A matroidal framework for network-error correcting codes

Matroidal networks were introduced by Dougherty et al. and have been well studied in the recent past. It was shown that a network has a scalar linear network coding solution if and only if it is matroidal associated with a representable matroid. The current work attempts to establish a connection between matroid theory and network-error correcting codes. In a similar vein to the theory connecting matroids and network coding, we abstract the essential aspects of network-error correcting codes to arrive at the definition of a matroidal error correcting network. An acyclic network (with arbitrary sink demands) is then shown to possess a scalar linear error correcting network code if and only if it is a matroidal error correcting network associated with a representable matroid. Therefore, constructing such network-error correcting codes implies the construction of certain representable matroids that satisfy some special conditions, and vice versa.

Greening the IP Over Optical Backbone Network

In this paper we examine the energy consumption of IP Over Optical WDM Networks. As the number of Internet users increases the Internet expands in reach and capacity. This results in increased energy consumption of the network. Minimizing the power consumption, termed as ``Greening the Internet'', is desirable to help service providers (SP) operate their networks and provide services more efficiently in terms of power consumption. Minimizing the operational power typically depends on the strategy (e. g., lightpath bypass, lightpath non-bypass and traffic grooming) and operations (e. g., electronic domain versus optical domain). We consider a typical optical backbone network model, and develop a model which minimizes the power consumption. Performance calculation shows that our method consumes less power compared to traffic grooming approach.

An asymptotically optimal push-pull method for multicasting over a random network

We consider multicast flow problems where either all of the nodes or only a subset of the nodes may be in session. Traffic from each node in the session has to be sent to every other node in the session. If the session does not consist of all the nodes, the remaining nodes act as relays. The nodes are connected by undirected edges whose capacities are independent and identically distributed random variables. We study the asymptotics of the capacity region (with network coding) in the limit of a large number of nodes, and show that the normalized sum rate converges to a constant almost surely. We then provide a decentralized push-pull algorithm that asymptotically achieves this normalized sum rate.

Optimal capacity relay node placement in a multi-hop network on a line

We use information theoretic achievable rate formulas for the multi-relay channel to study the problem of optimal placement of relay nodes along the straight line joining a source node and a destination node. The achievable rate formulas that we utilize are for full-duplex radios at the relays and decode-and-forward relaying. For the single relay case, and individual power constraints at the source node and the relay node, we provide explicit formulas for the optimal relay location and the optimal power allocation to the source-relay channel, for the exponential and the power-law path-loss channel models. For the multiple relay case, we consider exponential path-loss and a total power constraint over the source and the relays, and derive an optimization problem, the solution of which provides the optimal relay locations. Numerical results suggest that at low attenuation the relays are mostly clustered close to the source in order to be able to cooperate among themselves, whereas at high attenuation they are uniformly placed and work as repeaters. We also prove that a constant rate independent of the attenuation in the network can be achieved by placing a large enough number of relay nodes uniformly between the source and the destination, under the exponential path-loss model with total power constraint.

Channel quantization for physical layer network-coded two-way relaying

The design of modulation schemes for the physical layer network-coded two way relaying scenario is considered with the protocol which employs two phases: Multiple access (MA) Phase and Broadcast (BC) phase. It was observed by Koike-Akino et al. that adaptively changing the network coding map used at the relay according to the channel conditions greatly reduces the impact of multiple access interference which occurs at the relay during the MA phase. In other words, the set of all possible channel realizations (the complex plane) is quantized into a finite number of regions, with a specific network coding map giving the best performance in a particular region. We obtain such a quantization analytically for the case when M-PSK (for M any power of 2) is the signal set used during the MA phase. We show that the complex plane can be classified into two regions: a region in which any network coding map which satisfies the so called exclusive law gives the same best performance and a region in which the choice of the network coding map affects the performance, which is further quantized based on the choice of the network coding map which optimizes the performance. The quantization thus obtained analytically, leads to the same as the one obtained using computer search for 4-PSK signal set by Koike-Akino et al., for the specific value of M = 4.

