In situ formation of silver nanowire networks on paper

Simple, universally adaptable techniques for fabricating conductive patterns are required to translate laboratory-scale innovations into low-cost solutions for the developing world. Silver nanostructures have emerged as attractive candidates for forming such conductive patterns. We report here the in situ formation of conductive silver-nanowire networks on paper, thereby eliminating the need for either cost-intensive ink formulation or substrate preparation or complex post-deposition sintering steps. Reminiscent of the photographic process of `salt printing', a desktop office printer was used to deposit desired patterns of silver bromide on paper, which were subsequently exposed to light and then immersed in a photographic developer. Percolating silver nanowire networks that conformally coated the paper fibres were formed after 10 min of exposure to light from a commercial halogen lamp. Thus, conductive and patterned films with sheet resistances of the order of 4 Omega/rectangle can be easily formed by combining two widely used processes - inkjet printing and photographic development.

Role of Crosslinking and Entanglements in the Mechanics of Silicone Networks

The goal of this study is to investigate the applicability of different constitutive models for silicone networks using comprehensive multiaxial experimental tests, including non-equibiaxial mechanical tests which introduce differential constraints on the networks in the two orthogonal directions, on samples prepared using various crosslinking densities. Uniaxial stress-strain experiments show that a decrease in crosslinker amounts used in the preparation of silicone networks lead to more compliant material response as compared to that obtained using higher amounts of crosslinker. Biaxial data were used to obtain fits to the neo- Hookean, Mooney-Rivlin, Arruda-Boyce and the Edward-Vilgis slip-link constitutive models. Our results show that the slip-link model, based on separation of the individual contributions of chemical crosslinks and physical entanglements, is better at describing the stress-strain response of highly crosslinked networks at low stretches as compared to other constitutive models. Modulus obtained using the slip-link model for highly crosslinked networks agrees with experimentally determined values obtained using uniaxial tension experiments. In contrast, moduli obtained using coefficients to the other constitutive models underpredict experimentally determined moduli by over 40 %. However, the slip-link model did not predict the experimentally observed stiffening response at higher stretches which was better captured using the Arruda-Boyce model.

Give-and-take based peer-to-peer content distribution networks

Content Distribution Networks (CDNs) are widely used to distribute data to large number of users. Traditionally, content is being replicated among a number of surrogate servers, leading to high operational costs. In this context, Peer-to-Peer (P2P) CDNs have emerged as a viable alternative. An issue of concern in P2P networks is that of free riders, i.e., selfish peers who download files and leave without uploading anything in return. Free riding must be discouraged. In this paper, we propose a criterion, the Give-and-Take (G&T) criterion, that disallows free riders. Incorporating the G&T criterion in our model, we study a problem that arises naturally when a new peer enters the system: viz., the problem of downloading a `universe' of segments, scattered among other peers, at low cost. We analyse this hard problem, and characterize the optimal download cost under the G&T criterion. We propose an optimal algorithm, and provide a sub-optimal algorithm that is nearly optimal, but runs much more quickly; this provides an attractive balance between running time and performance. Finally, we compare the performance of our algorithms with that of a few existing P2P downloading strategies in use. We also study the computation time for prescribing the strategy for initial segment and peer selection for the newly arrived peer for various existing and proposed algorithms, and quantify cost-computation time trade-offs.

The opportunity for sampling: the ecological context of female mate choice

Female mate choice decisions, which influence sexual selection, involve complex interactions between the 2 sexes and the environment. Theoretical models predict that male movement and spacing in the field should influence female sampling tactics, and in turn, females should drive the evolution of male movement and spacing to sample them optimally. Theoretically, simultaneous sampling of males using the best-of-n or comparative Bayes strategy should yield maximum mating benefits to females. We examined the ecological context of female mate sampling based on acoustic signals in the tree cricket Oecanthus henryi to determine whether the conditions for such optimal strategies were met in the field. These strategies involve recall of the quality and location of individual males, which in turn requires male positions to be stable within a night. Calling males rarely moved within a night, potentially enabling female sampling strategies that require recall. To examine the possibility of simultaneous acoustic sampling of males, we estimated male acoustic active spaces using information on male spacing, call transmission, and female hearing threshold. Males were found to be spaced far apart, and active space overlap was rare. We then examined female sampling scenarios by studying female spacing relative to male acoustic active spaces. Only 15% of sampled females could hear multiple males, suggesting that simultaneous mate sampling is rare in the field. Moreover, the relatively large distances between calling males suggest high search costs, which may favor threshold strategies that do not require memory.

