Tunable Locally-Optimal Geographical Forwarding in Wireless Sensor Networks with Sleep-Wake Cycling Nodes

We consider a wireless sensor network whose main function is to detect certain infrequent alarm events, and to forward alarm packets to a base station, using geographical forwarding. The nodes know their locations, and they sleep-wake cycle, waking up periodically but not synchronously. In this situation, when a node has a packet to forward to the sink, there is a trade-off between how long this node waits for a suitable neighbor to wake up and the progress the packet makes towards the sink once it is forwarded to this neighbor. Hence, in choosing a relay node, we consider the problem of minimizing average delay subject to a constraint on the average progress. By constraint relaxation, we formulate this next hop relay selection problem as a Markov decision process (MDP). The exact optimal solution (BF (Best Forward)) can be found, but is computationally intensive. Next, we consider a mathematically simplified model for which the optimal policy (SF (Simplified Forward)) turns out to be a simple one-step-look-ahead rule. Simulations show that SF is very close in performance to BF, even for reasonably small node density. We then study the end-to-end performance of SF in comparison with two extremal policies: Max Forward (MF) and First Forward (FF), and an end-to-end delay minimising policy proposed by Kim et al. 1]. We find that, with appropriate choice of one hop average progress constraint, SF can be tuned to provide a favorable trade-off between end-to-end packet delay and the number of hops in the forwarding path.

Optimal sleep-wake scheduling for quickest intrusion detection using sensor networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.

Optimal Sleep-Wake Scheduling for Quickest Intrusion Detection using wireless sensor Networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices,we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: 1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, 2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which 3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time),based on the sensor observations obtained until time slot k.Our results show that an optimum closed loop control onMk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Relay Selection for Geographical Forwarding in Sleep-Wake Cycling Wireless Sensor Networks

Our work is motivated by geographical forwarding of sporadic alarm packets to a base station in a wireless sensor network (WSN), where the nodes are sleep-wake cycling periodically and asynchronously. We seek to develop local forwarding algorithms that can be tuned so as to tradeoff the end-to-end delay against a total cost, such as the hop count or total energy. Our approach is to solve, at each forwarding node enroute to the sink, the local forwarding problem of minimizing one-hop waiting delay subject to a lower bound constraint on a suitable reward offered by the next-hop relay; the constraint serves to tune the tradeoff. The reward metric used for the local problem is based on the end-to-end total cost objective (for instance, when the total cost is hop count, we choose to use the progress toward sink made by a relay as the reward). The forwarding node, to begin with, is uncertain about the number of relays, their wake-up times, and the reward values, but knows the probability distributions of these quantities. At each relay wake-up instant, when a relay reveals its reward value, the forwarding node's problem is to forward the packet or to wait for further relays to wake-up. In terms of the operations research literature, our work can be considered as a variant of the asset selling problem. We formulate our local forwarding problem as a partially observable Markov decision process (POMDP) and obtain inner and outer bounds for the optimal policy. Motivated by the computational complexity involved in the policies derived out of these bounds, we formulate an alternate simplified model, the optimal policy for which is a simple threshold rule. We provide simulation results to compare the performance of the inner and outer bound policies against the simple policy, and also against the optimal policy when the source knows the exact number of relays. Observing the good performance and the ease of implementation of the simple policy, we apply it to our motivating problem, i.e., local geographical routing of sporadic alarm packets in a large WSN. We compare the end-to-end performance (i.e., average total delay and average total cost) obtained by the simple policy, when used for local geographical forwarding, against that obtained by the globally optimal forwarding algorithm proposed by Kim et al. 1].

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

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.

Information capacity of energy harvesting sensor nodes

Sensor nodes with energy harvesting sources are gaining popularity due to their ability to improve the network life time and are becoming a preferred choice supporting `green communication'. We study such a sensor node with an energy harvesting source and compare various architectures by which the harvested energy is used. We find its Shannon capacity when it is transmitting its observations over an AWGN channel and show that the capacity achieving energy management policies are related to the throughput optimal policies. We also obtain the capacity when energy conserving sleep-wake modes are supported and an achievable rate for the system with inefficiencies in energy storage.

A comparative-study of vapor-compression refrigeration working fluids, in the wake of the montreal protocal

A comparative study has been carried out of R-12, 22, 125, 134a, 152a, 218, 245, 500, 502, 507 and 717 as working fluids in a vapour-compression refrigeration system. Two performance parameters were defined, which are expressed in reduced quantities for a corresponding-states comparison of these refrigerants in the temperature range -20 to 50-degrees-C. One is based on the product of temperature drop to pressure penalty ratio and the available volumetric heat of vaporisation at the evaporator; the other considers the effect of isentropic compression in the ideal gas state. It was shown that R-125, 507 and 218 could be better alternatives to R-12 than R-134a. Among these, R-218 has a lower maximum cycle pressure.

