An algorithm for network and data-aware placement of multi-tier applications in cloud data centers
- Authors: Ferdaus, Md Hasanul , Murshed, Manzur , Calheiros, Rodrigo , Buyya, Rajkumar
- Date: 2017
- Type: Text , Journal article
- Relation: Journal of Network and Computer Applications Vol. 98, no. (2017), p. 65-83
- Full Text: false
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- Description: Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and storage devices to address the ever increasing demand for computing and storage resources, network resource demands are emerging as one of the key areas of performance bottleneck. This paper addresses network-aware placement of virtual components (computing and data) of multi-tier applications in data centers and formally defines the placement as an optimization problem. The simultaneous placement of Virtual Machines and data blocks aims at reducing the network overhead of the data center network infrastructure. A greedy heuristic is proposed for the on-demand application components placement that localizes network traffic in the data center interconnect. Such optimization helps reducing communication overhead in upper layer network switches that will eventually reduce the overall traffic volume across the data center. This, in turn, will help reducing packet transmission delay, increasing network performance, and minimizing the energy consumption of network components. Experimental results demonstrate performance superiority of the proposed algorithm over other approaches where it outperforms the state-of-the-art network-aware application placement algorithm across all performance metrics by reducing the average network cost up to 67% and network usage at core switches up to 84%, as well as increasing the average number of application deployments up to 18%. © 2017 Elsevier Ltd
A hybrid wireless sensor network framework for range-free event localization
- Authors: Iqbal, Anindya , Murshed, Manzur
- Date: 2015
- Type: Text , Journal article
- Relation: Ad Hoc Networks Vol. 27, no. (2015), p. 81-98
- Full Text: false
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- Description: In event localization, wireless sensors try to locate the source of an event from its emitted power. This is more challenging than sensor localization as the power level at the source of an event is neither predictable with precision nor can be controlled. Considering the emerging trend of long sensing range for cost-effective sensor deployment, locating events within a region much smaller than the sensing area of a single sensor has gained research interest. This paper proposes the first range-free event localization framework, which avoids expensive hardware needed by the range-based counterparts. Our approach first develops a sensing range model from the statistical information on the emitted power of a type of events so that user-defined event-detection quality can be provisioned using a minimal network of static sensors. Then an accurate event location boundary estimation technique is developed from the sensing feedbacks, which also facilitates guided expansion of the area of possible event location (APEL) to deal with sensing errors. Finally, user-defined event-localization quality guarantee is provisioned cost-effectively by inviting mobile sensors on-demand to target positions. Analytical solutions are provided whenever appropriate and comprehensive simulations are carried out to evaluate localization performance. The proposed event localization technique outperforms the state-of-the-art range-based counterpart (Xu et al., 2011) in realistic environment with path loss, shadow fading, and sensor positioning errors.
Symbol coding of Laplacian distributed prediction residuals
- Authors: Ali, Mortuza , Murshed, Manzur
- Date: 2015
- Type: Text , Journal article
- Relation: Digital Signal Processing: A Review Journal Vol. 44, no. 1 (2015), p. 76-87
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text: false
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- Description: Predictive coding schemes, proposed in the literature, essentially model the residuals with discrete distributions. However, real-valued residuals can arise in predictive coding, for example, from the usage of an r order linear predictor specified by r real-valued coefficients. In this paper, we propose a symbol-by-symbol coding scheme for the Laplace distribution, which closely models the distribution of real-valued residuals in practice. To efficiently exploit the real-valued predictions at a given precision, the proposed scheme essentially combines the process of residual computation and coding, in contrast to conventional schemes that separate these two processes. In the context of adaptive predictive coding framework, where the source statistics must be learnt from the data, the proposed scheme has the advantage of lower 'model cost' as it involves learning only one parameter. In this paper, we also analyze the proposed parametric coding scheme to establish the relationship between the optimal value of the coding parameter and the scale parameter of the Laplace distribution. Our experimental results demonstrated the compression efficiency and computational simplicity of the proposed scheme in adaptive coding of residuals against the widely used arithmetic coding, Rice-Golomb coding, and the Merhav-Seroussi-Weinberger scheme adopted in JPEG-LS.
