13,929 research outputs found
Resource dimensioning through buffer sampling
Link dimensioning, i.e., selecting a (minimal) link capacity such that the users’ performance requirements are met, is a crucial component of network design. It requires insight into the interrelationship among the traffic offered (in terms of the mean offered load , but also its fluctuation around the mean, i.e., ‘burstiness’), the envisioned performance level, and the capacity needed. We first derive, for different performance criteria, theoretical dimensioning formulas that estimate the required capacity as a function of the input traffic and the performance target. For the special case of Gaussian input traffic, these formulas reduce to , where directly relates to the performance requirement (as agreed upon in a service level agreement) and reflects the burstiness (at the timescale of interest). We also observe that Gaussianity applies for virtually all realistic scenarios; notably, already for a relatively low aggregation level, the Gaussianity assumption is justified.\ud
As estimating is relatively straightforward, the remaining open issue concerns the estimation of . We argue that particularly if corresponds to small time-scales, it may be inaccurate to estimate it directly from the traffic traces. Therefore, we propose an indirect method that samples the buffer content, estimates the buffer content distribution, and ‘inverts’ this to the variance. We validate the inversion through extensive numerical experiments (using a sizeable collection of traffic traces from various representative locations); the resulting estimate of is then inserted in the dimensioning formula. These experiments show that both the inversion and the dimensioning formula are remarkably accurate
Resource dimensioning through buffer sampling
Link dimensioning, i.e., selecting a (minimal) link capacity such that the users’ performance requirements are met, is a crucial component of network design. It requires insight into the interrelationship between the traffic offered (in terms of the mean offered load M, but also its fluctuation around the mean, i.e., ‘burstiness’), the envisioned performance level, and the capacity needed. We first derive, for different performance criteria, theoretical dimensioning formulae that estimate the required capacity C as a function of the input traffic and the performance target. For the special case of Gaussian input traffic these formulae reduce to C = M+V , where directly relates to the performance requirement (as agreed upon in a service level agreement) and V reflects the burstiness (at the timescale of interest). We also observe that Gaussianity applies for virtually all realistic scenarios; notably, already for a relatively low aggregation level the Gaussianity assumption is justified.\ud
As estimating M is relatively straightforward, the remaining open issue concerns the estimation of V . We argue that, particularly if V corresponds to small time-scales, it may be inaccurate to estimate it directly from the traffic traces. Therefore, we propose an indirect method that samples the buffer content, estimates the buffer content distribution, and ‘inverts’ this to the variance. We validate the inversion through extensive numerical experiments (using a sizeable collection of traffic traces from various representative locations); the resulting estimate of V is then inserted in the dimensioning formula. These experiments show that both the inversion and the dimensioning formula are remarkably accurate
Control-Based Resource Management Procedures for Satellite Networks
This paper describes the resource management of a DVBRCS
geostationary satellite network. The functional modules
of the access layer aim at efficiently exploiting the link
resources while assuring the contracted Quality of Service
(QoS) to the traffic entering the satellite network. The main
novelty is the integration between the Connection Admission
Control and the Congestion Control procedures. Both them
exploit the estimation of the traffic load, performed by a
Kalman filter. The proposed solution has been analysed via
computer simulations, which confirmed their effectiveness
TCP over High Speed Variable Capacity Links: A Simulation Study for Bandwidth Allocation
New optical network technologies provide opportunities for fast, controllable bandwidth management. These technologies can now explicitly provide resources to data paths, creating demand driven bandwidth reservation across networks where an applications bandwidth needs can be meet almost exactly. Dynamic synchronous Transfer Mode (DTM) is a gigabit network technology that provides channels with dynamically adjustable capacity. TCP is a reliable end-to-end transport protocol that adapts its rate to the available capacity. Both TCP and the DTM bandwidth can react to changes in the network load, creating a complex system with inter-dependent feedback mechanisms. The contribution of this work is an assessment of a bandwidth allocation scheme for TCP flows on variable capacity technologies. We have created a simulation environment using ns-2 and our results indicate that the allocation of bandwidth maximises TCP throughput for most flows, thus saving valuable capacity when compared to a scheme such as link over-provisioning. We highlight one situation where the allocation scheme might have some deficiencies against the static reservation of resources, and describe its causes. This type of situation warrants further investigation to understand how the algorithm can be modified to achieve performance similar to that of the fixed bandwidth case
Verifiable Network-Performance Measurements
In the current Internet, there is no clean way for affected parties to react
to poor forwarding performance: when a domain violates its Service Level
Agreement (SLA) with a contractual partner, the partner must resort to ad-hoc
probing-based monitoring to determine the existence and extent of the
violation. Instead, we propose a new, systematic approach to the problem of
forwarding-performance verification. Our mechanism relies on voluntary
reporting, allowing each domain to disclose its loss and delay performance to
its neighbors; it does not disclose any information regarding the participating
domains' topology or routing policies beyond what is already publicly
available. Most importantly, it enables verifiable performance measurements,
i.e., domains cannot abuse it to significantly exaggerate their performance.
Finally, our mechanism is tunable, allowing each participating domain to
determine how many resources to devote to it independently (i.e., without any
inter-domain coordination), exposing a controllable trade-off between
performance-verification quality and resource consumption. Our mechanism comes
at the cost of deploying modest functionality at the participating domains'
border routers; we show that it requires reasonable processing and memory
resources within modern network capabilities.Comment: 14 page
Energy-saving Resource Allocation by Exploiting the Context Information
Improving energy efficiency of wireless systems by exploiting the context
information has received attention recently as the smart phone market keeps
expanding. In this paper, we devise energy-saving resource allocation policy
for multiple base stations serving non-real-time traffic by exploiting three
levels of context information, where the background traffic is assumed to
occupy partial resources. Based on the solution from a total energy
minimization problem with perfect future information,a context-aware BS
sleeping, scheduling and power allocation policy is proposed by estimating the
required future information with three levels of context information.
Simulation results show that our policy provides significant gains over those
without exploiting any context information. Moreover, it is seen that different
levels of context information play different roles in saving energy and
reducing outage in transmission.Comment: To be presented at IEEE PIMRC 2015, Hong Kong. This work was
supported by National Natural Science Foundation of China under Grant
61120106002 and National Basic Research Program of China under Grant
2012CB31600
- …