Adaptive available bandwidth estimation for internet video streaming

Tunali, Turhan; Anar, Koray

doi:10.1016/j.image.2005.10.001

Cited by 6 publications

(3 citation statements)

References 23 publications

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“…In this work the available bandwidth was measured based on measuring the average throughput for the ultrasound stream over time at the receiver using the bottleneck capacity estimation described in [10]. The measurement of this average throughput is then sent from the expert station to the patient station.…”

Section: Implementation and Resultsmentioning

confidence: 99%

Provisioning of medical quality of services for HSDPA and mobile WiMAX in healthcare applications

Istepanian

Philip

2009

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Mobile healthcare, or m-health, is an evolutionary concept that provides both mobility and an 'always connected' healthcare functionality. The development of this concept depends on how best the available bandwidth in (HSDPA/HSUPA) and emerging (Mobile WiMAX) networks can be correlated with the relevant medical quality of services issues. In this paper we address and discuss some of these issues and challenges. We also provide an example of a bandwidth demanding application to verify such provision mechanisms.

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Section: Implementation and Resultsmentioning

confidence: 99%

Provisioning of medical quality of services for HSDPA and mobile WiMAX in healthcare applications

Istepanian

Philip

2009

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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“…The available bandwidth estimation is done by mathematically computing the measured sent and received gaps between probe packets. The list of the protocols that falls under packet pair/train dispersion active protocol in literature are: twoway available bandwidth estimation(TWABE) [32], gaps of non-adjacent probe packet (GNAPP) [8], network link characteristics using packet pair dispersion (NLCPPD) [33], new enhanced available bandwidth measurement technique (NEXT) [34], new enhanced available bandwidth measurement technique extension (NEXT-V2) [35], new enhanced available bandwidth measurement technique extension with piggybacking (NEXTV2 with piggybacking), WBest [36], RT-WABEST [37], initial gap increase (IGI) [38] [39], adaptive available bandwidth estimation (AABE) [40], etc.…”

Section: Figure 2: Effect Of Packet Probing At Nodes Having Time Sepamentioning

confidence: 99%

Bandwidth Estimation for Admission Control in MANET: Review and Conceptual MANET Admission Control Framework

Aina

Yousef

Osanaiye

2018

Advances in Intelligent Systems and Computing

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Mobile ad-hoc network (MANET) is one of the main technologies for the next generation wireless networking because of the positive impact it poses over other wireless networks having undergone rapid progress, which has inspired many applications. However, providing quality of service (QoS) assurance to MANET is hard because of the unpredictable nature of the wireless medium, contention problem amongst the channel, mobility problem and lack of central coordinator. Admission control is therefore seen as one of the methods for providing QoS. Admission control aim at estimating the network resource states and decides whether to admit a session without assuring more resources bandwidth space than what is available, to avoid the violation of any rules that has been previously made. Some recent solution considered the MAC layer back-off impact due to collision as well as the non-synchronization between the sender and receiver when estimating the available bandwidth. None of the previous work proposed a technique that sends a HELLO packet to its one-hop neighbours which further aggregates to the rest of the nodes to retrieve the available bandwidth on a carrier sensing region, in order to limit the impact of additional overhead of the carrier sensing multiple access with collision avoidance (CSMA/CA). Also, none of the existing solution has properly addressed the channel idle time dependency between the sending node and the receiving node by differentiating the BUSY state from the SENSE BUSY states and the IDLE state caused by an empty queue. This paper, therefore reviews the bandwidth estimation techniques for admission control for MANET. The bandwidth estimation techniques for admission control have been categorized into two, active and passive estimation. An outline of each technique has been discussed as well as the proposed conceptual framework. The contribution as identified in this research work is the proposal of conceptual framework that adapts the following into the bandwidth estimation for admission control in MANET: (i) HELLO packet advertisement to one hop which further aggregates to retrieve the available bandwidth on the carrier sensing region, (ii) Considering the channel idle time measurement by differentiating the channel busy state from channel sensing state and regarding an empty queue as an idle state. Future research directions are also outlined.

