Ubiquitous Computing for Remote Cardiac Patient Monitoring: A Survey

New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation

EFFICIENT UTILIZATION OF BARE METAL CORES WITH DYNAMIC MONITORING AND CALIBRATION

In existing cloud environments it is not possible to mix, on the same server at the same time, workloads that use part of a processor core, or that use cores on a best-effort basis, with workloads that must both be assigned to a single core and have that core dedicated to their use (i.e., nothing else runs on the core). To address these challenges and inefficiencies, techniques are presented herein that support a division of resources in a way that they can then be appropriately assigned to workloads. One logical pool of cores may be assigned for workloads requiring shared resources and another pool may be assigned for workloads requiring dedicated resources. The boundary between those pools may shift dynamically as, for example, additional resources are required

Cross-Layer Prioritized Video Transmission : : Adaptive Packetization, FEC Protection and Scheduling Methods

The quality of H.264/AVC compressed video delivery over time-varying and error-prone wireless channels is affected by packet losses. To support quality of service (QoS) for video delivery over wireless networks cross-layer schemes have been discussed in the literature. We introduce a cross-layer priority-aware packet fragmentation scheme at the medium access control (MAC) layer to enhance the quality of pre-encoded H.264/AVC compressed bitstreams over bit-rate limited error-prone links in wireless networks. Larger fragments are more likely to be in error but smaller fragments require more overhead. The H.264 slices are classified in four priorities at the encoder based on their cumulative mean square error (CMSE) contribution towards the received video quality. The slices of a priority class in each frame are aggregated into video packets of corresponding priority at the application (APP) layer. We derive the optimal fragment size for each priority class which achieves the maximum expected weighted goodput at different encoded video bit rates, slice sizes and bit error rates. Priority-aware packet fragmentation invokes slice discard in the buffer due to channel bit rate constraints on allocating fragment header bits. We propose a slice discard scheme using frame importance and slice CMSE contribution to control error propagation effects. Packet fragmentation is then extended to slice fragmentation by modifying the conventional H.264 decoder to handle partial slice decoding. Priority-aware slice fragmentation combined with the proposed slice discard scheme provides considerable peak signal-to-noise ratio (PSNR) and video quality metric gains as compared to priority-agnostic fragmentation. Distortion due to channel errors can be alleviated by assigning stronger channel code rates, at the cost of reduced rate for source coding. Besides MAC layer fragmentation, aggregating H.264/AVC slices at the APP layer to form video packets with sizes adapted to their importance can also improve transmission reliability. We present a cross-layer dynamic programming (DP) approach to minimize the expected received video distortion by jointly addressing the priority-adaptive packet formation at the APP layer and rate compatible punctured convolutional (RCPC) code rate allocation at the physical layer for pre-encoded prioritized slices of each group of pictures (GOP). Our scheme discards some low priority slices in order to improve protection to more important slices and meet the channel bitrate limitations, whenever necessary. Simulation results show that our proposed approach significantly improves received video quality compared to other error protection schemes. Further, we extend our cross-layer DP-based scheme to slices of each frame by predicting the expected channel bit budget per frame for real-time transmission. The prediction uses a generalized linear model developed over the parameters - CMSE per frame, channel SNR, and normalized compressed frame bit budget determined over a video dataset that spans high, medium and low motion complexity. This predicted frame bit budget is used to derive the packet sizes and their corresponding RCPC code rates for transmission using our DP-based approach. Simulation results show good correlation with the results of our DP-based scheme applied over the GOP. Unique characteristics of video traffic, such as the temporal and spatial dependencies between different video frames and their deadline constraints, pose a challenge in supporting the video quality rendered to the clients over time- varying, bandwidth-limited channels. Scalable Video Coding (H.264/SVC) enables the transmission and decoding of partial bit streams to provide video services with lower temporal or spatial resolutions or reduced fidelity while retaining a reconstruction quality that is high relative to the rate of the partial bit streams. We propose a sliding-window based flow control for scheduling the network abstraction layer (NAL) units in the post-encoding buffer of the streaming server for a real-time scalable video transmission scenario over a fast time-varying channel. Our scheduling scheme considers the importance of the NAL unit in terms of (i ) its CMSE distortion contributed to the received video quality, (ii ) its size in bits, and (iii ) its time-to-expiry in seconds. The scheduling problem of determining the appropriate order of transmission is formulated as a 0-1 knapsack problem and a DP solution is proposed which runs in polynomial time. Our scheduling approach significantly reduces the number of whole frames discarded as compared to (a) a CMSE-based scheme which considers the importance of the NAL units only in terms of their CMSE contribution, and (b) the earliest deadline first scheme which minimizes the dwelling time of the NAL units in the post-encoding buffer. Simulation results show significant PSNR gains for different video sequences at different pre-roll delay

An Image Dehazing Model considering Multiplicative Noise and Sensor Blur

A restoration model considering the data-dependent multiplicative noise, shift-invariant blur, and haze has been introduced in this paper. The proposed strategy adopts a two-step model to perform a single image dehazing under the blurred and noisy observations. The first step uses the well-known dark channel prior method to estimate the transmission of the medium and atmospheric light that signifies the global color of the haze and dehaze the images. The second step performs denoising and deblurring under a Gamma distributed noise setup and a linear blurring artefact. The restoration under the above mentioned setup has quite a few applications in satellite and long-distant telescopic imaging systems, where the captured images are noisy due to atmospheric pressure turbulence and hazy due to the presence of atmospheric dust formation; further they are blurred due to the common device artefacts. The proposed strategy is tested using a large amount of available image-sets and the performance of the model is analysed in detail in the results section

Robust On-Demand Multipath Routing with Dynamic Path Upgrade for Delay-Sensitive Data over Ad Hoc Networks

Node mobility in mobile ad hoc networks (MANETs) causes frequent route breakages and intermittent link stability. In this paper, we introduce a robust routing scheme, known as ad hoc on-demand multipath distance vector with dynamic path update (AOMDV-DPU), for delay-sensitive data transmission over MANET. The proposed scheme improves the AOMDV scheme by incorporating the following features: (i) a routing metric based on the combination of minimum hops and received signal strength indicator (RSSI) for discovery of reliable routes; (ii) a local path update mechanism which strengthens the route, reduces the route breakage frequency, and increases the route longevity; (iii) a keep alive mechanism for secondary route maintenance which enables smooth switching between routes and reduces the route discovery frequency; (iv) a packet salvaging scheme to improve packet delivery in the event of a route breakage; and (v) low HELLO packet overhead. The simulations are carried out in ns-2 for varying node speeds, number of sources, and traffic load conditions. Our AOMDV-DPU scheme achieves significantly higher throughput, lower delay, routing overhead, and route discovery frequency and latency compared to AOMDV. For H.264 compressed video traffic, AOMDV-DPU scheme achieves 3 dB or higher PSNR gain over AOMDV at both low and high node speeds