On resource management and QoS guarantees for long range dependent traffic

Adas, A.; Mukherjee, Amarnath

doi:10.1109/infcom.1995.515947

Cited by 74 publications

(52 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It should be noted that the idea is not only to show the application of this view, but also to present results that dissent from it. The self-similar or fractal behavior of traffic in WAN networks is shown in [14]- [16], pointing out the failure of Poisson models to represent the strong correlations that exist at different temporal scales. Evidence and conclusions on this behavior in traffic due to the WWW are provided in [17]- [19], considering interconnection scenarios as well as traffic patterns in browsers.…”

Section: Bibliographic Discussionmentioning

confidence: 99%

“…It also presents an analysis of traffic traces which shows the statistically self-similar nature of the traffic due to WWW and to the VBR video over these types of networks. In [30] develops a new model for traffic in wireless networks that has its origin in the alternating fractal renewal processes (AFRP) proposed as traffic models in [14], and in the wide band network traffic model using the extended alternating fractal renewal processes (EAFRP) proposed in [31]. With the incorporation of a limiting rate for alternation between the two states, called extended limiting rate, the Rate-Limited EAFRP model is formulated, which assumes an advance with respect to the wireline models used traditionally for model traffic in wireless networks, since it takes care of its two main deficiencies: omission of the effects of the LRD temporal correlations, and inability to make reliable performance forecasts due to the high dependence on short-range processes.…”

Section: Bibliographic Discussionmentioning

confidence: 99%

“…In both cases the performance of the system is compared with computer simulations that consider real time traffic with long-range dependence that is manifested trough a polynomial type decay of the self-correlation function. To model the traffic generated by the many terminals within the WLAN, recourse is made to the On/Off methodology presented in [14], supporting its foundations on [37]. Finally, in the same context, Discussion of the Analysis of Self-similar Teletraffic with Long-range Dependence (LRD) at the Network Layer Level 803 but in another field of application, [38] deals with the use of fractal geometry in the antenna design process, while in [39] a general synthesis methodology is proposed that covers the efficient design of fractal antennas and their WiMAX applications.…”

Section: Bibliographic Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Discussion of the Analysis of Self-similar Teletraffic with Long-range Dependence (LRD) at the Network Layer Level

Millán

Kaschel

Lefranc

2010

INT J COMPUT COMMUN

View full text Add to dashboard Cite

Traffic streams, sources as well as aggregated traffic flows, often exhibit long-range-dependent (LRD) properties. This paper presents the theoretical foundations to justify that the behavior of traffic in a high-speed computer network can be modeled from a self-similar perspective by limiting its scope of analysis to the network layer, since the most relevant properties of self-similar processes are consistent for use in the formulation of traffic models when performing this specific task.

show abstract

Section: Bibliographic Discussionmentioning

confidence: 99%

Section: Bibliographic Discussionmentioning

confidence: 99%

Section: Bibliographic Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Discussion of the Analysis of Self-similar Teletraffic with Long-range Dependence (LRD) at the Network Layer Level

Millán

Kaschel

Lefranc

2010

INT J COMPUT COMMUN

View full text Add to dashboard Cite

show abstract

“…Recently, the presence of burstiness has also been identified in a variety of settings, including enterprise systems [2], [16], grids [1], storage systems [17], [18] and file systems [19]. The impact of burstiness on system performance has been examined and reported in [20], [21], [2].…”

Section: Related Workmentioning

confidence: 99%

ArA: Adaptive resource allocation for cloud computing environments under bursty workloads

Tai

Zhang

et al. 2011

30th IEEE International Performance Computing and Communications Conference

View full text Add to dashboard Cite

Abstract-Cloud computing nowadays becomes quite popular among a community of cloud users by offering a variety of resources. However, burstiness in user demands often dramatically degrades the application performance. In order to satisfy peak user demands and meet Service Level Agreement (SLA), efficient resource allocation schemes are highly demanded in the cloud. However, we find that conventional load balancers unfortunately neglect cases of bursty arrivals and thus experience significant performance degradation. Motivated by this problem, we propose new burstiness-aware algorithms to balance bursty workloads across all computing sites, and thus to improve overall system performance. We present a smart load balancer, which leverages the knowledge of burstiness to predict the changes in user demands and on-the-fly shifts between the schemes that are "greedy" (i.e., always select the best site) and "random" (i.e., randomly select one) based on the predicted information. Both simulation and real experimental results show that this new load balancer can adapt quickly to the changes in user demands and thus improve performance by making a smart site selection for cloud users under both bursty and non-bursty workloads.

show abstract

“…Traffic measurements obtained from packet networks have convincingly established the existence of statistical features that are characteristic of fractal traffic processes (Adas and Mukherjee, 1995;Erramilli et al, 1996;Jeong, 2002), particularly in the sense that these features regularly span many time scales, see Erramilli et al (1994) and Taqqu ଁ The synthetic LRD sequences generated using the Spline method are given in the supplementary material.…”

Section: Introductionmentioning

confidence: 99%

Two approximation methods to synthesize the power spectrum of fractional Gaussian noise

Ledesma

Liu

Hernández

2007

Computational Statistics & Data Analysis

View full text Add to dashboard Cite

The simplest models with long-range dependence (LRD) are self-similar processes. Self-similar processes have been formally considered for modeling packet traffic in communication networks. The fractional Gaussian noise (FGN) is a proper example of exactly self-similar processes. Several numeric approximation methods are considered and reviewed, two methods are found that are able to provide a better accuracy and less running time than previous approximation methods for synthesizing the power spectrum of FGN. The first method is based on a second-order approximation. It is demonstrated that a parabolic curve can be indirectly used to approximate the power spectrum of FGN. The second method is based on cubic splines. Despite the fact that splines cannot be used directly to approximate the power spectrum of FGN, they can, however, considerably simplify the calculations while maintaining high accuracy. Both of the methods proposed can be used to estimate the Hurst parameter using Whittle's estimator. Additionally, they can be used on synthesis of LRD sequences.

show abstract

On resource management and QoS guarantees for long range dependent traffic

Cited by 74 publications

References 13 publications

Discussion of the Analysis of Self-similar Teletraffic with Long-range Dependence (LRD) at the Network Layer Level

Discussion of the Analysis of Self-similar Teletraffic with Long-range Dependence (LRD) at the Network Layer Level

ArA: Adaptive resource allocation for cloud computing environments under bursty workloads

Two approximation methods to synthesize the power spectrum of fractional Gaussian noise

Contact Info

Product

Resources

About