Impact of Energy Expenditure Rate Constraints on the performance of Multihop Wireless Mesh Networks

In this article we study the problem of joint congestion control, routing and MAC layer scheduling in multi-hop wireless mesh network, where the nodes in the network are subjected to maximum energy expenditure rates. We model link contention in the wireless network using the contention graph and we model energy expenditure rate constraint of nodes using the energy expenditure rate matrix. We formulate the problem as an aggregate utility maximization problem and apply duality theory in order to decompose the problem into two sub-problems namely, network layer routing and congestion control problem and MAC layer scheduling problem. The source adjusts its rate based on the cost of the least cost path to the destination where the cost of the path includes not only the prices of the links in it but also the prices associated with the nodes on the path. The MAC layer scheduling of the links is carried out based on the prices of the links. We study the e�ects of energy expenditure rate constraints of the nodes on the optimal throughput of the network.

Apparatus and method for heat-run test on high-power PWM converters with low energy expenditure

Before installation, a voltage source converter is usually subjected to heat-run test to verify its thermal design and performance under load. For heat-run test, the converter needs to be operated at rated voltage and rated current for a substantial length of time. Hence, such tests consume huge amount of energy in case of high-power converters. Also, the capacities of the source and loads available in the research and development (R&D) centre or the production facility could be inadequate to conduct such tests. This paper proposes a method to conduct heat-run tests on high-power, pulse width modulated (PWM) converters with low energy consumption. The experimental set-up consists of the converter under test and another converter (of similar or higher rating), both connected in parallel on the ac side and open on the dc side. Vector-control or synchronous reference frame control is employed to control the converters such that one draws certain amount of reactive power and the other supplies the same; only the system losses are drawn from the mains. The performance of the controller is validated through simulation and experiments. Experimental results, pertaining to heat-run tests on a high-power PWM converter, are presented at power levels of 25 kVA to 150 kVA.

Embodied energy in cement stabilised rammed earth walls

Rammed earth walls are low carbon emission and energy efficient alternatives to load bearing walls. Large numbers of rammed earth buildings have been constructed in the recent past across the globe. This paper is focused on embodied energy in cement stabilised rammed earth (CSRE) walls. Influence of soil grading, density and cement content on compaction energy input has been monitored. A comparison between energy content of cement and energy in transportation of materials, with that of the actual energy input during rammed earth compaction in the actual field conditions and the laboratory has been made. Major conclusions of the investigations are (a) compaction energy increases with increase in clay fraction of the soil mix and it is sensitive to density of the CSRE wall, (b) compaction energy varies between 0.033 MJ/m(3) and 0.36 MJ/m(3) for the range of densities and cement contents attempted, (c) energy expenditure in the compaction process is negligible when compared to energy content of the cement and (d) total embodied energy in CSRE walls increases linearly with the increase in cement content and is in the range of 0.4-0.5 GJ/m(3) for cement content in the rage of 6-8%. (C) 2009 Elsevier B.V. All rights reserved.

Time and Energy Complexity of Distributed Computation of a Class of Functions in Wireless Sensor Networks

We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

Analytical models for energy consumption in infrastructure WLAN STAs carrying TCP traffic

We develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fraction of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than just using CAM. For short file downloads we compute the number of file downloads that can be completed with given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator.

Embodied energy assessment of building materials in India using process and input-output analysis

Growing demand for urban built spaces has resulted in unprecedented exponential rise in production and consumption of building materials in construction. Production of materials requires significant energy and contributes to pollution and green house gas (GHG) emissions. Efforts aimed at reducing energy consumption and pollution involved with the production of materials fundamentally requires their quantification. Embodied energy (EE) of building materials comprises the total energy expenditure involved in the material production including all upstream processes such as raw material extraction and transportation. The current paper deals with EE of a few common building materials consumed in bulk in Indian construction industry. These values have been assessed based on actual industrial survey data. Current studies on EE of building materials lack agreement primarily with regard to method of assessment and energy supply assumptions (whether expressed in terms of end use energy or primary energy). The current paper examines the suitability of two basic methods; process analysis and input-output method and identifies process analysis as appropriate for EE assessment in the Indian context. A comparison of EE values of building materials in terms of the two energy supply assumptions has also been carried out to investigate the associated discrepancy. The results revealed significant difference in EE of materials whose production involves significant electrical energy expenditure relative to thermal energy use. (C) 2014 Elsevier B.V. All rights reserved.

A Haplotype at the UCP1 Gene Locus Contributes to Genetic Risk for Type 2 Diabetes in Asian Indians (CURES-72)

Background: The gene encoding for uncoupling protein-1 (UCP1) is considered to be a candidate gene for type 2 diabetes because of its role in thermogenesis and energy expenditure. The objective of the study was to examine whether genetic variations in the UCP1 gene are associated with type 2 diabetes and its related traits in Asian Indians. Methods: The study subjects, 810 type 2 diabetic subjects and 990 normal glucose tolerant (NGT) subjects, were chosen from the Chennai Urban Rural Epidemiological Study (CURES), an ongoing population-based study in southern India. The polymorphisms were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies. Results: The three polymorphisms, namely -3826A -> G, an A -> C transition in the 5'-untranslated region (UTR) and Met229Leu, were not associated with type 2 diabetes. However, the frequency of the A-C-Met (-3826A -> G-5'UTR A -> C-Met229Leu) haplotype was significantly higher among the type 2 diabetic subjects (2.67%) compared with the NGT subjects (1.45%, P < 0.01). The odds ratio for type 2 diabetes for the individuals carrying the haplotype A-C-Met was 1.82 (95% confidence interval, 1.29-2.78, P = 0.009). Conclusions: The haplotype, A-C-Met, in the UCP1 gene is significantly associated with the increased genetic risk for developing type 2 diabetes in Asian Indians.

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 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.