Scheduling Algorithms for Cloud: A Survey and Analysis

Cloud Computing is a fast growing computing paradigm due to the vast benefits it provides to the users. Scheduling becomes one of the key aspects due to the pay-as-you-go nature of the Cloud. The factors affecting the technique of scheduling applied change with change in scenarios. For instance for scheduling in hybrid clouds the data transfer speed has to be taken into consideration whereas for mobile environments scheduling becomes dependent on context change. Moreover scheduling can be improvised on many fronts such as energy efficiency, cost minimization, Maximization of resource utilization, etc. This paper surveys scheduling techniques in various Cloud Computing scenarios and sites the most efficient scheduling technique available for a particular set of user needs by comparing various techniques and the problems they address

Open Source Virtual Machines on Xen: Creation, Implementaion and Analysis

With the rapid emergence of Cloud Computing, lots of organizations, communities, groups and individuals are rushing towards Cloud services. The cloud services have the inherent benefits like minimum running and executing cost, hassle free service accessibility, on demand availability of services, viz. computing services, storage services and even using the platforms and applications directly on pay as per use basis. The backbone of Cloud is Virtualization Technology, which is re-invented to use the underlying physical resources like CPU usage, storage devices, network devices and I/O devices in an efficient and optimum way. Virtual Machine Monitors (VMMs) facilitates this by running multiple instances of Virtual Machines (VMs) that are configurable, updatable, reusable and manageable. To achieve this, open source VMM namely Xen is chosen, which is highly used in most of the Clouds used for commercial and academic purposes. A wide and detailed study of Xen VM creation, implementation, suggestions and critical analysis of the same is presented here, which may help understand the Xen usage in a better way and about the intricacies and challenges of adopting Xen for developing and running applications on it

Efficient two-dimensional magnetotellurics modelling using implicitly restarted Lanczos method

This paper presents an efficient algorithm, FDA2DMT (Free Decay Analysis for 2D Magnetotellurics (MT)), based on eigenmode approach to solve the relevant partial differential equation, for forward computation of two-dimensional (2D) responses. The main advantage of this approach lies in the fact that only a small subset of eigenvalues and corresponding eigenvectors are required for satisfactory results. This small subset (pre-specified number) of eigenmodes are obtained using shift and invert implementation of Implicitly Restarted Lanczos Method (IRLM). It has been established by experimentation that only 15-20% smallest eigenvalue and corresponding eigenvectors are sufficient to secure the acceptable accuracy. Once the single frequency response is computed using eigenmode approach, the responses for subsequent frequencies can be obtained in negligible time. Experiment design results for validation of FDA2DMT are presented by considering two synthetic models from COMMEMI report, Brewitt-Taylor and Weaver (1976) model and a field data based model from Garhwal Himalaya

Incentive Stackelberg Mean-payoff Games

We introduce and study incentive equilibria for multi-player meanpayoff games. Incentive equilibria generalise well-studied solution concepts such as Nash equilibria and leader equilibria (also known as Stackelberg equilibria). Recall that a strategy profile is a Nash equilibrium if no player can improve his payoff by changing his strategy unilaterally. In the setting of incentive and leader equilibria, there is a distinguished player called the leader who can assign strategies to all other players, referred to as her followers. A strategy profile is a leader strategy profile if no player, except for the leader, can improve his payoff by changing his strategy unilaterally, and a leader equilibrium is a leader strategy profile with a maximal return for the leader. In the proposed case of incentive equilibria, the leader can additionally influence the behaviour of her followers by transferring parts of her payoff to her followers. The ability to incentivise her followers provides the leader with more freedom in selecting strategy profiles, and we show that this can indeed improve the payoff for the leader in such games. The key fundamental result of the paper is the existence of incentive equilibria in mean-payoff games. We further show that the decision problem related to constructing incentive equilibria is NP-complete. On a positive note, we show that, when the number of players is fixed, the complexity of the problem falls in the same class as two-player mean-payoff games. We also present an implementation of the proposed algorithms, and discuss experimental results that demonstrate the feasibility of the analysis of medium sized games.Comment: 15 pages, references, appendix, 5 figure

