Publication Type : Journal Article
Publisher : National Level Conference on Emerging Trends in Computing and Network Technologies
Source : National Level Conference on Emerging Trends in Computing and Network Technologies (2011)
Url : https://dl.acm.org/doi/10.1145/1999309.1999319
Keywords : Artificial Neural Network, logistic regression, Machine learning, Machine Learning (ML) Algorithms
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2011
Abstract : The rapid growth in the use of wireless communication and mobile devices has created a potential for variety of mobile transaction support. The variety of mobile transaction models have already been developed for dealing with different challenging requirements in this environment. However, a transaction management in mobile computing environment faces several challenges such as scarce bandwidth, limited energy resources, asymmetry in wired and wireless connectivity, asymmetry in mobile and fixed hosts, and mobility of host and their limitations. Due to these constraints, data loss, frequent disconnection, unpredicted number of wireless and wired access and high transaction aborts have been occurred. In this paper we propose a new transaction scheme called Surrogate Object based mobile transaction model. The main focus is to support data caching at surrogate object for faster data access and database operations among mobile transactions at different mobile hosts in mobile environment. This is done by creating the surrogate object in the static network to act on behalf of each mobile device. One consequence of using the surrogate object model is that mobile devices would be transparent to the instability of wireless communication. The surrogate object can remain active, maintaining information regarding the current state and plays an active role on behalf of the device and reduces the network congestions, overcomes the asymmetry in wired and wireless access and achieve the low abort rate. The performance of the proposed model for mobile transaction is evaluated and compared in the absence of surrogate object. Results showed that a significant reduction in wireless access and abort probability can be obtained with the proposed model when measuring performance metrics.
Cite this Research Publication : R. S. and Dr. Anbazhagan M, “An improved kangaroo transaction model using surrogate objects for distributed mobile system”, National Level Conference on Emerging Trends in Computing and Network Technologies, 2011.