Analysis of minimal backlogging-based available bandwidth estimation mechanism

Nam, Seung Yeob; Kim, Sunggon; Park, Wonyoung

doi:10.1016/j.comcom.2011.11.011

Cited by 9 publications

(13 citation statements)

References 30 publications

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“…Active probing provides an important degree of freedom, as the shape of the probe traffic can be tailored to the specific purpose. Typical probes are packet pairs, i.e., two packets sent with a defined spacing [50], packet trains, i.e., a sequence of packets sent at a constant rate [43], [45]- [49], [51], [53], or packet chirps that are packet trains with an increasing rate [46], [52]. The variety of probes that are used in practice raises the question of a potentially optimal probe.…”

Section: Measurement-based Estimation Methodsmentioning

confidence: 99%

A Non-Stationary Service Curve Model for Estimation of Cellular Sleep Scheduling

Becker

Fidler

2019

IEEE Trans. on Mobile Comput.

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While steady-state solutions of backlog and delay have been derived for essential wireless systems, the analysis of transient phases still poses significant challenges. Considering the majority of short-lived and interactive flows, transient startup effects, as caused by sleep scheduling in cellular networks, have, however, a substantial impact on the performance. To facilitate reasoning about the transient behavior of systems, this paper contributes a notion of non-stationary service curves. Models of systems with sleep scheduling are derived and transient backlogs and delays are analyzed. Further, measurement methods that estimate the service of an unknown system from observations of selected probe traffic are developed. Fundamental limitations of existing measurement methods are explained by the nonconvexity of the transient service and further difficulties are shown to be due to the super-additivity of network service processes. A novel two-phase probing technique is devised that first determines the shape of a minimal probe and subsequently obtains an accurate estimate of the unknown service. In a comprehensive measurement campaign, the method is used to evaluate the service of cellular networks with sleep scheduling (2G, 3G, and 4G), revealing considerable transient backlog and delay overshoots that persist for long relaxation times.

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Section: Measurement-based Estimation Methodsmentioning

confidence: 99%

A Non-Stationary Service Curve Model for Estimation of Cellular Sleep Scheduling

Becker

Fidler

2019

IEEE Trans. on Mobile Comput.

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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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“…From (18), and the piecewise linear assumption for Pr(Q 0,i ≤ t), we obtain the following relations. The detailed derivation is given in Appendix A.…”

Section: Estimation Of Available Bandwidth Ratio Considering Coarse Rmentioning

confidence: 99%

“…These assumptions might be realized in the future internet environment, where the redesign of router architecture is also considered [38,39]. Many schemes have been proposed to estimate the end-to-end available bandwidth [8][9][10][11][12][13][14][15][16][17][18]. Most of them can be classified into probe gap model (PGM) or packet rate model (PRM) [13], and they usually use a simplified model of single-hop path with fluid cross traffic even for multihop cases [40].…”

Section: Related Workmentioning

confidence: 99%

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Estimation of the available bandwidth ratio of a remote link or path segments

et al. 2013

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Available bandwidth is usually sensitive to network anomalies such as physical link failure, congestion, and DDoS attack. Thus, real-time available bandwidth information can be used to detect network anomalies. Many schemes have been proposed to estimate the end-to-end available bandwidth or end-to-end capacity. However, the problem of estimating the available bandwidth for a specific remote link has not been investigated in detail yet. We propose a new scheme to estimate the available bandwidth ratio of a remote link or remote path segments, a group of consecutive links, without deploying our tool at the remote nodes. The scheme would be helpful in accurately pinpointing anomalous links. Two streams of ICMP timestamp packets are sent to both end nodes of a target link according to a Poisson process, and the available bandwidth ratio for the target link is estimated based on the measured packet delay. Since the proposed scheme needs not incur a short-term congestion, unlike conventional end-to-end available bandwidth estimation mechanisms, the intrusiveness is low and the proposed scheme overcomes the limitation of conventional approaches, inability to probe the links beyond the tight link with the minimum available bandwidth. The performance of the proposed scheme is evaluated by ns-2 simulation.

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Analysis of minimal backlogging-based available bandwidth estimation mechanism

Cited by 9 publications

References 30 publications

A Non-Stationary Service Curve Model for Estimation of Cellular Sleep Scheduling

A Non-Stationary Service Curve Model for Estimation of Cellular Sleep Scheduling

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

Estimation of the available bandwidth ratio of a remote link or path segments

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