2,026 research outputs found
A Priority-based Fair Queuing (PFQ) Model for Wireless Healthcare System
Healthcare is a very active research area, primarily due to the increase in the elderly population that leads to increasing number of emergency situations that require urgent actions. In recent years some of wireless networked medical devices were equipped with different sensors to measure and report on vital signs of patient remotely. The most important sensors are Heart Beat Rate (ECG), Pressure and Glucose sensors. However, the strict requirements and real-time nature of medical applications dictate the extreme importance and need for appropriate Quality of Service (QoS), fast and accurate delivery of a patientâs measurements in reliable e-Health ecosystem.
As the elderly age and older adult population is increasing (65 years and above) due to the advancement in medicine and medical care in the last two decades; high QoS and reliable e-health ecosystem has become a major challenge in Healthcare especially for patients who require continuous monitoring and attention. Nevertheless, predictions have indicated that elderly population will be approximately 2 billion in developing countries by 2050 where availability of medical staff shall be unable to cope with this growth and emergency cases that need immediate intervention. On the other side, limitations in communication networks capacity, congestions and the humongous increase of devices, applications and IOT using the available communication networks add extra layer of challenges on E-health ecosystem such as time constraints, quality of measurements and signals reaching healthcare centres.
Hence this research has tackled the delay and jitter parameters in E-health M2M wireless communication and succeeded in reducing them in comparison to current available models. The novelty of this research has succeeded in developing a new Priority Queuing model ââPriority Based-Fair Queuingââ (PFQ) where a new priority level and concept of ââPatientâs Health Recordââ (PHR) has been developed and
integrated with the Priority Parameters (PP) values of each sensor to add a second level of priority. The results and data analysis performed on the PFQ model under different scenarios simulating real M2M E-health environment have revealed that the PFQ has outperformed the results obtained from simulating the widely used current models such as First in First Out (FIFO) and Weight Fair Queuing (WFQ).
PFQ model has improved transmission of ECG sensor data by decreasing delay and jitter in emergency cases by 83.32% and 75.88% respectively in comparison to FIFO and 46.65% and 60.13% with respect to WFQ model. Similarly, in pressure sensor the improvements were 82.41% and 71.5% and 68.43% and 73.36% in comparison to FIFO and WFQ respectively. Data transmission were also improved in the Glucose sensor by 80.85% and 64.7% and 92.1% and 83.17% in comparison to FIFO and WFQ respectively. However, non-emergency cases data transmission using PFQ model was negatively impacted and scored higher rates than FIFO and WFQ since PFQ tends to give higher priority to emergency cases.
Thus, a derivative from the PFQ model has been developed to create a new version namely âPriority Based-Fair Queuing-Tolerated Delayâ (PFQ-TD) to balance the data transmission between emergency and non-emergency cases where tolerated delay in emergency cases has been considered. PFQ-TD has succeeded in balancing fairly this issue and reducing the total average delay and jitter of emergency and non-emergency cases in all sensors and keep them within the acceptable allowable standards. PFQ-TD has improved the overall average delay and jitter in emergency and non-emergency cases among all sensors by 41% and 84% respectively in comparison to PFQ model
Content-Aware Multimedia Communications
The demands for fast, economic and reliable dissemination of multimedia
information are steadily growing within our society. While people and
economy increasingly rely on communication technologies, engineers still
struggle with their growing complexity.
Complexity in multimedia communication originates from several sources. The
most prominent is the unreliability of packet networks like the Internet.
Recent advances in scheduling and error control mechanisms for streaming
protocols have shown that the quality and robustness of multimedia delivery
can be improved significantly when protocols are aware of the content they
deliver. However, the proposed mechanisms require close cooperation between
transport systems and application layers which increases the overall system
complexity. Current approaches also require expensive metrics and focus on
special encoding formats only. A general and efficient model is missing so
far.
This thesis presents efficient and format-independent solutions to support
cross-layer coordination in system architectures. In particular, the first
contribution of this work is a generic dependency model that enables
transport layers to access content-specific properties of media streams,
such as dependencies between data units and their importance. The second
contribution is the design of a programming model for streaming
communication and its implementation as a middleware architecture. The
programming model hides the complexity of protocol stacks behind simple
programming abstractions, but exposes cross-layer control and monitoring
options to application programmers. For example, our interfaces allow
programmers to choose appropriate failure semantics at design time while
they can refine error protection and visibility of low-level errors at
run-time.
Based on some examples we show how our middleware simplifies the
integration of stream-based communication into large-scale application
architectures. An important result of this work is that despite cross-layer
cooperation, neither application nor transport protocol designers
experience an increase in complexity. Application programmers can even
reuse existing streaming protocols which effectively increases system
robustness.Der Bedarf unsere Gesellschaft nach kostengĂŒnstiger und
zuverlÀssiger
Kommunikation wÀchst stetig. WÀhrend wir uns selbst immer mehr von modernen
Kommunikationstechnologien abhĂ€ngig machen, mĂŒssen die Ingenieure dieser
Technologien sowohl den Bedarf nach schneller EinfĂŒhrung neuer Produkte
befriedigen als auch die wachsende KomplexitÀt der Systeme beherrschen.
Gerade die Ăbertragung multimedialer Inhalte wie Video und Audiodaten ist
nicht trivial. Einer der prominentesten GrĂŒnde dafĂŒr ist die
UnzuverlÀssigkeit heutiger Netzwerke, wie z.B.~dem Internet. Paketverluste
und schwankende Laufzeiten können die DarstellungsqualitÀt massiv
beeintrĂ€chtigen. Wie jĂŒngste Entwicklungen im Bereich der
Streaming-Protokolle zeigen, sind jedoch QualitÀt und Robustheit der
Ăbertragung effizient kontrollierbar, wenn Streamingprotokolle
Informationen ĂŒber den Inhalt der transportierten Daten ausnutzen.