Inferring biochemical routes from biochemical networks

Metabolism is a defining feature of life, and its study is important to understand how a cell works, alterations that lead to disease and for applications in drug discovery. From a systems perspective, metabolism can be represented as a network that captures all the metabolites as nodes and the inter-conversions among pairs of them as edges. Such an abstraction enables the networks to be studied by applying graph theory, particularly, to infer the flow of chemical information in the networks by identifying relevant metabolic pathways. In this study, different weighting schemes are used to illustrate that appropriately weighted networks can capture the quantitative cellular dynamics quite accurately. Thus, the networks now combine the elegance and simplicity of representation of the system and ease of analysing metabolic graphs. Metabolic routes or paths determined by this therefore are likely to be more biologically meaningful. The usefulness of the approach is demonstrated with two examples, first for understanding bacterial stress response and second for studying metabolic alterations that occurs in cancer cells.

Precoding-Based Network Alignment Using Transform Approach for Acyclic Networks With Delay

The algebraic formulation for linear network coding in acyclic networks with the links having integer delay is well known. Based on this formulation, for a given set of connections over an arbitrary acyclic network with integer delay assumed for the links, the output symbols at the sink nodes, at any given time instant, is a F(p)m-linear combination of the input symbols across different generations, where F(p)m denotes the field over which the network operates (p is prime and m is a positive integer). We use finite-field discrete Fourier transform to convert the output symbols at the sink nodes, at any given time instant, into a F(p)m-linear combination of the input symbols generated during the same generation without making use of memory at the intermediate nodes. We call this as transforming the acyclic network with delay into n-instantaneous networks (n is sufficiently large). We show that under certain conditions, there exists a network code satisfying sink demands in the usual (nontransform) approach if and only if there exists a network code satisfying sink demands in the transform approach. When the zero-interference conditions are not satisfied, we propose three precoding-based network alignment (PBNA) schemes for three-source three-destination multiple unicast network with delays (3-S 3-D MUN-D) termed as PBNA using transform approach and time-invariant local encoding coefficients (LECs), PBNA using time-varying LECs, and PBNA using transform approach and block time-varying LECs. We derive sets of necessary and sufficient conditions under which throughputs close to n' + 1/2n' + 1, n'/2n' + 1, and n'/2n' + 1 are achieved for the three source-destination pairs in a 3-S 3-D MUN-D employing PBNA using transform approach and time-invariant LECs, and PBNA using transform approach and block time-varying LECs, where n' is a positive integer. For PBNA using time-varying LECs, we obtain a sufficient condition under which a throughput demand of n(1)/n, n(2)/n, and n(3)/n can be met for the three source-destination pairs in a 3-S 3-D MUN-D, where n(1), n(2), and n(3) are positive integers less than or equal to the positive integer n. This condition is also necessary when n(1) + n(3) = n(1) + n(2) = n where n(1) >= n(2) >= n(3).

Co-Evolution of Content Spread and Popularity in Mobile Opportunistic Networks

We consider a setting in which a single item of content is disseminated in a population of mobile nodes by opportunistic copying when pairs of nodes come in radio contact. The nodes in the population may either be interested in receiving the content (referred to as destinations) or not yet interested in receiving the content (referred to as relays). We consider a model for the evolution of popularity, the process by which relays get converted into destinations. A key contribution of our work is to model and study the joint evolution of content popularity and its spread in the population. Copying the content to relay nodes is beneficial since they can help spread the content to destinations, and could themselves be converted into destinations. We derive a fluid limit for the joint evolution model and obtain optimal policies for copying to relay nodes in order to deliver content to a desired fraction of destinations, while limiting the fraction of relay nodes that get the content but never turn into destinations. We prove that a time-threshold policy is optimal for controlling the copying to relays, i.e., there is an optimal time-threshold up to which all opportunities for copying to relays are exploited, and after which relays are not copied to. We then utilize simulations and numerical evaluations to provide insights into the effects of various system parameters on the optimally controlled co-evolution model.

