ordering and overlap of 1d self-assembled polyelectrolyte species.

A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time

The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

Comparison of ANN models for predicting water quality in distribution systems

Deterministic models have been widely used to predict water quality in distribution systems, but their calibration requires extensive and accurate data sets for numerous parameters. In this study, alternative data-driven modeling approaches based on artificial neural networks (ANNs) were used to predict temporal variations of two important characteristics of water quality chlorine residual and biomass concentrations. The authors considered three types of ANN algorithms. Of these, the Levenberg-Marquardt algorithm provided the best results in predicting residual chlorine and biomass with error-free and ``noisy'' data. The ANN models developed here can generate water quality scenarios of piped systems in real time to help utilities determine weak points of low chlorine residual and high biomass concentration and select optimum remedial strategies.

Voltage and Temperature Aware Statistical Leakage Analysis Framework Using Artificial Neural Networks

Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process parameters, supply voltage and temperature can be modeled accurately with ANNs. However, the complex nature of the ANN model, with the standard sigmoidal activation functions, does not allow analytical expressions for its mean and variance. We propose the use of a new activation function that allows us to derive an analytical expression for the mean and a semi-analytical expression for the variance of the ANN-based leakage model. To the best of our knowledge this is the first result in this direction. Our neural network model also includes the voltage and temperature as input parameters, thereby enabling voltage and temperature aware statistical leakage analysis (SLA). All existing SLA frameworks are closely tied to the exponential polynomial leakage model and hence fail to work with sophisticated ANN models. In this paper, we also set up an SLA framework that can efficiently work with these ANN models. Results show that the cumulative distribution function of leakage current of ISCAS'85 circuits can be predicted accurately with the error in mean and standard deviation, compared to Monte Carlo-based simulations, being less than 1% and 2% respectively across a range of voltage and temperature values.

Design of logical topologies for wavelength-routed optical networks

his paper studies the problem of designing a logical topology over a wavelength-routed all-optical network (AON) physical topology, The physical topology consists of the nodes and fiber links in the network, On an AON physical topology, we can set up lightpaths between pairs of nodes, where a lightpath represents a direct optical connection without any intermediate electronics, The set of lightpaths along with the nodes constitutes the logical topology, For a given network physical topology and traffic pattern (relative traffic distribution among the source-destination pairs), our objective is to design the logical topology and the routing algorithm on that topology so as to minimize the network congestion while constraining the average delay seen by a source-destination pair and the amount of processing required at the nodes (degree of the logical topology), We will see that ignoring the delay constraints can result in fairly convoluted logical topologies with very long delays, On the other hand, in all our examples, imposing it results in a minimal increase in congestion, While the number of wavelengths required to imbed the resulting logical topology on the physical all optical topology is also a constraint in general, we find that in many cases of interest this number can be quite small, We formulate the combined logical topology design and routing problem described above (ignoring the constraint on the number of available wavelengths) as a mixed integer linear programming problem which we then solve for a number of cases of a six-node network, Since this programming problem is computationally intractable for larger networks, we split it into two subproblems: logical topology design, which is computationally hard and will probably require heuristic algorithms, and routing, which can be solved by a linear program, We then compare the performance of several heuristic topology design algorithms (that do take wavelength assignment constraints into account) against that of randomly generated topologies, as well as lower bounds derived in the paper.

Throughput performance of distributed applications in switched networks in presence of end-system bottlenecks

The steady state throughput performance of distributed applications deployed in switched networks in presence of end-system bottlenecks is studied in this paper. The effect of various limitations at an end-system is modelled as an equivalent transmission capacity limitation. A class of distributed applications is characterised by a static traffic distribution matrix that determines the communication between various components of the application. It is found that uniqueness of steady state throughputs depends only on the traffic distribution matrix and that some applications (e.g., broadcast applications) can yield non-unique values for the steady state component throughputs. For a given switch capacity, with traffic distribution that yield fair unique throughputs, the trade-off between the end-system capacity and the number of application components is brought out. With a proposed distributed rate control, it has been illustrated that it is possible to have unique solution for certain traffic distributions which is otherwise impossible. Also, by proper selection of rate control parameters, various throughput performance objectives can be realised.

