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.

A provably tight delay-driven concurrently congestion mitigating global routing algorithm

Routing is a very important step in VLSI physical design. A set of nets are routed under delay and resource constraints in multi-net global routing. In this paper a delay-driven congestion-aware global routing algorithm is developed, which is a heuristic based method to solve a multi-objective NP-hard optimization problem. The proposed delay-driven Steiner tree construction method is of O(n(2) log n) complexity, where n is the number of terminal points and it provides n-approximation solution of the critical time minimization problem for a certain class of grid graphs. The existing timing-driven method (Hu and Sapatnekar, 2002) has a complexity O(n(4)) and is implemented on nets with small number of sinks. Next we propose a FPTAS Gradient algorithm for minimizing the total overflow. This is a concurrent approach considering all the nets simultaneously contrary to the existing approaches of sequential rip-up and reroute. The algorithms are implemented on ISPD98 derived benchmarks and the drastic reduction of overflow is observed. (C) 2014 Elsevier Inc. All rights reserved.

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

Relay Selection with Channel Probing in Sleep-Wake Cycling Wireless Sensor Networks

In geographical forwarding of packets in a large wireless sensor network (WSN) with sleep-wake cycling nodes, we are interested in the local decision problem faced by a node that has ``custody'' of a packet and has to choose one among a set of next-hop relay nodes to forward the packet toward the sink. Each relay is associated with a ``reward'' that summarizes the benefit of forwarding the packet through that relay. We seek a solution to this local problem, the idea being that such a solution, if adopted by every node, could provide a reasonable heuristic for the end-to-end forwarding problem. Toward this end, we propose a local relay selection problem consisting of a forwarding node and a collection of relay nodes, with the relays waking up sequentially at random times. At each relay wake-up instant, the forwarder can choose to probe a relay to learn its reward value, based on which the forwarder can then decide whether to stop (and forward its packet to the chosen relay) or to continue to wait for further relays to wake up. The forwarder's objective is to select a relay so as to minimize a combination of waiting delay, reward, and probing cost. The local decision problem can be considered as a variant of the asset selling problem studied in the operations research literature. We formulate the local problem as a Markov decision process (MDP) and characterize the solution in terms of stopping sets and probing sets. We provide results illustrating the structure of the stopping sets, namely, the (lower bound) threshold and the stage independence properties. Regarding the probing sets, we make an interesting conjecture that these sets are characterized by upper bounds. Through simulation experiments, we provide valuable insights into the performance of the optimal local forwarding and its use as an end-to-end forwarding heuristic.

Flexible implementation of power system corrective topology control

This paper proposes a novel decision making framework for optimal transmission switching satisfying the AC feasibility, stability and circuit breaker (CB) reliability requirements needed for practical implementation. The proposed framework can be employed as a corrective tool in day to day operation planning scenarios in response to potential contingencies. The switching options are determined using an efficient heuristic algorithm based on DC optimal power flow, and are presented in a multi-branch tree structure. Then, the AC feasibility and stability checks are conducted and the CB condition monitoring data are employed to perform a CB reliability and line availability assessment. Ultimately, the operator will be offered multiple AC feasible and stable switching options with associated benefits. The operator can use this information, other operating conditions not explicitly considered in the optimization, and his/her own experience to implement the best and most reliable switching action(s). The effectiveness of the proposed approach is validated on the IEEE-118 bus test system. (C) 2015 Elsevier B.V. All rights reserved.

