In IoT researches are found millions of devices are connected in global digital infrastructure framed in network fashion. Most of the things on the network use cloud or central database to share their data and control signals to control and manage the devices on the IoT network. Devices on the network need fast traversing paths, to take correct decision in right time. The data synchronization between source and destination is very important in real time parameter maintenance. The multidimensional parametric evaluation of the environment or the surrounding area is facing problems with data synchronization and congestion in the sensor network. This will lead arrival of fault data at the destination. The fault data also leads a misconception at user end. In the present work pipeline integration is proposed to overcome the misconception and synchronization failures. The pipeline and Arduino UNO processor are integrated on Proteus simulation tool. Transducer nodes and the functionalities are analysed with pipeline.
Mining the data from the huge collection that are present in the database and uncovering the relationships between the item set are one of the key aspects of data mining technologies. Itinerary planning system with personalization in selecting the places to the users is one of the demanding features in most of the travel plan. In this work, the system is designed in such a way to provide the customized journey plan to the users and also the effective one to the back pack travelers. Here the Points of Interests are the places to visit in each destination for the number of days chosen by the travelers. In this system, the users are allowed to specify the desired POIs to visit for the selected destination and can make their customized travel plan effectively. This proposed system is designed to choose the customized places to visit and to plan travel for K-day itineraries. The most visited itineraries are saved and updated in the database. Association rules are used to find out the frequent places visited in each destination and to provide the reputed places to the users to plan the journey. Here the Weka tool is used to evaluate the performance of the algorithm and the rules that are generated for the given travel dataset. Data set is designed by considering several attributes that can take part during travel such as source, destination, travel cost, budget, etc. Statistical analysis is done to evaluate the performance of the proposed system and the list of features that are present in the system. During the analysis part, registered users, number of logins, frequent visits, and attributes are analyzed. Thus the system can be redefined further with the
To ensure that the services are always-on and globally distributed, cloud service providers sacrifice consistency for availability. Most Cloud Service Provider's provide only eventual consistency which is a form of weak consistency. Strong Consistency is required for certain applications which are interactive. In such cases an SLA is to be engaged between the Cloud Service Provider and the users which stipulate the level of consistency the cloud service provider should provide to the users of the data cloud. Existing Commercial clouds provide strong consistency guarantees but it is hard for the users to verify it. This paper proposes a Novel Heuristic Auditor based on loosely synchronized clocks which help the users to verify whether the data cloud provides the assured level of consistency as stated in the SLA. It uses a two level auditing structure to check for strong consistency violations namely Read-After-Write(RAW) consistency and Monotonic-Write(MW) consistency. Experiments were done to verify the strong consistency guarantees provided by Google Cloud Storage (GCS). The different types of storage buckets are tested for consistency violations and are quantified with different metrics.
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