• Journal of Internet Computing and Services
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• v.7 no.1
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• pp.131-141
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• 2006

Recently, many researchers have been studied several high performance data transmission techniques such as TCP buffer Tuning, XCP and Parallel Sockets. The Parallel Sockets is an application level library for parallel data transfer, while TCP tuning, XCP and DRS are developed on kernel level. However, parallel socket is not analyzed in detail yet and need more enhancements, In this paper, we verify performance of parallel transfer technique through several experiments and analyze character of traffic interference among socket connections. In order to enhance parallel transfer management mechanism, we predict the number of socket connections to obtain SLA of the network resource and at the same time, affected network bandwidth of existing connections is measured mathematically due to the interference of other parallel transmission. Our analytical scheme predicts very well network bandwidth for applications using the parallel socket only with 8% error.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.199-211
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• 2009

Recent advancements in wireless networks have enabled support for mobile applications to transfer data over heterogeneous wireless paths in parallel using data striping technique [2]. Traditionally, high performance data transfer requires tuning of multiple TCP sockets, at sender's end, based on bandwidth delay product (BDP). Moreover, traditional techniques like Automatic TCP Buffer Tuning (ATBT), which balance memory and fulfill network demand, is designed for wired infrastructure assuming single flow on a single socket. Hence, in this paper we propose a buffer tuning technique at senders end designed to ensure high performance data transfer by striping data at transport layer across heterogeneous wireless paths. Our mechanism has the capability to become a resource management system for transport layer connections running on multi-homed mobile host supporting features for wireless link i.e. mobility, bandwidth fluctuations, link level losses. We show that our proposed mechanism performs better than ATBT, in efficiently utilizing memory and achieving aggregate throughput.