Framework for enabling highly available distributed applications for utility computing

The move towards IT outsourcing is the first step towards an environment where compute infrastructure is treated as a service. In utility computing this IT service has to honor Service Level Agreements (SLA) in order to meet the desired Quality of Service (QoS) guarantees. Such an environment requires reliable services in order to maximize the utilization of the resources and to decrease the Total Cost of Ownership (TCO). Such reliability cannot come at the cost of resource duplication, since it increases the TCO of the data center and hence the cost per compute unit. We, in this paper, look into aspects of projecting impact of hardware failures on the SLAs and techniques required to take proactive recovery steps in case of a predicted failure. By maintaining health vectors of all hardware and system resources, we predict the failure probability of resources based on observed hardware errors/failure events, at runtime. This inturn influences an availability aware middleware to take proactive action (even before the application is affected in case the system and the application have low recoverability). The proposed framework has been prototyped on a system running HP-UX. Our offline analysis of the prediction system on hardware error logs indicate no more than 10% false positives. This work to the best of our knowledge is the first of its kind to perform an end-to-end analysis of the impact of a hardware fault on application SLAs, in a live system.

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Lectin binding to complex carbohydrate at the interface: a study by resonance energy transfer

The binding affinity of the oligosaccharide moiety of a neutral glycosphingolipid, asialoGM1, towards Ricinus communis agglutinin (RCAI) was determined for the first time by fluorescence resonance energy transfer (RET). The asialoGM1 was incorporated into a phospholipid (DMPC) vesicle doped with dansylated DPPE and then titrated with an increasing amount of the galactose specific RCAI. The efficiency of RET was determined by a saturable increase in the quenching of 'donor' fluorescence, i.e. the 'trp' residue of RCAI, due to the energy transfer from the 'acceptor' dansyl group on the surface of the vesicle. The apparent binding constant was found to be in the range of 10(5)-10(6) M-1 at 27 degrees C.

Solubilization of n-decane into n-decyl-polyoxyethylene surfactants: A cavity forming free energy based model

The present paper reports the results of a theoretical study of the forces and factors driving the solubilization of n-alkane solubilizates into the micellar core of some non-ionic surfactants, based on a micellar model which includes the cavity forming free energy as a component of micellization. The solubilizate is n-decane and the non-ionic surfactants considered are n-decyl-polyoxyethylene surfactants. The extent of solubilization, i.e. the mole fraction of the solubilizate within the core has been calculated. The results indicate that the incorporated solubilizate has more translational and rotational degrees of freedom as compared to those of the tail parts of the surfactants present in the core. This drives the total free energy of aggregation after solubilization into a more favourable direction. The results are in fair agreement with the experimental results.

A molecular dynamics study based post facto free energy analysis of the binding of bovine angiogenin with UMP and CMP ligands

Angiogenin is a protein belonging to the superfamily of RNase A. The RNase activity of this protein is essential for its angiogenic activity. Although members of the RNase A family carry out RNase activity, they differ markedly in their strength and specificity. In this paper, we address the problem of higher specificity of angiogenin towards cytosine against uracil in the first base binding position. We have carried out extensive nano-second level molecular dynamics(MD) computer simulations on the native bovine angiogenin and on the CMP and UMP complexes of this protein in aqueous medium with explicit molecular solvent. The structures thus generated were subjected to a rigorous free energy component analysis to arrive at a plausible molecular thermodynamic explanation for the substrate specificity of angiogenin.

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

Solar energy decision support system

Energy plays a prominent role in human society. As a result of technological and industrial development,the demand for energy is rapidly increasing. Existing power sources that are mainly fossil fuel based are leaving an unacceptable legacy of waste and pollution apart from diminishing stock of fuels.Hence, the focus is now shifted to large-scale propagation of renewable energy. Renewable energy technologies are clean sources of energy that have a much lower environmental impact than conventional energy technologies. Solar energy is one such renewable energy. Most renewable energy comes either directly or indirectly from the sun. Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a decision support system (DSS)would help in estimating solar energy potential considering the region’s energy requirement.This article explains the design and implementation of DSS for assessment of solar energy. The DSS with executive information systems and reporting tools helps to tap vast data resources and deliver information. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in time and can be used by decision-making bodies to assess various scenarios. It also offers means of entering, accessing, and interpreting the information for the purpose of sound decision making.