An Efficient Scheme for Establishing Pairwise Keys for Wireless Sensor Networks

This paper addresses the problem of secure path key establishment in wireless sensor networks that uses the random key pre-distribution technique. Inspired by the recent proxy-based scheme in the work of Ling and Znati (2005) and Li et al. (2005), we introduce a friend-based scheme for establishing pairwise keys securely. We show that the chances of finding friends in a neighbourhood are considerably more than that of finding proxies, leading to lower communication overhead. Further, we prove that the friend-based scheme performs better than the proxy-based scheme both in terms of resilience against node capture as well as in energy consumption for pairwise key establishment, making our scheme more feasible.

Optimizing Delay in Sequential Change Detection on Ad Hoc Wireless Sensor Networks

We consider the classical problem of sequential detection of change in a distribution (from hypothesis 0 to hypothesis 1), where the fusion centre receives vectors of periodic measurements, with the measurements being i.i.d. over time and across the vector components, under each of the two hypotheses. In our problem, the sensor devices ("motes") that generate the measurements constitute an ad hoc wireless network. The motes contend using a random access protocol (such as CSMA/CA) to transmit their measurement packets to the fusion centre. The fusion centre waits for vectors of measurements to accumulate before taking decisions. We formulate the optimal detection problem, taking into account the network delay experienced by the vectors of measurements, and find that, under periodic sampling, the detection delay decouples into network delay and decision delay. We obtain a lower bound on the network delay, and propose a censoring scheme, where lagging sensors drop their delayed observations in order to mitigate network delay. We show that this scheme can achieve the lower bound. This approach is explored via simulation. We also use numerical evaluation and simulation to study issues such as: the optimal sampling rate for a given number of sensors, and the optimal number of sensors for a given measurement rate

Evolving Random Geometric Graph Models for Mobile Wireless Networks

We consider evolving exponential RGGs in one dimension and characterize the time dependent behavior of some of their topological properties. We consider two evolution models and study one of them detail while providing a summary of the results for the other. In the first model, the inter-nodal gaps evolve according to an exponential AR(1) process that makes the stationary distribution of the node locations exponential. For this model we obtain the one-step conditional connectivity probabilities and extend it to the k-step case. Finite and asymptotic analysis are given. We then obtain the k-step connectivity probability conditioned on the network being disconnected. We also derive the pmf of the first passage time for a connected network to become disconnected. We then describe a random birth-death model where at each instant, the node locations evolve according to an AR(1) process. In addition, a random node is allowed to die while giving birth to a node at another location. We derive properties similar to those above.

Efficient Key Management and Distribution for MANET

Ad hoc networks are being used in applications ranging from disaster recovery to distributed collaborative entertainment applications. Ad hoc networks have become one of the most attractive solution for rapid deployment of interconnecting large number of mobile personal devices. The user community of mobile personal devices are demanding a variety of value added multimedia entertainment services. The popularity of peer group is increasing and one or some members of the peer group need to send data to some or all members of the peer group. The increasing demand for group oriented value added services is driving for efficient multicast service over ad hoc networks. Access control mechanisms need to be deployed to provide guarantee that the unauthorized users cannot access the multicast content. In this paper, we present a topology aware key management and distribution scheme for secure overlay multicast over MANET to address node mobility related issues for multicast key management. We use overlay approach for key distribution and our objective is to keep communication overhead low for key management and distribution. We also incorporate reliability using explicit acknowledgments with the key distribution scheme. Through simulations we show that the proposed key management scheme has low communication overhead for rekeying and improves the reliability of key distribution.

Relay Precoder Optimization in MIMO-Relay Networks With Imperfect CSI

In this paper, we consider robust joint designs of relay precoder and destination receive filters in a nonregenerative multiple-input multiple-output (MIMO) relay network. The network consists of multiple source-destination node pairs assisted by a MIMO-relay node. The channel state information (CSI) available at the relay node is assumed to be imperfect. We consider robust designs for two models of CSI error. The first model is a stochastic error (SE) model, where the probability distribution of the CSI error is Gaussian. This model is applicable when the imperfect CSI is mainly due to errors in channel estimation. For this model, we propose robust minimum sum mean square error (SMSE), MSE-balancing, and relay transmit power minimizing precoder designs. The next model for the CSI error is a norm-bounded error (NBE) model, where the CSI error can be specified by an uncertainty set. This model is applicable when the CSI error is dominated by quantization errors. In this case, we adopt a worst-case design approach. For this model, we propose a robust precoder design that minimizes total relay transmit power under constraints on MSEs at the destination nodes. We show that the proposed robust design problems can be reformulated as convex optimization problems that can be solved efficiently using interior-point methods. We demonstrate the robust performance of the proposed design through simulations.

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.