Delay sensitive delivery of rich images over WLAN in telemedicine applications
Sankara Krishnan, Shivaranjani
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Transmission of medical images, that mandate lossless transmission of content over WLANs, presents a great challenge. The large size of these images coupled with the low acceptance of traditional image compression techniques within the medical community compounds the problem even more. These factors are of enormous significance in a hospital setting in the context of real-time image collaboration. However, recent advances in medical image compression techniques such as diagnostically lossless compression methodology, has made the solution to this difficult problem feasible. The growing popularity of high speed wireless LAN in enterprise applications and the introduction of the new 802.11n draft standard have made this problem pertinent. The thesis makes recommendations on the degree of compression to be performed for specific instances of image communication applications based on the image size and the underlying network devices and their topology. During our analysis, it was found that for most cases, only a portion of the image; typically the region of interest of the image will be able to meet the time deadline requirement. This dictates a need for adaptive method for maximizing the percentage of the image delivered to the receiver within the deadline. The problem of maximizing delivery of regions of interest of image data within the deadline has been effectively modeled as a multi-commodity flow problem in this work. Though this model provides an optimal solution to the problem, it is NP hard in computational complexity and hence cannot be implemented in dynamic networks. An approximation algorithm that uses greedy approach to flow allocation is proposed to cater to the connection requests in real time. While implementing integer programming model is not feasible due to time constraints, the heuristic can be used to provide a near-optimal solution for the problem of maximizing the reliable delivery of regions of interest of medical images within delay deadlines. This scenario may typically be expected when new connection requests are placed after the initial flow allocations have been made.