A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.     

Modelling microtubules in the brain as n-qudit quantum Hopfield network and beyond

The scientific approach to understand the nature of consciousness revolves around the study of the human brain. Neurobiological studies that compare the nervous system of different species have accorded the highest place to humans on account of various factors that include a highly developed cortical area comprising of approximately 100 billion neurons, that are intrinsically connected to form a highly complex network. Quantum theories of consciousness are based on mathematical abstraction and the Penrose–Hameroff Orch-OR theory is one of the most promising ones. Inspired by the Penrose–Hameroff Orch-OR theory, Behrman et al. have simulated a quantum Hopfield neural network with the structure of a microtubule. They have used an extremely simplified model of the tubulin dimers with each dimer represented simply as a qubit, a single quantum two-state system. The extension of this model to n-dimensional quantum states or n-qudits presented in this work holds considerable promise for even higher mathematical abstraction in modelling consciousness systems.     

Multi‐band pattern reconfigurable Yagi‐Uda antenna

In this study, novel designs of single‐band and tri‐band pattern reconfigurable antennas are proposed. The design of single‐band pattern reconfigurable antenna is accomplished by the use of varactor diodes with the parasitic elements placed on both sides of the driven conventional printed dipole antenna. By tuning the capacitance of varactor, the antenna operates in four different configurations of radiation pattern which include bi‐directional end‐fire, broadside, and uni‐directional end‐fire radiation patterns. The tri‐band pattern reconfigurable antenna design is achieved by the use of parasitic elements on both sides of a tri‐band driven dipole antenna. Dual‐band LC resonators are used as loading elements along the arms of printed dipole to get two lower order modes in addition to the reference dipole mode, resulting in a triband operation of the driven element. The electrical lengths of the parasitic elements with respect to the tri‐band driven element are controlled by suitably embedding varactor and PIN diodes with them. The proposed tri‐band antenna operates in ten different configurations of radiation patterns in the three operating bands. Fully functional prototypes of single‐band and tri‐band pattern reconfigurable antennas along with the DC bias networks have been fabricated to validate the results obtained in simulation.     

A blind medical image watermarking: DWT-SVD based robust and secure approach for telemedicine applications

Multimedia Tools and Applications - In this paper, a blind image watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed. In this scheme,...     

A new representation and associated algorithms for generalized planning

Constructing plans that can handle multiple problem instances is a longstanding open problem in AI. We present a framework for generalized planning that captures the notion of algorithm-like plans and unifies various approaches developed for addressing this problem. Using this framework, and building on the TVLA system for static analysis of programs, we develop a novel approach for computing generalizations of classical plans by identifying sequences of actions that will make measurable progress when placed in a loop. In a wide class of problems that we characterize formally in the paper, these methods allow us to find generalized plans with loops for solving problem instances of unbounded sizes and also to determine the correctness and applicability of the computed generalized plans. We demonstrate the scope and scalability of the proposed approach on a wide range of planning problems.     

An improved timestamp-based remote user authentication scheme

To protect the remote server from various malicious attacks, many authentication schemes have been proposed. Some schemes have to maintain a password verification table in the remote server for checking the legitimacy of the login users. To overcome potential risks of verification tables, researchers proposed remote user authentication schemes using smartcard, in which the remote server only keeps a secret key for computing the user’s passwords and does not need any verification table for verifying legal user. In 2003 Shen, Lin, and Hwang proposed a timestamp-based password authentication scheme using smartcards in which the remote server does not need to store the passwords or verification table for user authentication. Unfortunately, this scheme is vulnerable to some deadly attacks. In this paper, we analyze few attacks and finally propose an improved timestamp-based remote user authentication scheme. The modified scheme is more efficient and secure than original scheme.     

Reconstruction Based Recognition of Scenes with Multiple Repeated Components

This paper proposes an invariance based recognition scheme for scenes with multiple repeated components. The scheme considers three component subsets which characterize the scene completely. Each such three component subset is reconstructed using single image based information. We have developed a mathematical framework for the projective reconstruction based on relative affine structure of each such three component building block. This is extended to the case when each of the components is a quadric. A set of projective invariants of three quadrics has also been obtained by us. Although the reconstruction scheme is general and applicable to all multiple repeated components, it requires the computation of infinite homography. The infinite homography and hence the reconstruction scheme are only image computable with the given information in the case of translational repetition. We therefore develop a recognition strategy for the specific case of translationally repeated quadrics. As a recognition strategy for scenes with multiple translationally repeated quadric components, we propose to compute and store invariant values for each such three component subsets. Experiments on real data have shown the applicability of this approach for recognition of aerial images of power plants. The discriminatory power of the invariants and the stability of the recognition results have also been experimentally demonstrated.     

An Algebraic QoS-Based Resource Allocation Model for Competitive Multimedia Applications

A new class of multimedia applications require new mechanisms to consider various Quality of Services with respect to resource constraints so that they could support reliable services and utilize available resources optimally. In this paper we present a new analytical and generic resource management model that is QoS-based. The approach for resource allocation and relevant algorithms is based on a mathematically proved model that manages resource and QoS allocation intelligently so that the total system utility of is maximized. We use the constructs of application benefit functions and resource demand functions to represent the system configuration and to solve the resource allocation problems. Extensive surveys on the related work including systematic and analytical approaches are also presented.     

Electrospinning hollow and core/sheath nanofibers using hydrodynamic fluid focusing

Hollow poly (vinylpyrrolidone) (PVP) + TiO₂ and polypyrrole (core)/PVP (sheath) nanofibers were successfully electrospun using hydrodynamic fluid focusing. Utilizing a two-dimensional fluid focusing technique previously applied to aqueous solutions, intersecting microchannels cast in (poly)dimethylsiloxane were utilized to dynamically center core fluids in immiscible sheath fluids prior to electrospinning at the channel outlet. Advantages of using microfluidic channel networks for the electrospinning of composite nanofibers include spatiotemporal control over input reagents, ease of fabrication and the ability to focus the core stream into sheath layer without the need of complex co-annular nozzles.     

Reconstruction-based recognition of scenes with translationallyrepeated quadrics

This paper addresses the problem of invariant-based recognition of quadric configurations from a single image. These configurations consist of a pair of rigidly connected translationally repeated quadric surfaces. This problem is approached via a reconstruction framework. A new mathematical framework, using relative affine structure, on the lines of Luong and Vieville (1996), has been proposed. Using this mathematical framework, translationally repeated objects have been projectively reconstructed, from a single image, with four image point correspondences of the distinguished points on the object and its translate. This has been used to obtain a reconstruction of a pair of translationally repeated quadrics. We have proposed joint projective invariants of a pair of proper quadrics. For the purpose of recognition of quadric configurations, we compute these invariants for the pair of reconstructed quadrics. Experimental results on synthetic and real images, establish the discriminatory power and stability of the proposed invariant-based recognition strategy. As a specific example, we have applied this technique for discriminating images of monuments which are characterized by translationally repeated domes modeled as quadrics