Geographic Resources Decision Support System – an Open Source GIS

Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.

Energy-Efficient Decentralized Routing with Localized Cooperation Suitable for Fast Fading

Wireless networks transmit information from a source to a destination via multiple hops in order to save energy and, thus, increase the lifetime of battery-operated nodes. The energy savings can be especially significant in cooperative transmission schemes, where several nodes cooperate during one hop to forward the information to the next node along a route to the destination. Finding the best multi-hop transmission policy in such a network which determines nodes that are involved in each hop, is a very important problem, but also a very difficult one especially when the physical wireless channel behavior is to be accounted for and exploited. We model the above optimization problem for randomly fading channels as a decentralized control problem – the channel observations available at each node define the information structure, while the control policy is defined by the power and phase of the signal transmitted by each node.In particular, we consider the problem of computing an energy-optimal cooperative transmission scheme in a wireless network for two different channel fading models: (i) slow fading channels, where the channel gains of the links remain the same for a large number of transmissions, and (ii) fast fading channels,where the channel gains of the links change quickly from one transmission to another. For slow fading, we consider a factored class of policies (corresponding to local cooperation between nodes), and show that the computation of an optimal policy in this class is equivalent to a shortest path computation on an induced graph, whose edge costs can be computed in a decentralized manner using only locally available channel state information(CSI). For fast fading, both CSI acquisition and data transmission consume energy. Hence, we need to jointly optimize over both these; we cast this optimization problem as a large stochastic optimization problem. We then jointly optimize over a set of CSI functions of the local channel states, and a corresponding factored class of control policies corresponding to local cooperation between nodes with a local outage constraint. The resulting optimal scheme in this class can again be computed efficiently in a decentralized manner. We demonstrate significant energy savings for both slow and fast fading channels through numerical simulations of randomly distributed networks.

Potential of biomass energy for electricity generation in sub-Saharan Africa

The paper explores the biomass based power generation potential of Africa. Access to electricity in sub-Saharan Africa (SSA) is about 26% and falls to less than 1% in the rural areas. On the basis of the agricultural and forest produce of this region, the residues generated after processing are estimated for all the countries. The paper also addresses the use of gasification technology - an efficient thermo-chemical process for distributed power generation - either to replace fossil fuel in an existing diesel engine based power generation system or to generate electricity using a gas engine. This approach enables the implementation of electrification programs in the rural sector and gives access to grid quality power. This study estimates power generation potential at about 5000 MW and 10,000 MW by using 30% of residues generated during agro processing and 10% of forest residues from the wood processing industry, respectively. A power generation potential of 15000 MW could generate 100 terawatt-hours (TWh), about 15% of current generation in SSA. The paper also summarizes some of the experience in using the biomass gasification technology for power generation in Africa and India. The paper also highlights the techno economics and key barriers to promotion of biomass energy in sub-Saharan Africa. (C) 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Distributed Simulation Of Flexible Manufacturing Systems

Flexible Manufacturing Systems (FMS), widely considered as the manufacturing technology of the future, are gaining increasing importance due to the immense advantages they provide in terms of cost, quality and productivity over the conventional manufacturing. An FMS is a complex interconnection of capital intensive resources and high levels of system performance is very crucial for survival in a competing environment.Discrete event simulation is one of the most popular methods for performance evaluation of FMS during planning, design and operation phases. Indeed fast simulators are suggested for selection of optimal strategies for flow control (which part type to enter and at what instant), AGV scheduling (which vehicle to carry which part), routing (which machine to process the part) and part selection (which part for processing next). In this paper we develop a C-net based model for an FMS and use the same for distributed discrete event simulation. We illustrate using examples the efficacy of destributed discrete event simulation for the performance evaluation of FMSs.