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“…The accuracy of these techniques is still not satisfactory. The active techniques present in literature are Variable Packet Size (VPS) [11], SelfLoading Periodic Streams (SLoPS) [12,13], Train of Packet Pairs (TOPP) [14], Packet Train Pair (PTP) [15], SelfLoading Decreasing Rate Train (SLDRT) [16], Probabilistic Available Bandwidth (PAB) [17], Initial Gap Increasing (IGI) [18], Twoway Available Bandwidth Estimation (TWABE) [19], Gaps of Nonadjacent Probing packet (GNAPP) [20], Network Link Characteristics using PacketPair Dispersion (NLCPPD) [21], Feedbackassisted Robust Estimation of Available Bandwidth (bTRack) [22], Adaptive Available BE (AABE) [23], Bandwidth Available in RealTime (BART) [24], MultiRate BART (MRBART) [25], Minimal Backlogging Techniques (MiBT) [26], Distributed Admission Control For MANET Environment (DACME) [27], Reactive Bandwidth Measurement (RBM) [28,29], NeuroFuzzy Estimator (NFE) [30], Dualcarrier Sense with Parallel Transmission Awareness (DCSPT) [31], Packet Probing with RTS/CTS Handshake (PPRCH) [31]. In passive techniques, network statistic data is collected at the router level to infer network performance information from passive observation, which does not disturb the network traffic but waste limited computation and storage resources causing the delay.…”

Section: Bandwidth Estimation Techniquesmentioning

confidence: 99%

Available Bandwidth Estimation Using Collision Probability, Idle Period Synchronization and Random Waiting Time in MANETs: Cognitive Agent Based Approach

Chaudhari

Biradar

2015

Wireless Pers Commun

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In Mobile Ad hoc NETworks (MANETs), each node estimates available bandwidth (AB) before transmission of real-time multimedia data, as the channel is shared. The existing AB estimation techniques lack accuracy and add overhead. Accuracy of these AB estimation techniques could be enhanced by adopting some intelligent techniques. Intelligent software agents such as cognitive agent (CA) have significant potential to solve the challenges of estimating AB in MANETs. Intelligence is provided similar to the logical thinking like human for decision making in CA. The predominant CA architecture is belief desire intention model, which performs the task on behalf of human user as an assistant to him/her. In this paper, we propose CA-based available bandwidth estimation using collision probability, Idle period synchronization and random waiting time (BECIT) in MANETs. The proposed BECIT technique uses CA at each node to create mobile agents for collecting and distributing the statistics (such as idle period, packet loss, and AB, etc.) over the network. The collected network statistics are used by CA to estimate AB using our previous work distributed lagrange interpolation based AB estimation (DLI-ABE). The DLI-ABE comprises of statistical models for idle period synchronization by differentiating their states as BUSY, IDLE, and SENSE BUSY; collision probability using distributed Lagrange Interpolation polynomial; and random waiting time that consumes AB such as request-to-send, clear-to-send commands in IEEE 802.11 standard. Estimation of end-toend AB on a multi-hop path uses each node AB. The simulation results show that BECIT performs approximately 30 % more accurate than the non-agent based AB estimation scheme. Memory overhead is essential to store knowledge base for agents whereas the & Shilpa Shashikant Chaudhari

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Adaptive available bandwidth estimation for internet video streaming

Cited by 6 publications

References 23 publications

Provisioning of medical quality of services for HSDPA and mobile WiMAX in healthcare applications

Provisioning of medical quality of services for HSDPA and mobile WiMAX in healthcare applications

Bandwidth Estimation for Admission Control in MANET: Review and Conceptual MANET Admission Control Framework

Available Bandwidth Estimation Using Collision Probability, Idle Period Synchronization and Random Waiting Time in MANETs: Cognitive Agent Based Approach

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