1,720,961 research outputs found
Admission control and path allocation for SLAs in DiffServ networks
No full textIn this paper we consider a Differentiated Service domain, in which the domain administrator has to decide whether to accept or to reject service level agreements (SLA) requested by users. After introducing the admission criteria which are used to verify if there are enough resources to satisfy the SLA request, we focus our attention to the problem of the SLA routing, i.e., the selection of paths along which traffic may flow. In particular, we show that the construction of an optimal set of paths is equivalent to the construction of a multicast tree, or a Steiner tree which is known to be an NP-hard problem. We therefore propose a class of simple heuristics, whose performance is assessed by simulations. Results show that it is possible to increase up to 40% the amount of capacity a network provider can reserve to SLA requests without violating the QoS constraints or to reduce the SLA blocking probability by a order of magnitude by using the proposed algorithms
An Analytical Framework for SLA Admission Control in a DiffServ Domain
No full textWe define an analytical approach and a methodology to determine the set of service level agreements (SLA) that can be effectively supported by a DiffServ IP network. We consider the assured forwarding (AF) per hop behavior (PHB), and, based on the SLA probabilistic description, we derive a worst-case mathematical formulation for the overbooking probability, i.e., the probability that the traffic crossing any link of a source-destination path exceeds the link capacity. We then compare analytical results with simulation of different traffic models
Web User-session Inference by Means of Clustering Techniques
Full text linkThis paper focuses on the definition and identification of "Web user-sessions", aggregations of several TCP connections generated by the same source host. The identification of a user-session is non trivial. Traditional approaches rely on threshold based mechanisms. However, these techniques are very sensitive to the value chosen for the threshold, which may be difficult to set correctly. By applying clustering techniques, we define a novel methodology to identify Web user-sessions without requiring an a priori definition of threshold values. We define a clustering based approach, we discuss pros and cons of this approach, and we apply it to real traffic traces. The proposed methodology is applied to artificially generated traces to evaluate its benefits against traditional threshold based approaches. We also analyze the characteristics of user-sessions extracted by the clustering methodology from real traces and study their statistical properties. Web user-sessions tend to be Poisson, but correlation may arise during periods of network/hosts anomalous behavio
Web User Session Characterization via Clustering Techniques
Full text linkWe focus on the identification and definition of "Web user-sessions", an aggregation of several TCP connections generated by the same source host on the basis of TCP connection opening time. The identification of a user session is non trivial; traditional approaches rely on threshold based mechanisms, which are very sensitive to the value assumed for the threshold and may be difficult to correctly set. By applying clustering techniques, we define a novel methodology to identify Web user-sessions without requiring an a priori definition of threshold values. We analyze the characteristics of user sessions extracted from real traces, studying the statistical properties of the identified sessions. From the study it emerges that Web user-sessions tend to be Poisson, but correlation may arise during periods of network/hosts anomalous functioning
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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