An Approach for Solving Multiple Travelling Salesman Problem using Ant Colony Optimization

Ant Colony Optimization (ACO) is a heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization (CO) problems. The traveling salesman problem (TSP) is one of the most important combinatorial problems. Multiple traveling salesman problem (MTSP) is a typical computationally complex combinatorialOptimization problem, which is an extension of the famous traveling salesman problem (TSP). The paper proposed an approach to show how the ant colony optimization (ACO) can be applied to the MTSP with ability constraint. There are several reasons for the choice of the TSP as the problem to explain the working of ACO algorithms: it is an important NP-hard optimization problem that arises in several applications; it is a problem to which ACO algorithms are easily applied; it is easily understandable, so that the algorithm behavior is not obscured by too many technicalities; and it is a standard test bed for new algorithmic ideas as a good performance on the TSP is often taken as a proof of their usefulness. Keywords— Ant colony optimization, Traveling salesman proble

Leveraging Distributional Bias for Reactive Collision Avoidance under Uncertainty: A Kernel Embedding Approach

Many commodity sensors that measure the robot and dynamic obstacle's state have non-Gaussian noise characteristics. Yet, many current approaches treat the underlying-uncertainty in motion and perception as Gaussian, primarily to ensure computational tractability. On the other hand, existing planners working with non-Gaussian uncertainty do not shed light on leveraging distributional characteristics of motion and perception noise, such as bias for efficient collision avoidance. This paper fills this gap by interpreting reactive collision avoidance as a distribution matching problem between the collision constraint violations and Dirac Delta distribution. To ensure fast reactivity in the planner, we embed each distribution in Reproducing Kernel Hilbert Space and reformulate the distribution matching as minimizing the Maximum Mean Discrepancy (MMD) between the two distributions. We show that evaluating the MMD for a given control input boils down to just matrix-matrix products. We leverage this insight to develop a simple control sampling approach for reactive collision avoidance with dynamic and uncertain obstacles. We advance the state-of-the-art in two respects. First, we conduct an extensive empirical study to show that our planner can infer distributional bias from sample-level information. Consequently, it uses this insight to guide the robot to good homotopy. We also highlight how a Gaussian approximation of the underlying uncertainty can lose the bias estimate and guide the robot to unfavorable states with a high collision probability. Second, we show tangible comparative advantages of the proposed distribution matching approach for collision avoidance with previous non-parametric and Gaussian approximated methods of reactive collision avoidance

Progress in fluorescence biosensing and food safety towards point-of-detection (PoD) system

The detection of pathogens in food substances is of crucial concern for public health and for the safety of the natural environment. Nanomaterials, with their high sensitivity and selectivity have an edge over conventional organic dyes in fluorescent-based detection methods. Advances in microfluidic technology in biosensors have taken place to meet the user criteria of sensitive, inexpensive, user-friendly, and quick detection. In this review, we have summarized the use of fluorescence-based nanomaterials and the latest research approaches towards integrated biosensors, including microsystems containing fluorescence-based detection, various model systems with nano materials, DNA probes, and antibodies. Paper-based lateral-flow test strips and microchips as well as the most-used trapping components are also reviewed, and the possibility of their performance in portable devices evaluated. We also present a current market-available portable system which was developed for food screening and highlight the future direction for the development of fluorescence-based systems for on-site detection and stratification of common foodborne pathogens

Physico-chemical analysis of selected ground water samples of Agra city, India

The aim of present study was carried out to assess the status of the groundwater in Agra city .The range of physicochemical parameters like pH (7.2-7.7), EC (1580-5200 mmhos), TDS (1020-4950 mg/l), Turbidity (1.1-31.4 NTU), Total Alkalinity (330-525 mg/l), Total hardness 240-1425 mg/l), Chloride (295-1140 mg/l), Calcium (72-436 mg/l), Magnesium 14.6-151.2 mg/l), Sodium (126.5-1254.9 mg/l) and Potassium (1.9-60.6 mg/l) were found to be higher than the natural background level of groundwater. This indicates the groundwater pollution in selected water samples from 12 sampling sites from Feb. to May 2011 of Agra city. The results considered that the groundwater of the study area in general cannot be considered as good quality