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In most of the inventory management model, deterioration of item is considered as a common problem. In this study, non-instantaneous type of items are taken to examine a new decision making model of Optimal Replenishment Policy (ORP) scheme with multi-ware house multi-item model. This model is solved by a recent optimization algorithm named as Rain Optimization Algorithm (ROA) by considering different parameters like total cost, total delivery time and total investment on each item. Moreover, this research is developed with multi-warehouse model in which one is an own house and others are rented houses with restricted volume of storage. In particular period of time, deterioration of item is considered as constant and demand of items are assumed as stock independent. Shortage are allowed in the own warehouse model with backlogging. Major goal of this research is to discover retailers’ replenishment policy to obtain maximum total profit on each items with less total cost. Matlab tool is utilized to illustrate the proposed methodology as well as to solve the mathematical model. Footwear inventory management dataset engaged to evaluate the robustness of proposed methodology. Sensitivity and statistical analysis are made to examine the influence of different significant metrics on system decision variables and its outcomes are compared with different optimization algorithms.

Cloud computing relies on the advancement of distributed computing and virtualization technologies to achieve cost efficiency in the consumption of computing resources. Efficient resource allocation is one of the important concerns for cloud users. To satisfy the need of each cloud user in an efficient manner, provision has to be made to make sure that the resources are available to them at all the time. Optimal resource allocation with minimum wastage and maximizing the profit is considered to be challenging. Also once the resources are allocated, isolation among them is critical from security point of view as there exits various kinds of adversary attacks in the real world. In this paper a novel method has been proposed for priority based dynamic Virtual Machine (VM) allocation on the basis of various parameters such as No. of nodes or processor’s request, Time of execution, Importance of user, Amount of storage required etc. and isolation among the allocated virtual machines since the virtualized services, hardware, software and infrastructures share the same physical resources. Also there are chances of adversary users hosted on the same hardware which may lead to various kinds of cross VM attacks and security threats. Finally an approximation technique for resource allocation problem has been addressed which consider each unallocated resource request from user that may lead to penalty for cloud administrator which increases as time elapses. As the resource allocation problem is considered for various applications, particularly for emergency service allocations such as scientific simulations related to cyclone prediction, monsoon prediction, rainfall etc. which needs high performance computational power. Thus allocating the resource request within the predetermined time limit is of primary concern otherwise it may lose its purpose.

Network security has been an area of concern and with more and more devices getting connected to the internet, security is an indispensable functionality. Statistics show that, networks are attacked every day and we need to keep protecting the data and network from different types of attacks. In our work we have considered security issues specifically for voice communication over a mobile device. The security features implemented in the proposed work differ from existing systems. Existing systems rely on the service provider for confidentiality and authentication. In our work security measures are implemented at the device. Thus this system can provide better security when the security measures provided by the service provider are compromised. Additionally the work can also be used to provide confidently in Bluetooth networks.

Compact exceptionally delegated frameworks (MANETs) are without establishment frameworks prompted by remote adaptable contraptions with kept battery life. This enveloped battery confines in MANETs makes it required to consider the imperativeness mindfulness feature in their layout. In perspective of the way that guiding traditions have central part in MANETs, their essentialness mindfulness grows orchestrate life time by capably utilizing of the open limited imperativeness. TORA is one of these directing traditions that offer abnormal state of flexibility. This paper uses the EBC (Efficient Binary Calculation) to organize the vitality mindfulness feature to the TORA directing tradition. The proposed tradition considers courses length in its course isolate plans and furthermore fuses courses imperativeness level in its figures. It figures the directing issue as a change predicament and thereafter uses EBC to sedative a course that extends a weighted limit of the course length and the course imperativeness level. Expansive amusements in ns-2 test framework condition exhibit that the proposed directing tradition, called EBC-TORA, expands the framework lifetime shockingly and beats TORA to the extent framework life time, structure life time and total appropriated data.

Currently climate research is most priority area as climate change generally affects the society as a whole. So there is requirement to study the weather and climate variability at very high resolution in multiple spatial and temporal scales. Presently climate data are huge in size as more data are being generated compared to past. Also sophisticated models are being used for prediction of weather and climate variability, generating vast amount of multidimensional digital data. As such climate data is considered to be big data which is multi-dimensional, multi-approach and multisource. So the demand of high performance computing and cloud computing is being increased to do the climate research. This paper gives an outline of a few strategies in supporting big data administration and investigation in geoscience domain for climate studies. By analyzing contemporary information technologies and approaches, it can confirm what operational program framework and approaches are at hand and pertinent in developing big data-driven climate research. A transitory overview of HBase for storing and managing notable geoscience data across distributed machinery is highlighted. Withal MapReduce-predicated techniques to fortify parallel access of massive NetCDF data are considered. The outcomes can recognize basic issues and enhances the proficiency of dissecting huge geoscience information by lessening information preparing time.

Extraction Transformation Load (ETL) is an important component of data warehouse. Extraction deals with the retrieval of data from various sources. These sources of data can be of different format and different location in space (1). Each of these locations must be analyzed before it is loaded on to the data warehouse. The most important and complex part of ETL is the Transformation phase. Transformation can be visualized as the change that must be made on to the source data before it is loaded on to the data warehouse. There are various methods that are used for transformation. Usual transformation include deletion of a column, conversion of values from one representation to the other, aggregation of values for better retrieval, removal of null values, converting multiple representations in to a single format and joining of multiple tables. The last phase is the loading phase which copies the information from the transformed data to the warehouse. The overall process consists of three major steps first identification of the source targets second is the actual data representation also called conversion and the last phase is moving resultant to the target location. These tasks can be done in intermediate stages or as a single logical execution. Each of these stages indicated separately will help improve the overall representation of Data Warehouse. The initial design of conceptual schema plays an important role and also propagates to other stages. The complexity of extraction transformation and load lies in the mapping of data from source to destination. As indicated by Alkis Simitsis (1) the environment of ETL process can be shown in fig 1. The left side we have source representation where in information is

Cloud resources like Amazon EC2 and Google Compute Engine have become an integral part of our life with their pay-per-use pricing models. On the other hand, attempts have also been made to create virtual clouds on the fly using available devices in the locality like smartphones and tablets. Such devices being equipped with powerful processors, this is a novel method of utilizing their normally unused computational capabilities. We attempt to design and develop a pricing model for such resources created for opportunistic computing. Since the values of the resources in these virtual clouds cannot be calculated, the pay-per-resource model has to give way to a pay-per-effort model. We model the scenario as a principal-agent problem with moral hazards and propose an incentive-driven Quality of Service (QoS) to ensure that the agents act appropriately. In view of the short contractual duration, we consider only deterministic contracts which are easy to understand and implement. We show that the mobile devices can be modeled as economic actors in a contractual arrangement and discuss how the optimal decisions are identified.

Privacy Preserving Data Mining is a method which ensures privacy of individual information during mining. Most important task involves retrieving information from multiple data bases which is distributed. The data once in the data warehouse can be used by mining algorithms to retrieve confidential information. The proposed framework has two major tasks, secure transmission and privacy of confidential information during mining. Secure transmission is handled by using elliptic curve cryptography and data distortion for privacy preservation ensuring highly secure environment., 8 pages