Amplitude death in complex networks induced by environment

We present a mechanism for amplitude death in coupled nonlinear dynamical systems on a complex network having interactions with a common environment like external system. We develop a general stability analysis that is valid for any network topology and obtain the threshold values of coupling constants for the onset of amplitude death. An important outcome of our study is a universal relation between the critical coupling strength and the largest nonzero eigenvalue of the coupling matrix. Our results are fully supported by the detailed numerical analysis for different network topologies.

Delay Optimal Event Detection on Ad Hoc Wireless Sensor Networks

We consider a small extent sensor network for event detection, in which nodes periodically take samples and then contend over a random access network to transmit their measurement packets to the fusion center. We consider two procedures at the fusion center for processing the measurements. The Bayesian setting, is assumed, that is, the fusion center has a prior distribution on the change time. In the first procedure, the decision algorithm at the fusion center is network-oblivious and makes a decision only when a complete vector of measurements taken at a sampling instant is available. In the second procedure, the decision algorithm at the fusion center is network-aware and processes measurements as they arrive, but in a time-causal order. In this case, the decision statistic depends on the network delays, whereas in the network-oblivious case, the decision statistic does not. This yields a Bayesian change-detection problem with a trade-off between the random network delay and the decision delay that is, a higher sampling rate reduces the decision delay but increases the random access delay. Under periodic sampling, in the network-oblivious case, the structure of the optimal stopping rule is the same as that without the network, and the optimal change detection delay decouples into the network delay and the optimal decision delay without the network. In the network-aware case, the optimal stopping problem is analyzed as a partially observable Markov decision process, in which the states of the queues and delays in the network need to be maintained. A sufficient decision statistic is the network state and the posterior probability of change having occurred, given the measurements received and the state of the network. The optimal regimes are studied using simulation.

Insights into the Fold Organization of TIM Barrel from Interaction Energy Based Structure Networks

There are many well-known examples of proteins with low sequence similarity, adopting the same structural fold. This aspect of sequence-structure relationship has been extensively studied both experimentally and theoretically, however with limited success. Most of the studies consider remote homology or ``sequence conservation'' as the basis for their understanding. Recently ``interaction energy'' based network formalism (Protein Energy Networks (PENs)) was developed to understand the determinants of protein structures. In this paper we have used these PENs to investigate the common non-covalent interactions and their collective features which stabilize the TIM barrel fold. We have also developed a method of aligning PENs in order to understand the spatial conservation of interactions in the fold. We have identified key common interactions responsible for the conservation of the TIM fold, despite high sequence dissimilarity. For instance, the central beta barrel of the TIM fold is stabilized by long-range high energy electrostatic interactions and low-energy contiguous vdW interactions in certain families. The other interfaces like the helix-sheet or the helix-helix seem to be devoid of any high energy conserved interactions. Conserved interactions in the loop regions around the catalytic site of the TIM fold have also been identified, pointing out their significance in both structural and functional evolution. Based on these investigations, we have developed a novel network based phylogenetic analysis for remote homologues, which can perform better than sequence based phylogeny. Such an analysis is more meaningful from both structural and functional evolutionary perspective. We believe that the information obtained through the ``interaction conservation'' viewpoint and the subsequently developed method of structure network alignment, can shed new light in the fields of fold organization and de novo computational protein design.

Non-monotonic, distance-dependent relaxation of water in reverse micelles: Propagation of surface induced frustration along hydrogen bond networks

Layer-wise, distance-dependent orientational relaxation of water confined in reverse micelles (RM) is studied using theoretical and computational tools. We use both a newly constructed ``spins on a ring'' (SOR) Ising-type model (with Shore-Zwanzig rotational dynamics) and atomistic simulations with explicit water. Our study explores the effect of reverse micelle size and role of intermolecular correlations, compromised by the presence of a highly polar surface, on the distance (from the interface) dependence of water relaxation. The ``spins on a ring'' model can capture some aspects of distance dependence of relaxation, such as acceleration of orientational relaxation at intermediate layers. In atomistic simulations, layer-wise decomposition of hydrogen bond formation pattern clearly reveals that hydrogen bond arrangement of water at a certain distance away from the surface can remain frustrated due to the interaction with the polar surface head groups. This layer-wise analysis also reveals the presence of a non-monotonic slow relaxation component which can be attributed to this frustration effect and which is accentuated in small to intermediate size RMs. For large size RMs, the long time component decreases monotonically from the interface to the interior of the RMs with slowest relaxation observed at the interface. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4732095]

Bond Graph Modeling for Energy-Harvesting Wireless Sensor Networks

Researchers can use bond graph modeling, a tool that takes into account the energy conservation principle, to accurately assess the dynamic behavior of wireless sensor networks on a continuous basis.

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

Understanding the Magnetization Reversal in Six-Fold Anisotropic Hexagonal Networks

Isolated magnetic nanowires have been studied extensively and the magnetization reversal mechanism is well understood in these systems. But when these nanowires are joined together in different architectures, they behave differently and can give novel properties. Using this approach, one can engineer the network architectures to get artificial anisotropy. Here, we report six-fold anisotropy by joining the magnetic nanowires into hexagonal network. For this study, we also benchmark the widely used micromagnetic packages: OOMMF, Nmag, and LLG-simulator. Further, we propose a local hysteresis method by post processing the spatial magnetization information. With this approach we obtained the hysteresis of nanowires to understand the six-fold anisotropy and the reversal mechanism within the hexagonal networks.