- Description: Predictive coding schemes, proposed in the literature, essentially model the residuals with discrete distributions. However, real-valued residuals can arise in predictive coding, for example, from the usage of an r order linear predictor specified by r real-valued coefficients. In this paper, we propose a symbol-by-symbol coding scheme for the Laplace distribution, which closely models the distribution of real-valued residuals in practice. To efficiently exploit the real-valued predictions at a given precision, the proposed scheme essentially combines the process of residual computation and coding, in contrast to conventional schemes that separate these two processes. In the context of adaptive predictive coding framework, where the source statistics must be learnt from the data, the proposed scheme has the advantage of lower 'model cost' as it involves learning only one parameter. In this paper, we also analyze the proposed parametric coding scheme to establish the relationship between the optimal value of the coding parameter and the scale parameter of the Laplace distribution. Our experimental results demonstrated the compression efficiency and computational simplicity of the proposed scheme in adaptive coding of residuals against the widely used arithmetic coding, Rice-Golomb coding, and the Merhav-Seroussi-Weinberger scheme adopted in JPEG-LS. © 2015 Elsevier Inc. All rights reserved.
Analytical modeling of enhanced IEEE 802.11 with multiuser dynamic OFDMA under saturation load
- Authors: Ferdous, Hasan , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: 17th Asia-Pacific Conference on Communications, APCC 2011 p. 524-529
- Full Text: false
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- Description: Multiuser dynamic OFDMA based IEEE 802.11 distributed coordination function (DCF) has received significant interest from the researchers in recent time. Though several proposals have been made, to the best of our knowledge, none of these have presented an analytical model for this kind of medium access control protocols for IEEE 802.11. This paper provides a simple, nevertheless, very accurate analytical model to estimate the performance characteristics of IEEE 802.11 DCF with OFDMA under the assumptions of ideal channel conditions and saturation load. Our model accounts for important system parameters like throughput, collision rate, transmission delay, average contention window size, average retry count and average time wasted in backoff. Analytical results are verified through extensive simulations.
Video coding using arbitrarily shaped block partitions in globally optimal perspective
- Authors: Paul, Manoranjan , Murshed, Manzur
- Date: 2011
- Type: Text , Journal article
- Relation: EURASIP Journal on Advances in Signal Processing Vol. 16, no. (2011), p.
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- Description: Algorithms using content-based patterns to segment moving regions at the macroblock (MB) level have exhibited good potential for improved coding efficiency when embedded into the H.264 standard as an extra mode. The content-based pattern generation (CPG) algorithm provides local optimal result as only one pattern can be optimally generated from a given set of moving regions. But, it failed to provide optimal results for multiple patterns from entire sets. Obviously, a global optimal solution for clustering the set and then generation of multiple patterns enhances the performance farther. But a global optimal solution is not achievable due to the non-polynomial nature of the clustering problem. In this paper, we propose a near-optimal content-based pattern generation (OCPG) algorithm which outperforms the existing approach. Coupling OCPG, generating a set of patterns after clustering the MBs into several disjoint sets, with a direct pattern selection algorithm by allowing all the MBs in multiple pattern modes outperforms the existing pattern-based coding when embedded into the H.264.
Adaptive contention window based wireless medium access mechanism for periodic sensor data collection applications
- Authors: Haque, Ahsanul , Murshed, Manzur , Ali, Mortuza
- Date: 2009
- Type: Text , Conference paper
- Relation: Communications (MICC), 2009 IEEE 9th Malaysia International Conference
- Full Text: false
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- Description: Contention window based medium access protocols are of practical interest in low data rate wireless communication scenarios. In periodic data collection applications, nodes mostly produce small data packets that are collected by the cluster heads and routed to the base station. In this paper, a new mechanism for adaptively selecting the size of the contention window based on the number of contending nodes has been presented. The proposed scheme effectively reduces the number of collisions in periodic collection scenarios with fixed number of nodes. Theoretical analysis and simulation results demonstrate that, in periodic data collection processes, the new protocol reduces the data collection time significantly as compared to IEEE 802.11 and the recently proposed Synchronized Shared Contention Window (SSCW) based scheme.
Prefix coding of integers with real-valued predictions using cosets
- Authors: Ali, Mortuza , Murshed, Manzur
- Date: 2007
- Type: Text , Journal article
- Relation: IEEE Communications Letters, vol. 11, no. 10, IEEE Communications Society, p. 814-816
- Full Text: false
- Description: In predictive coding of integers real-valued residuals are mapped to integers before encoding, leaving room for improvement by reducing the loss due to rounding. In this paper, we propose a new prefix coding scheme where actual integer values, instead of the residuals, are encoded using cosets with real domain predictions as the side information. This novel coding scheme outperforms Golomb-based coding by reducing the rounding loss with similar computational and memory complexity.