Enhancing live virtual machine migration process via optimized resource allocation in next generation mobile edge network: A hybrid evolutionary approach

The evolution of 5th Generation wireless technology introduced Mobile Edge Computing, where edge servers are placed at the edge of the network, and are associated with evolved Node Base Stations (eNBs). This enables mobile users to offload their resource‐intensive tasks to these servers and improve network performance by reducing end‐to‐end delay. However, frequent user mobility leads to frequent re‐planning of network and increases network load. This demands dynamic Virtual Machine (VM) migration in Mobile Edge paradigm for an improved Quality of Service (QoS). For an enhanced VM migration process, an optimal pair of migrating VMs and destination edge servers needs to be chosen. In this paper, we propose an optimized decision‐making policy that chooses such optimal pairs. Several decision parameters such as average wait time, processing delay, migration delay, transmission power, and processing power are modeled. A profit function is developed using these modeled decision parameters that chooses the optimal pairs. This function is maximized using the proposed hybrid evolutionary algorithm, which combines the advantages of PSO and GA. The pairs are chosen in such a manner, that the selection guarantees high network throughput, reduced service delay, and energy consumption which is reflected in the simulation.     

Fuzzy mean–variance–skewness portfolio selection models by interval analysis

In portfolio selection problem, the expected return, risk, liquidity etc. cannot be predicted precisely. The investor generally makes his portfolio decision according to his experience and his economic wisdom. So, deterministic portfolio selection is not a good choice for the investor. In most of the recent works on this problem, fuzzy set theory is widely used to model the problem in uncertain environments. This paper utilizes the concept of interval numbers in fuzzy set theory to extend the classical mean–variance (MV) portfolio selection model into mean–variance–skewness (MVS) model with consideration of transaction cost. In addition, some other criteria like short and long term returns, liquidity, dividends, number of assets in the portfolio and the maximum and minimum allowable capital invested in stocks of any selected company are considered. Three different models have been proposed by defining the future financial market optimistically, pessimistically and in the combined form to model the fuzzy MVS portfolio selection problem. In order to solve the models, fuzzy simulation (FS) and elitist genetic algorithm (EGA) are integrated to produce a more powerful and effective hybrid intelligence algorithm (HIA). Finally, our approaches are tested on a set of stock data from Bombay Stock Exchange (BSE).     

Activatable tiles for compact robust programmable molecular assembly and other applications

Algorithmic DNA self-assembly is capable of forming complex patterns and shapes, that have been shown theoretically, and experimentally. Its experimental demonstrations, although improving over recent years, have been limited by significant assembly errors. Since 2003 there have been several designs of error-resilient tile sets but all of these existing error-resilient tile systems assumed directional growth of the tiling assembly. This is a very strong assumption because experiments show that tile self-assembly does not necessarily behave in such a fashion, since they may also grow in the reverse of the intended direction. The assumption of directional growth of the tiling assembly also underlies the growth model in theoretical assembly models such as the TAM. What is needed is a means for enforce this directionality constraint, which will allow us to reduce assembly errors. In this paper we describe a protection/deprotection strategy to strictly enforce the direction of tiling assembly growth so that the assembly process is robust against errors. Initially, we start with (1) a single “activated” tile with output pads that can bind with other tiles, along with (2) a set of “deactivated” tiles, meaning that the tile’s output pads are protected and cannot bind with other tiles. After other tiles bind to a “deactivated” tile’s input pads, the tile transitions to an active state and its output pads are exposed, allowing further growth. When these are activated in a desired order, we can enforce a directional assembly at the same scale as the original one. Such a system can be built with minimal modifications of existing DNA tile nanostructures. We propose a new type of tiles called activatable tiles and its role in compact proofreading. Activatable tiles can be thought of as a particular case of the more recent signal tile assembly model, where signals transmit binding/unbinding instructions across tiles on binding to one or more input sites. We describe abstract and kinetic models of activatable tile assembly and show that the error rate can be decreased significantly with respect to Winfree’s original kinetic tile assembly model without considerable decrease in assembly growth speed. We prove that an activatable tile set is an instance of a compact, error-resilient and self-healing tile-set. We describe a DNA design of activatable tiles and a mechanism of deprotection using DNA polymerization and strand displacement. We also perform detailed stepwise simulations using a DNA Tile simulator Xgrow, and show that the activatable tiles mechanism can reduce error rates in self assembly. We conclude with a brief discussion on some applications of activatable tiles beyond computational tiling, both as (1) a novel system for concentration of molecules, and (2) a catalyst in sequentially triggered chemical reactions.     