A systematic investigation of fracture mechanisms in Al-Si based eutectic alloy-Effect of Si modification

The fracture characteristics of Al-Si based eutectic alloy are investigated in the unmodified and modified conditions under compression. The investigations are carried out at different strain rates and temperatures. Fracture of the alloy starts with eutectic Si particle fracture and modification plays an important role in particle fracture. The fraction of fractured particles is found to be always lesser in the modified condition than in the unmodified condition. Particle fracture increases with increase in strain. It is found that the Si particle fracture shows an increase with increase in strain rate and decreases with increase in temperature at 10% strain. Large and elongated particles show a greater tendency for fracture in the unmodified and modified conditions. Particle orientation plays an important role on fracture and the cracks are found to occur almost in a direction normal to the tensile strain imposed upon the particles by the deforming matrix in the unmodified alloy. The modified alloy shows a random distribution of fractured particles and crack orientation. The criteria of fracture based on dislocation pile-up mechanism and fiber loading explain the observed difference in particle fracture characteristics due to modification. The particle fracture for the modified alloy is also discussed in terms of Weibull statistics and the existing models of dispersion hardening. Particle/matrix interface decohesion is observed at higher strain rates and temperatures in the modified alloy. Dendritic rotation of 10 degrees is also observed at higher strain rates, which can increase the amount of particle fracture. (C) 2013 Elsevier B.V. All rights reserved.

Measurement Based Impromptu Deployment of a Multi-Hop Wireless Relay Network

We study the problem of optimal sequential (''as-you-go'') deployment of wireless relay nodes, as a person walks along a line of random length (with a known distribution). The objective is to create an impromptu multihop wireless network for connecting a packet source to be placed at the end of the line with a sink node located at the starting point, to operate in the light traffic regime. In walking from the sink towards the source, at every step, measurements yield the transmit powers required to establish links to one or more previously placed nodes. Based on these measurements, at every step, a decision is made to place a relay node, the overall system objective being to minimize a linear combination of the expected sum power (or the expected maximum power) required to deliver a packet from the source to the sink node and the expected number of relay nodes deployed. For each of these two objectives, two different relay selection strategies are considered: (i) each relay communicates with the sink via its immediate previous relay, (ii) the communication path can skip some of the deployed relays. With appropriate modeling assumptions, we formulate each of these problems as a Markov decision process (MDP). We provide the optimal policy structures for all these cases, and provide illustrations of the policies and their performance, via numerical results, for some typical parameters.

Incorporation of Interfacial Intermetallic Morphology in Fracture Mechanism Map for Sn-Ag-Cu Solder Joints

A fracture mechanism map (FMM) is a powerful tool which correlates the fracture behavior of a material to its microstructural characteristics in an explicit and convenient way. In the FMM for solder joints, an effective thickness of the interfacial intermetallic compound (IMC) layer (t (eff)) and the solder yield strength (sigma (ys,eff)) are used as abscissa and ordinate axes, respectively, as these two predominantly affect the fracture behavior of solder joints. Earlier, a definition of t (eff), based on the uniform thickness of IMC (t (u)) and the average height of the IMC scallops (t (s)), was proposed and shown to aptly explain the fracture behavior of solder joints on Cu. This paper presents a more general definition of t (eff) that is more widely applicable to a range of metallizations, including Cu and electroless nickel immersion gold (ENIG). Using this new definition of t (eff), mode I FMM for SAC387/Cu joints has been updated and its validity was confirmed. A preliminary FMM for SAC387/Cu joints with ENIG metallization is also presented.

Network, nodes and nexus: systems approach to multitarget therapeutics

Systems biology is revealing multiple layers of regulatory networks that manifest spatiotemporal variations. Since genes and environment also influence the emergent property of a cell, the biological output requires dynamic understanding of various molecular circuitries. The metabolic networks continually adapt and evolve to cope with the changing milieu of the system, which could also include infection by another organism. Such perturbations of the functional networks can result in disease phenotypes, for instance tuberculosis and cancer. In order to develop effective therapeutics, it is important to determine the disease progression profiles of complex disorders that can reveal dynamic aspects and to develop mutitarget systemic therapies that can help overcome pathway adaptations and redundancy.