Existierende AnsÀtze, die den Inhalt von Multimediadatenströmen
beschreiben, sind allerdings meist auf einzelne Kompressionsverfahren
spezialisiert und verwenden berechnungsintensive Metriken. Das reduziert
ihren praktischen Nutzen deutlich. AuĂerdem erfordert der
Informationsaustausch eine enge Kooperation zwischen Applikationen und
Transportschichten. Da allerdings die Schnittstellen aktueller
Systemarchitekturen nicht darauf vorbereitet sind, mĂŒssen entweder die
Schnittstellen erweitert oder alternative Architekturkonzepte geschaffen
werden. Die Gefahr beider Varianten ist jedoch, dass sich die KomplexitÀt
eines Systems dadurch weiter erhöhen kann.
Das zentrale Ziel dieser Dissertation ist es deshalb,
schichtenĂŒbergreifende Koordination bei gleichzeitiger Reduzierung der
KomplexitÀt zu erreichen. Hier leistet die Arbeit zwei BetrÀge zum
aktuellen Stand der Forschung. Erstens definiert sie ein universelles
Modell zur Beschreibung von Inhaltsattributen, wie Wichtigkeiten und
AbhÀngigkeitsbeziehungen innerhalb eines Datenstroms. Transportschichten
können dieses Wissen zur effizienten Fehlerkontrolle verwenden. Zweitens
beschreibt die Arbeit das Noja Programmiermodell fĂŒr multimediale
Middleware. Noja definiert Abstraktionen zur Ăbertragung und Kontrolle
multimedialer Ströme, die die Koordination von Streamingprotokollen mit
Applikationen ermöglichen. Zum Beispiel können Programmierer geeignete
Fehlersemantiken und Kommunikationstopologien auswÀhlen und den konkreten
Fehlerschutz dann zur Laufzeit verfeinern und kontrolliere
Maximizing Resource Utilization In Video Streaming Systems
Video streaming has recently grown dramatically in popularity over the Internet, Cable TV, and wire-less networks. Because of the resource demanding nature of video streaming applications, maximizing resource utilization in any video streaming system is a key factor to increase the scalability and decrease the cost of the system. Resources to utilize include server bandwidth, network bandwidth, battery life in battery operated devices, and processing time in limited processing power devices. In this work, we propose new techniques to maximize the utilization of video-on-demand (VOD) server resources. In addition to that, we propose new framework to maximize the utilization of the network bandwidth in wireless video streaming systems.
Providing video streaming users in a VOD system with expected waiting times enhances their perceived quality-of-service (QoS) and encourages them to wait thereby increasing server utilization by increasing server throughput. In this work, we analyze waiting-time predictability in scalable video streaming. We also propose two prediction schemes and study their effectiveness when applied with various stream merging techniques and scheduling policies. The results demonstrate that the waiting time can be predicted accurately, especially when enhanced cost-based scheduling is applied. The combination of waiting-time prediction and cost-based scheduling leads to outstanding performance benefits. The achieved resource sharing by stream merging depends greatly on how the waiting requests are scheduled for service. Motivated by the development of cost-based scheduling, we investigate its effectiveness in great detail and discuss opportunities for further tunings and enhancements. Additionally, we analyze the effectiveness of incorporating video prediction results into the scheduling decisions. We also study the interaction between scheduling policies and the stream merging techniques and explore new ways for enhancements.
The interest in video surveillance systems has grown dramatically during the last decade. Auto-mated video surveillance (AVS) serves as an efficient approach for the realtime detection of threats and for monitoring their progress. Wireless networks in AVS systems have limited available bandwidth that have to be estimated accurately and distributed efficiently. In this research, we develop two cross-layer optimization frameworks that maximize the bandwidth optimization of 802.11 wireless network. We develop a distortion-based cross-layer optimization framework that manages bandwidth in the wire-less network in such a way that minimizes the overall distortion. We also develop an accuracy-based cross-layer optimization framework in which the overall detection accuracy of the computer vision algorithm(s) running in the system is maximized. Both proposed frameworks manage the application rates and transmission opportunities of various video sources based on the dynamic network conditions to achieve their goals. Each framework utilizes a novel online approach for estimating the effective airtime of the network. Moreover, we propose a bandwidth pruning mechanism that can be used with the accuracy-based framework to achieve any desired tradeoff between detection accuracy and power consumption. We demonstrate the effectiveness of the proposed frameworks, including the effective air-time estimation algorithms and the bandwidth pruning mechanism, through extensive experiments using OPNET
Error and Congestion Resilient Video Streaming over Broadband Wireless
In this paper, error resilience is achieved by adaptive, application-layer rateless channel coding, which is used to protect H.264/Advanced Video Coding (AVC) codec data-partitioned videos. A packetization strategy is an effective tool to control error rates and, in the paper, source-coded data partitioning serves to allocate smaller packets to more important compressed video data. The scheme for doing this is applied to real-time streaming across a broadband wireless link. The advantages of rateless code rate adaptivity are then demonstrated in the paper. Because the data partitions of a video slice are each assigned to different network packets, in congestion-prone wireless networks the increased number of packets per slice and their size disparity may increase the packet loss rate from buffer overflows. As a form of congestion resilience, this paper recommends packet-size dependent scheduling as a relatively simple way of alleviating the buffer-overflow problem arising from data-partitioned packets. The paper also contributes an analysis of data partitioning and packet sizes as a prelude to considering scheduling regimes. The combination of adaptive channel coding and prioritized packetization for error resilience with packet-size dependent packet scheduling results in a robust streaming scheme specialized for broadband wireless and real-time streaming applications such as video conferencing, video telephony, and telemedicine
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