Three-Dimensional Nanoarchitecture of BiFeO3 Anchored TiO2 Nanotube Arrays for Electrochemical Energy Storage and Solar Energy Conversion

Here, we report the synthesis of TiO2/BiFeO3 nano-heterostnicture (NH) arrays by anchoring BiFeO3 (BFO) particles on on TiO2 nanotube surface and investigate their pseudocapacitive and photoelectrochemical properties considering their applications in green energy fields. The unique TiO2/BFO NHs have been demonstrated both as energy conversion and storage materials. The capacitive behavior of the NHs has been found to be significantly higher than that of the pristine TiO2 NTs, which is mainly due to the anchoring of redox active BFO nanoparticles. A specific capacitance of about 440 F g(-1) has been achieved for this NHs at a current density of 1.1 A g(-1) with similar to 80% capacity retention at a current density of 2.5 A g(-1). The NHs also exhibit high energy and power performance (energy density of 46.5 Wh kg(-1) and power density of 1.2 kW kg(-1) at a current density of 2.5 A g(-1)) with moderate cycling stability (92% capacity retention after 1200 cycles). Photoelectrochemical investigation reveals that the photocurrent density of the NHs is almost 480% higher than the corresponding dark current and it shows significantly improved photoswitching performance as compared to pure TiO2 nanotubes, which has been demonstrated based the interfacial type-II band alignment between TiO2 and BFO.

Training-Based Antenna Selection for PER Minimization: A POMDP Approach

This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

Necessary and sufficient conditions for optimality in constrained general sum stochastic games

In this paper we first derive a necessary and sufficient condition for a stationary strategy to be the Nash equilibrium of discounted constrained stochastic game under certain assumptions. In this process we also develop a nonlinear (non-convex) optimization problem for a discounted constrained stochastic game. We use the linear best response functions of every player and complementary slackness theorem for linear programs to derive both the optimization problem and the equivalent condition. We then extend this result to average reward constrained stochastic games. Finally, we present a heuristic algorithm motivated by our necessary and sufficient conditions for a discounted cost constrained stochastic game. We numerically observe the convergence of this algorithm to Nash equilibrium. (C) 2015 Elsevier B.V. All rights reserved.

QoS Constrained Optimal Sink and Relay Placement in Planned Wireless Sensor Networks

We are given a set of sensors at given locations, a set of potential locations for placing base stations (BSs, or sinks), and another set of potential locations for placing wireless relay nodes. There is a cost for placing a BS and a cost for placing a relay. The problem we consider is to select a set of BS locations, a set of relay locations, and an association of sensor nodes with the selected BS locations, so that the number of hops in the path from each sensor to its BS is bounded by h(max), and among all such feasible networks, the cost of the selected network is the minimum. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard, and is hard to even approximate within a constant factor. For this problem, we propose a polynomial time approximation algorithm (SmartSelect) based on a relay placement algorithm proposed in our earlier work, along with a modification of the greedy algorithm for weighted set cover. We have analyzed the worst case approximation guarantee for this algorithm. We have also proposed a polynomial time heuristic to improve upon the solution provided by SmartSelect. Our numerical results demonstrate that the algorithms provide good quality solutions using very little computation time in various randomly generated network scenarios.

A CAPABILITY APPROACH BASED STAKEHOLDER ANALYSIS FOR THE BASE OF THE PYRAMID: A CASE STUDY OF THE FIREWOOD BASED COOK-STOVES

People living under $2 income per day, referred as Base of the Pyramid (BoP), face undesired situations like lack of nutrition, health, education etc. Design as a process of changing current undesired situation to a desired situation has failed. A crucial reason behind these failures is lack of normative basis to identify and understand the absent or unsatisfied stakeholder. Currently stakeholder analysis in the design is heuristic. This paper uses a normative framework of Capability Approach (CA) for the stakeholder analysis. A brief discussion on stakeholder theory and analysis is used to identify gaps in the literature. The constructs of the CA are discussed for its suitability to the purpose. Along with methodological details, data generated from the stakeholder interviews, focus groups in a case study of dissemination of improved cook-stoves is used to interlink the theory with the practice. The scope of this work is in identifying and investigating the motives of the stakeholders in the involvement in the product. Though a lot of insights to discern and manage crucial stakeholders is inbuilt in the methodology, this work does not claim explicit coverage of these aspects.