A weighted average-based external clock synchronisation protocol for wireless sensor networks

Wireless Sensor Networks (WSNs) have many application scenarios where external clock synchronisation may be required because a WSN may consist of components which are not connected to each other. In this paper, we first propose a novel weighted average-based internal clock synchronisation (WICS) protocol, which synchronises all the clocks of a WSN with the clock of a reference node periodically. Based on this protocol, we then propose our weighted average-based external clock synchronisation (WECS) protocol. We have analysed the proposed protocols for maximum synchronisation error and shown that it is always upper bounded. Extensive simulation studies of the proposed protocols have been carried out using Castalia simulator. Simulation results validate our above theoretical claim and also show that the proposed protocols perform better in comparison to other protocols in terms of synchronisation accuracy. A prototype implementation of the WICS protocol using a few TelosB motes also validates the above conclusions.

Generalizing the Amplify-and-Forward Relay Gain Model: An Optimal SEP Perspective

Two models for AF relaying, namely, fixed gain and fixed power relaying, have been extensively studied in the literature given their ability to harness spatial diversity. In fixed gain relaying, the relay gain is fixed but its transmit power varies as a function of the source-relay channel gain. In fixed power relaying, the relay transmit power is fixed, but its gain varies. We revisit and generalize the fundamental two-hop AF relaying model. We present an optimal scheme in which an average power constrained AF relay adapts its gain and transmit power to minimize the symbol error probability (SEP) at the destination. Also derived are insightful and practically amenable closed-form bounds for the optimal relay gain. We then analyze the SEP of MPSK, derive tight bounds for it, and characterize the diversity order for Rayleigh fading. Also derived is an SEP approximation that is accurate to within 0.1 dB. Extensive results show that the scheme yields significant energy savings of 2.0-7.7 dB at the source and relay. Optimal relay placement for the proposed scheme is also characterized, and is different from fixed gain or power relaying. Generalizations to MQAM and other fading distributions are also discussed.

Secure Computation in a Bidirectional Relay

Bidirectional relaying, where a relay helps two user nodes to exchange equal length binary messages, has been an active area of recent research. A popular strategy involves a modified Gaussian MAC, where the relay decodes the XOR of the two messages using the naturally-occurring sum of symbols simultaneously transmitted by user nodes. In this work, we consider the Gaussian MAC in bidirectional relaying with an additional secrecy constraint for protection against a honest but curious relay. The constraint is that, while the relay should decode the XOR, it should be fully ignorant of the individual messages of the users. We exploit the symbol addition that occurs in a Gaussian MAC to design explicit strategies that achieve perfect independence between the received symbols and individual transmitted messages. Our results actually hold for a more general scenario where the messages at the two user nodes come from a finite Abelian group G, and the relay must decode the sum within G of the two messages. We provide a lattice coding strategy and study optimal rate versus average power trade-offs for asymptotically large dimensions.

Solid State and Solution Mediated Multistep Sequential Transformations in Metal-Organic Coordination Networks

Sequential transformation in a family of metal-organic framework compounds has been investigated employing both a solid-state as well as a solution mediated route. The compounds, cobalt oxy-bis(benzoate) and manganese oxybis(benzoate) having a two-dimensional structure, were reacted with bipyridine forming cobalt oxy-bis(benzoate)-4,4'-bipyridine and manganese oxy-bis(benzoate)-4,4'-bipyridine, respectively. The bipyridine containing compounds appear to form sequentially through stable intermediates. For the cobalt system, the transformation from a two-dimensional compound, Co(H2O)(2)(OBA)] (OBA = 4,4'-oxy-bis(benzoate)), I, to two different three-dimensional compounds, Co(bpy)(OBA)]center dot bpy, II, (bpy = 4,4'-bipyridine) and Co(bpy)(0.5)(OBA)], III, and reversibility between II and III have been investigated. In the manganese system, transformation from a two-dimensional compound, Mn(H2O)(2)(OBA)], Ia, to two different three-dimensional compounds, Mn (bpy)(OBA)]center dot bpy, Ha and Ha to Mn(bpy)(0.5)(OBA)], Ilia, has been investigated. It has also been possible to identify intermediate products during these transformation reactions. The possible pathways for the formation of the compounds were postulated.

Design and analysis of a peer-to-peer based distributed clock synchronisation protocol for wireless sensor networks

Clock synchronisation is an important requirement for various applications in wireless sensor networks (WSNs). Most of the existing clock synchronisation protocols for WSNs use some hierarchical structure that introduces an extra overhead due to the dynamic nature of WSNs. Besides, it is difficult to integrate these clock synchronisation protocols with sleep scheduling scheme, which is a major technique to conserve energy. In this paper, we propose a fully distributed peer-to-peer based clock synchronisation protocol, named Distributed Clock Synchronisation Protocol (DCSP), using a novel technique of pullback for complete sensor networks. The pullback technique ensures that synchronisation phases of any pair of clocks always overlap. We have derived an exact expression for a bound on maximum synchronisation error in the DCSP protocol, and simulation study verifies that it is indeed less than the computed upper bound. Experimental study using a few TelosB motes also verifies that the pullback occurs as predicted.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.