Two timescale convergent Q-learning for sleep-scheduling in wireless sensor networks

In this paper, we consider an intrusion detection application for Wireless Sensor Networks. We study the problem of scheduling the sleep times of the individual sensors, where the objective is to maximize the network lifetime while keeping the tracking error to a minimum. We formulate this problem as a partially-observable Markov decision process (POMDP) with continuous stateaction spaces, in a manner similar to Fuemmeler and Veeravalli (IEEE Trans Signal Process 56(5), 2091-2101, 2008). However, unlike their formulation, we consider infinite horizon discounted and average cost objectives as performance criteria. For each criterion, we propose a convergent on-policy Q-learning algorithm that operates on two timescales, while employing function approximation. Feature-based representations and function approximation is necessary to handle the curse of dimensionality associated with the underlying POMDP. Our proposed algorithm incorporates a policy gradient update using a one-simulation simultaneous perturbation stochastic approximation estimate on the faster timescale, while the Q-value parameter (arising from a linear function approximation architecture for the Q-values) is updated in an on-policy temporal difference algorithm-like fashion on the slower timescale. The feature selection scheme employed in each of our algorithms manages the energy and tracking components in a manner that assists the search for the optimal sleep-scheduling policy. For the sake of comparison, in both discounted and average settings, we also develop a function approximation analogue of the Q-learning algorithm. This algorithm, unlike the two-timescale variant, does not possess theoretical convergence guarantees. Finally, we also adapt our algorithms to include a stochastic iterative estimation scheme for the intruder's mobility model and this is useful in settings where the latter is not known. Our simulation results on a synthetic 2-dimensional network setting suggest that our algorithms result in better tracking accuracy at the cost of only a few additional sensors, in comparison to a recent prior work.

An Eigen Approach to Transmit Beamforming in Wireless Networks With Single Antenna Receivers

In this paper, we propose an eigen framework for transmit beamforming for single-hop and dual-hop network models with single antenna receivers. In cases where number of receivers is not more than three, the proposed Eigen approach is vastly superior in terms of ease of implementation and computational complexity compared with the existing convex-relaxation-based approaches. The essential premise is that the precoding problems can be posed as equivalent optimization problems of searching for an optimal vector in the joint numerical range of Hermitian matrices. We show that the latter problem has two convex approximations: the first one is a semi-definite program that yields a lower bound on the solution, and the second one is a linear matrix inequality that yields an upper bound on the solution. We study the performance of the proposed and existing techniques using numerical simulations.

Energy-efficient, delay-constrained, QoS-aware broadcast for cooperative wireless sensor networks

The problem of delay-constrained, energy-efficient broadcast in cooperative wireless networks is NP-complete. While centralised setting allows some heuristic solutions, designing heuristics in distributed implementation poses significant challenges. This is more so in wireless sensor networks (WSNs) where nodes are deployed randomly and topology changes dynamically due to node failure/join and environment conditions. This paper demonstrates that careful design of network infrastructure can achieve guaranteed delay bounds and energy-efficiency, and even meet quality of service requirements during broadcast. The paper makes three prime contributions. First, we present an optimal lower bound on energy consumption for broadcast that is tighter than what has been previously proposed. Next, iSteiner, a lightweight, distributed and deterministic algorithm for creation of network infrastructure is discussed. iPercolate is the algorithm that exploits this structure to cooperatively broadcast information with guaranteed delivery and delay bounds, while allowing real-time traffic to pass undisturbed.