Effects of Velocity-slip and Viscosity Variation for Lubrication of Roller Bearings

A generalised form of Reynolds equation for two symmetrical surfaces is derived considering velocity-slip at the bearing surfaces. This equation is applied to study the effects ofvelocity -slip for the lubrication of roller bearings under lightly loaded conditions. Expressions for the point of cavitation, load capacities, and coefficient of friction obtained are also studied theoretically for various parameters

An Automata Based Approach for Verifying Information Flow Properties

AbstractWe present an automated verification technique to verify trace based information flow properties for finite state systems. We show that the Basic Security Predicates (BSPs) defined by Mantel in [Mantel, H., Possibilistic Definitions of Security – An Assembly Kit, in: Proceedings of the 13th IEEE Computer Security Foundations Workshop (2000), pp. 185–199], which are shown to be the building blocks of known trace based information flow properties, can be characterised in terms of regularity preserving language theoretic operations. This leads to a decision procedure for checking whether a finite state system satisfies a given BSP. Verification techniques in the literature (e.g. unwinding) are based on the structure of the transition system and are incomplete in some cases. In contrast, our technique is language based and complete for all information flow properties that can be expressed in terms of BSPs

Personalized Recommendation Systems (PRES): A Comprehensive Study and Research Issues.

The type of information systems used to recommend items to the users are called Recommendation systems. The concept of recommendations was seen among cavemen, ants and other creatures too. Users often rely on opinion of their peers when looking for selecting something, this usual behavior of the humans, led to the development of recommendation systems. There exist various recommender systems for various areas. The existing recommendation systems use different approaches. The applications of recommendation systems are increasing with increased use of web based search for users’ specific requirements. Recommendation techniques are employed by general purpose websites such as google and yahoo based on browsing history and other information like user’s geographical locations, interests, behavior in the web, history of purchase and the way they entered the website. Document recommendation systems recommend documents depending on the similar search done previously by other users. Clickstream data which provides information like user behavior and the path the users take are captured and given as input to document recommendation system. Movie recommendation systems and music recommendation systems are other areas in use and being researched to improve. Social recommendation is gaining the momentum because of huge volume of data generated and diverse requirements of the users. Current web usage trends are forcing companies to continuously research for best ways to provide the users with the suitable information as per the need depending on the search and preferences. This paper

MSIGT: Most Significant Index Generation Technique for cloud environment

Cloud Computing is a computing paradigm for delivering computational power, storage and applications as services via Internet on a pay-as-you-go basis to consumers. The data owner outsources local data to the public cloud server to reduce the cost of the data management. Critical data has to be encrypted to ensure privacy before outsourcing. The state-of-the-art SSE schemes search only over encrypted data through keywords, hence they do not provide effective data utilisation for large dataset files in cloud. We propose a Most Significant Index Generation Technique (MSIGT), that supports secure and efficient index generation time using a Most Significant Digit (MSD) radix sort. MSD radix sort is simple and faster in sorting array strings. A mathematical model is developed to encrypt the indexed keywords for secure index generation without the overhead of learning from the attacker/cloud provider. It is seen that the MSIGT scheme can reduce the cost of data on owner side to O(NT × 3) with a score calculation of O(NT). The proposed scheme is effective and efficient in comparison with the existing algorithms

IGSK: Index Generation on Split Keyword for search over cloud data

Storage as a Service (Saas) of cloud computing has become an alternative option for data owners of various organizations to store their data into the cloud. Usually sensitive data is encrypted to achieve data security and then it is outsourced into cloud. Many traditional search schemes allow data user to search over encrypted cloud data through keywords and retrieve the files of interest selectively. In this paper, we propose an efficient approach for keyword search over encrypted cloud data. The main contribution of this paper involves index generation method for keywords by using split factor. The keywords are stored in wildcard based technique within the index tree that is stored securely with low storage cost. Extensive experimental results on real-time data sets shows that the proposed solution is effective as well as efficient in Index generation and storage cost

DRFSD: Directed Restricted Flooding For Secure Data-Aggregation In Wireless Sensor Networks

Secured Data Transmission is a major issue in Wireless Sensor Networks (WSNs). In this paper we have proposed Directed Restricted Flooding Protocol (DRFSD) in WSNs. This protocol is better than H-SPREAD (Hybrid Security Protocol for REliable dAta Delivery). In DRFSD, alternate multipaths are selected based on the sensor node, that are placed at 180? direction with the Base Station (BS). This scheme is ef?cient in sending the Data Packets to the Base Station in shorter duration than the H-SPREAD. Simulation Results show that our algorithm approach performs well with respect to latency in comparison with earlier algorithm

Cost and fault-tolerant aware resource management for scientific workflows using hybrid instances on clouds

Cloud service providers are offering computing resources at a reasonable price as a pay-per-use model. Further, cloud service providers have also introduced different pricing models like spot, blockspot and spotfleet instances that are cost effective and user’s have to go through the bidding to balance the reliability and monetary costs. Henceforth, Scientific Workflows (SWf) that are used to model applications of high throughput, computation and complex large-scale data analysis are significantly adopting these computing resources. Nevertheless, spot instances are terminated when the market spot price exceeds the users bid price. Moreover, failures are inevitable in such a large distributed systems and often pose a challenge to design a fault-tolerant scheduling algorithm for SWf. This paper presents an efficient, low-cost and fault-tolerant scheduling algorithm and a bidding strategy to minimize the

Data auditing and security in cloud computing: issues, challenges and future directions

Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discusse

CADR : Congestion Alleriation using Distance Based Routing in Wireless Sensor Networks

Congestion degrades the overall network performance in WSNs and it can min-imize the throughput of the network due to the large packet drop, increased energy consumption and end-to-end delay. Even though most of the proposed congestion control schemes reduce traffic rate, they affect the fidelity level re-quired by the applications. In this paper, we propose an algorithm Congestion Alleviation using Distance based Routing (CADR) technique, where the bursty traffic is diverted towards the sink via the nodes whose queue length is below the threshold and is at minimum distance from the sink. The residual energy and the depth of the nodes are additional parameters which supports congestion mitigation. Simulation results show that the overall throughput of the network has tremendously improves for large and dense wireless sensor networks when compared to the earlier works