6PANview: Application performance conscious network monitoring for 6LoWPAN based WSNs

6PANview[1] is a Wireless Sensor Network(WSN) monitoring system for 6LoWPAN/RPL networks which we developed as an overlay network for a WSN application. A monitoring system, while performing its operations for maintaining the health of the monitored network, must also be conscious of its impact on the application performance, and must strive to minimize this impact. To this end, we propose a centralized scheduling algorithm within 6PANview which non-intrusively analyzes application traffic arrival patterns at the base station, identifies network idle periods and schedules monitoring activities. The proposed algorithm finds those periodic sequences which are likely to have given rise to the pattern of arrivals seen at the base station. Parts of those sequences are then extended to coarsely predict future traffic and find epochs where low traffic is predicted, in order to schedule monitoring traffic or other activities at these times. We present simulation results for the proposed prediction and scheduling algorithm and its implementation as part of 6PANview. As an enhancement, we briefly talk about using 6PANview's overlay network architecture for distributed scheduling.

Providing QoS in a cognitive radio network

We consider the problem of wireless channel allocation (whenever the channels are free) to multiple cognitive radio users in a Cognitive Radio Network (CRN) so as to satisfy their Quality of Service (QoS) requirements efficiently. The CRN base station may not know the channel states of all the users. The multiple channels are available at random times. In this setup Opportunistic Splitting can be an attractive solution. A disadvantage of this algorithm is that it requires the metrics of all users to be an independent, identically distributed sequence. However we use a recently generalized version of this algorithm in which the optimal parameters are learnt on-line through stochastic approximation and metrics can be Markov. We provide scheduling algorithms which maximize weighted-sum system throughput or are throughput or delay optimal. We also consider the scenario when some traffic streams are delay sensitive.

Flow resistance network analysis of the back-pressure of automotive mufflers

Complexity of mufflers generally introduces considerable pressure drop, which affects the engine performance adversely. Not much literature is available for pressure drop across perforates. In this paper, the stagnation pressure drop across perforated muffler elements has been measured experimentally and generalized expressions have been developed for the pressure loss across cross-flow expansion and cross-flow contraction elements. A flow resistance model available in the literature has been made use of to analytically determine the flow distribution and thereby the pressure drop of mufflers. A generalized expression has been derived here for evaluation of the equivalent flow resistance for parallel flow paths. Expressions for flow resistance across perforated elements, derived by means of flow experiments, have been implemented in the flow resistance network. The results have been validated with experimental data. Thus, the newly developed integrated flow resistance networks would enable us to determine the normalized stagnation pressure drop of commercial automotive mufflers, thus enabling an efficient flow-acoustic design of silencing systems.

Experimental study of fracture behavior of magnesium single crystals

In this work, the fracture behavior of magnesium single crystals is studied by conducting experiments with notched three point bend specimens of three crystallographic orientations. In the first and second orientations, the c-axis is along the normal to the flat surface of the notch, while in the third it is aligned with the notch front. For all the orientations, in situ electron back scattered diffraction observations made around the notch root show profuse tensile twinning of {10 (1) over bar2} type. Further, in the first two orientations basal and prismatic slip traces are identified from optical metallography. The width of the most prominent twin saturates at around 120-150 mu m, while twins continue to nucleate farther away to accommodate plastic deformation. In all the orientations, crack initiation occurs before the attainment of peak load and the crack grows stably along twin-matrix interface before deflecting at twin-twin intersections. Results show that profuse tensile twinning is an important energy dissipating mechanism that enhances the fracture toughness. (C) 2013 Elsevier B.V. All rights reserved.

Effect of choice of basis functions in neural network for capturing unknown function for dynamic inversion control

The basic requirement for an autopilot is fast response and minimum steady state error for better guidance performance. The highly nonlinear nature of the missile dynamics due to the severe kinematic and inertial coupling of the missile airframe as well as the aerodynamics has been a challenge for an autopilot that is required to have satisfactory performance for all flight conditions in probable engagements. Dynamic inversion is very popular nonlinear controller for this kind of scenario. But the drawback of this controller is that it is sensitive to parameter perturbation. To overcome this problem, neural network has been used to capture the parameter uncertainty on line. The choice of basis function plays the major role in capturing the unknown dynamics. Here in this paper, many basis function has been studied for approximation of unknown dynamics. Cosine basis function has yield the best response compared to any other basis function for capturing the unknown dynamics. Neural network with Cosine basis function has improved the autopilot performance as well as robustness compared to Dynamic inversion without Neural network.