Adapting the streaming video based on the estimated motion position

In real time video streaming, the frames must meet their timing constraints, typically specified as their deadlines. Wireless networks may suffer from bandwidth limitations. To reduce the data transmission over the wireless networks, we propose an adaption technique in the server side by extracting a part of the video frames that considered as a Region Of Interest (ROI), and drop the part outside the ROI from the frames that are between reference frames. The estimated position of the selection of the ROI is computed by using the Sum of Squared Differences (SSD) between consecutive frames. The reconstruction mechanism to the region outside the ROI is implemented in the mobile side by using linear interpolation between reference frames. We evaluate the proposed approach by using Mean Opinion Score (MOS) measurements. MOS are used to evaluate two scenarios with equivalent encoding size, where the users observe the first scenario with low bit rate for the original videos, while for the second scenario the users observe our proposed approach with high bit rate. The results show that our technique significantly reduces the amounts of data are streamed over wireless networks, while the reconstruction mechanism will provides acceptable video quality

Energy-aware adaptive solutions for multimedia delivery to wireless devices

The functionality of smart mobile devices is improving rapidly but these devices are limited in terms of practical use because of battery-life. This situation cannot be remedied by simply installing batteries with higher capacities in the devices. There are strict limitations in the design of a smartphone, in terms of physical space, that prohibit this “quick-fix” from being possible. The solution instead lies with the creation of an intelligent, dynamic mechanism for utilizing the hardware components on a device in an energy-efficient manner, while also maintaining the Quality of Service (QoS) requirements of the applications running on the device. This thesis proposes the following Energy-aware Adaptive Solutions (EASE): 1. BaSe-AMy: the Battery and Stream-aware Adaptive Multimedia Delivery (BaSe-AMy) algorithm assesses battery-life, network characteristics, video-stream properties and device hardware information, in order to dynamically reduce the power consumption of the device while streaming video. The algorithm computes the most efficient strategy for altering the characteristics of the stream, the playback of the video, and the hardware utilization of the device, dynamically, while meeting application’s QoS requirements. 2. PowerHop: an algorithm which assesses network conditions, device power consumption, neighboring node devices and QoS requirements to decide whether to adapt the transmission power or the number of hops that a device uses for communication. PowerHop’s ability to dynamically reduce the transmission power of the device’s Wireless Network Interface Card (WNIC) provides scope for reducing the power consumption of the device. In this case shorter transmission distances with multiple hops can be utilized to maintain network range. 3. A comprehensive survey of adaptive energy optimizations in multimedia-centric wireless devices is also provided. Additional contributions: 1. A custom video comparison tool was developed to facilitate objective assessment of streamed videos. 2. A new solution for high-accuracy mobile power logging was designed and implemented