IFN-gamma inhibits growth of WISH cells in a cell cycle phase-specific manner

Treatment of WISH (human amnion) cells with interferon-gamma (IFN-gamma) inhibits their growth. Release of the cells from IFN-gamma-mediated growth inhibition led to a rapid and significant increase in DNA synthesis, followed by doubling of cell numbers. The DNA synthesis profile was strikingly similar to that shown by WISH cells released from growth arrest by the G(1)/S phase inhibitor, aphidicolin, This strongly suggested that IFN-gamma treatment leads to growth inhibition of WISH cells at the G(1)/S boundary of the cell cycle. In contrast, IFN-alpha blocked growth of these cells at the G(0)/G(1) boundary.

High temperature time-dependent low cycle fatigue behaviour of a type 316L(N) stainless steel

Total strain controlled low cycle fatigue tests on 316L(N) stainless steel have been conducted in air at various strain rates in the temperature range of 773-873 K to identify the operative time-dependent mechanisms and to understand their influence on the cyclic deformation and fracture behaviour of the alloy. The cyclic stress response at all the testing conditions was marked by an initial hardening followed by stress saturation. A negative strain rate stress response is observed under specific testing conditions which is attributed to dynamic strain ageing (DSA). Transmission electron microscopy studies reveal that there is an increase in the dislocation density and enhanced slip planarity in the DSA regime. Fatigue life is found to decrease with a decrease in strain rate. The degradation in fatigue resistance is attributed to the detrimental effects associated with DSA and oxidation. Quantitative measurement of secondary cracks indicate that both transgranular and intergranular cracking are accelerated predominantly under conditions conducive to DSA.

Hingeless-rotor aeromechanical stability in axial and forward flight with wake dynamics

A finite-state wake model is used to investigate aeromechanical stability of hingeless-rotor helicopters in the ground-contact, hover and trimmed-night conditions. The investigation covers three items: (1) the convergence of the damping with increasing number of wake harmonics for the lag regressing, and body pitch and roll modes; (2) a parametric study of the damping over a range of thrust level, advance ratio and number of blades; and (3) correlations, primarily with the damping and frequency measurements of these lag and body modes. The convergence and parametric studies are conducted in the hover and trimmed-flight conditions; they include predictions from the widely used dynamic inflow model. The correlations are conducted in the ground-contact conditions and include predictions from the dynamic inflow and vortex models; recently, this vortex model is proposed for the axial-flight conditions and is used to investigate the coupled free vibrations of rotor flapping and body modes. The convergence and parametric studies show that a finite-state wake model that goes well beyond the dynamic inflow model is required for fairly converged damping, Moreover, the correlations from the finite-state wake, dynamic inflow and vortex models are generally satisfactory.

Spool valve mechanism used in a 20 K Gifford-McMahon cycle cryorefrigerator and its effect on the P-V diagram

The design and fabrication of a spool valve for a two-stage Gifford-McMahon cycle cryorefrigerator is described. The effect of this valve on the P-V diagram and practical methods of reducing the P-V degradation are also discussed.

A low cost demagnetizer with controllable cycle and adjustable level

Demagnetization to zero remanent value or to a predetermined value is of interest to magnet manufacturers and material users. Conventional methods of demagnetization using a varying alternating demagnetizing field, under a damped oscillatory or conveyor system, result in either high cost for demagnetization or large power dissipation. A simple technique using thyristors is presented for demagnetizing the material. Power consumption is mainly in the first two half-cycles of applied voltage. Hence power dissipation is very much reduced. An optimum value calculation for a thyristor triggering angle for demagnetizing high coercive materials is also presented.

Two stage Gifford-McMahon cycle cryorefrigerator operating at 20 K

A two stage Gifford-McMahon cycle cryorefrigerator operating at 20 K is described. This refrigerator uses a very simple ‘spool valve’ and a modified indigenous compressor to compress helium gas. This cryorefrigerator reaches a lowest temperature of 15.5 K; it takes ≈ 50 min to reach 20 K and the cooling capacity is ≈ 2.5 W at 25 K. The cool-down characteristics and load characteristics are presented in graphical form. The effect of changing the operating pressure ratio and the second stage regenerator matrix size are also reported. Pressure-volume (P-V) diagrams obtained at various temperatures indicate that P-V losses form the major fraction of the total losses and this becomes more pronounced as the temperature is decreased. A heat balance analysis shows the relative magnitudes of various losses.