SMO: An Integrated Approach to Intra-array and Inter-array Storage Optimization

The polyhedral model provides an expressive intermediate representation that is convenient for the analysis and subsequent transformation of affine loop nests. Several heuristics exist for achieving complex program transformations in this model. However, there is also considerable scope to utilize this model to tackle the problem of automatic memory footprint optimization. In this paper, we present a new automatic storage optimization technique which can be used to achieve both intra-array as well as inter-array storage reuse with a pre-determined schedule for the computation. Our approach works by finding statement-wise storage partitioning hyper planes that partition a unified global array space so that values with overlapping live ranges are not mapped to the same partition. Our heuristic is driven by a fourfold objective function which not only minimizes the dimensionality and storage requirements of arrays required for each high-level statement, but also maximizes inter statement storage reuse. The storage mappings obtained using our heuristic can be asymptotically better than those obtained by any existing technique. We implement our technique and demonstrate its practical impact by evaluating its effectiveness on several benchmarks chosen from the domains of image processing, stencil computations, and high-performance computing.

Unimpeded permeation of water through biocidal graphene oxide sheets anchored on to 3D porous polyolefinic membranes

3D porous membranes were developed by etching one of the phases (here PEO, polyethylene oxide) from melt-mixed PE/PEO binary blends. Herein, we have systematically discussed the development of these membranes using X-ray micro-computed tomography. The 3D tomograms of the extruded strands and hot-pressed samples revealed a clear picture as to how the morphology develops and coarsens over a function of time during post-processing operations like compression molding. The coarsening of PE/PEO blends was traced using X-ray micro-computed tomography and scanning electron microscopy (SEM) of annealed blends at different times. It is now understood from X-ray micro-computed tomography that by the addition of a compatibilizer (here lightly maleated PE), a stable morphology can be visualized in 3D. In order to anchor biocidal graphene oxide sheets onto these 3D porous membranes, the PE membranes were chemically modified with acid/ethylene diamine treatment to anchor the GO sheets which were further confirmed by Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and surface Raman mapping. The transport properties through the membrane clearly reveal unimpeded permeation of water which suggests that anchoring GO on to the membranes does not clog the pores. Antibacterial studies through the direct contact of bacteria with GO anchored PE membranes resulted in 99% of bacterial inactivation. The possible bacterial inactivation through physical disruption of the bacterial cell wall and/or reactive oxygen species (ROS) is discussed herein. Thus this study opens new avenues in designing polyolefin based antibacterial 3D porous membranes for water purification.

Study of lateral mode SOI-MEMS resonators for reduced anchor loss

MEMS resonators fabricated in silicon-on-insulator (SOI) technology must be clamped to the substrate via anchoring stems connected either from within the resonator or through the sides, with the side-clamped solution often employed due to manufacturing constraints. This paper examines the effect of two types of commonly used side-clamped, anchoring-stem geometries on the quality factor of three different laterally-driven resonator topologies. This study employs an analytical framework which considers the relative distribution of strain energies between the resonating body and clamping stems. The ratios of the strain energies are computed using ANSYS FEA and used to provide an indicator of the expected anchor-limited quality factors. Three MEMS resonator topologies have been fabricated and characterized in moderate vacuum. The associated measured quality factors are compared against the computed strain energy ratios, and the trends are shown to agree well with the experimental data. © 2011 IOP Publishing Ltd.

Towards multilingual domain module acquisition

Máster y Doctorado en Sistemas Informáticos Avanzados, Informatika Fakultatea - Facultad de Informática

Dealing with Energy-QoE Trade-Offs in Mobile Video

Scalable video coding allows an efficient provision of video services at different quality levels with different energy demands. According to the specific type of service and network scenario, end users and/or operators may decide to choose among different energy versus quality combinations. In order to deal with the resulting trade-off, in this paper we analyze the number of video layers that are worth to be received taking into account the energy constraints. A single-objective optimization is proposed based on dynamically selecting the number of layers, which is able to minimize the energy consumption with the constraint of a minimal quality threshold to be reached. However, this approach cannot reflect the fact that the same increment of energy consumption may result in different increments of visual quality. Thus, a multiobjective optimization is proposed and a utility function is defined in order to weight the energy consumption and the visual quality criteria. Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.