Treatment of arsenic contaminated water in a batch reactor by using Ralstonia eutropha MTCC 2487 and granular activated carbon

This paper presents the observations on the bio-removal of arsenic from contaminated water by using Ralstonia eutropha MTCC 2487 and activated carbon in a batch reactor. The effects of agitation time, pH, type of granular activated carbon (GAC) and initial arsenic concentration (As(o)) on the % removal of arsenic have been discussed. Under the experimental conditions, optimum removal was obtained at the pH of 6-7 with agitation time of 100 h. The % removal of As(T) increased initially with the increase in As(o) and after attaining the maximum removal (~86%) at the As(o) value of around 15 ppm, it started to decrease. Simultaneous adsorption bioaccumulation (SABA) was observed, when fresh GAC was used as supporting media for bacterial immobilization. In case of SABA, the % removal of As(III) was almost similar (only ~1% more) to the additive values of individual removal of As(III) obtained by only adsorption and only bio-adsorption. However, for As(V) the % removal was less (~8%) than the additive value of the individual % removals obtained by only adsorption and bio-adsorption. Percentage removal of Fe, Mn, Cu and Zn were 65.17%, 72.76%, 98.6% and 99.31%, respectively. Maximum regeneration (~99.4%) of the used bio-adsorbent was achieved by the treatment with 5NH(2)SO(4) followed by 1N NaOH and 30% H(2)O(2) in HNO(3). The fitness of the isotherms to predict the specific uptake for bio-adsorption/accumulation process has been found to decrease in the following order: Temkin isotherm>Langmuir isotherm>Freundlich isotherm. For the adsorption process with fresh GAC the corresponding order is Freundlich isotherm>Langmuir isotherm>Temkin isotherm for As(V) and As(T). However, for As(III) it was Langmuir>Temkin>Freundlich.     

Thermal stability of Ti/Mo and Ti/MoN nanostructures for barrier applications in Cu interconnects

This work focuses on the barrier capabilities of sputter deposited Ti/Mo and Ti/MoN nanofilms against diffusion of Cu into Si substrates. The thermal stability of the corresponding bi-layer barrier structures is investigated after annealing Cu/barrier layer/Si samples at different temperatures in N(2) for 5?min. The drastic increase in sheet resistance of Cu and the probing of Cu(3)Si with x-ray diffraction after high temperature annealing indicate the failure of these barrier structures. The formation of Cu(3)Si at the barrier breakdown temperature is also confirmed by scanning electron microscopy and energy dispersive x-ray spectroscopy. Cu?diffusion barrier performance analyses show that a Ti(5?nm)/MoN(5?nm) bi-layer nanostructure fails only after annealing at 800?°C; on the other hand, a Ti(5?nm)/Mo(5?nm) barrier stack is found to break down at 700?°C.     

Error propagation of the track model and track fitting strategy for the Iron CALorimeter detector in India-based neutrino observatory

A Kalman filter package has been developed for reconstructing muon (μ^±)$\left({\mu }^{\pm }\right)$ tracks (coming from the neutrino interactions) in ICAL detector. Here, we describe the algorithm of muon track fitting, with emphasis on the error propagation of the elements of Kalman state vector along the muon trajectory through dense materials and inhomogeneous magnetic field. The higher order correction terms are included for reconstructing muon tracks at large zenith angle θ$\theta$ (measured from the perpendicular to the detector planes). The performances of this algorithm and its limitations are discussed.     

磁性隧道结器件的建模与验证

描述了一个简单的磁性隧道结器件的模型.利用基于运算放大器的反向放大器通过仿真和实验研究并验证了该模型的隧道磁致电阻效应.实验结果证实了仿真和理论的正确性.     

A distribution free newsvendor model with consignment policy and retailer’s royalty reduction

Reducing the system cost and achieving significant profit are the key factors for every successful business sector. A consignment contract under distribution-free approach may be a fruitful combination to achieve a profitable business. This model deals with a single-period newsvendor problem with a consignment policy. The consignment policy is an agreement between any two parties, named as the consignor and the consignee. Under Stackelberg approach, firms act as leader and follower. Both parties carry some parts of the holding cost instead of one. A new policy for paying the fixed fee to the consignee is introduced. This paper considers no specific probability distribution for customer’s demand except a known mean and standard deviation. An efficient approach is proposed to reduce the retailer’s cost and building a sustainable consignment contract. The solution of this model is obtained using distribution free approach. A comparison between the traditional supply chain policy and the consignment policy is established. The price-sensitivity on demand is analysed. Some numerical examples and graphical representations are given for both traditional and consignment policy. Result proves that consignment policy is dominating over the traditional policy and a significant reduction of retailer’s royalty is found.     

A New Groundwater Management Model by Coupling Analytic Element Method and Reverse Particle Tracking with Cat Swarm Optimization

The performance of groundwater management models mostly depends upon the methodology employed to simulate flow and transport processes and the efficiency of optimization algorithms. The present study examines the effectiveness of cat swarm optimization (CSO) for groundwater management problems, by coupling it with the analytic element method (AEM) and reverse particle tracking (RPT). In this study, we propose two coupled simulation-optimization models, viz. AEM-CSO and AEM-RPT-CSO by combining AEM with RPT and CSO. Both the models utilize the added advantages of AEM, such as precise estimation of hydraulic head at pumping location and generation of continuous velocity throughout the domain. The AEM-CSO model is applied to a hypothetical unconfined aquifer considering two different objectives, i.e., maximization of the total pumping of groundwater from the aquifer and minimization of the total pumping costs. The model performance reflects the superiority of CSO in comparison with other optimization algorithms. Further, the AEM-RPT-CSO model is successfully applied to a hypothetical confined aquifer to minimize the total number of contaminant sources, within the time related capture zone of the wells, while maintaining the required water demand. In this model, RPT gets continuous velocity information directly from the AEM model. The performance evaluation of the proposed methodology, illustrates its ability to solve groundwater management problems.     

An efficient circuit-level power reduction technique for ultralow power applications

Microsystem Technologies - This research work explores various circuit-level design techniques to identify the best technique suitable for low power circuit design. To establish a proper...