Lagrange relaxation based method for the QoS routing problem

Jüttner, Alpár; Szviatovski, B.; Mecs, I.; Rajko, Z.

doi:10.1109/infcom.2001.916277

Cited by 251 publications

(270 citation statements)

References 16 publications

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“…However, looking at the corresponding worst-case formulae (6) and (11) shows that the exception is only a figment due to the overestimate: for (i, j) ∈ A , both schedulers give the same L/w ij latency, which is clearly the minimum possible (a packet needs to be fully received before it can be re-transmitted). Comparing (12) with (14) also shows that, coeteris paribus, the WRP latency is always smaller than or equal to that of FB; this is confirmed by the worst-case versions (11) and (13).…”

Section: System Modelmentioning

confidence: 65%

“…However, as could be expected, CSP with two or more constraints, even additive or multiplicative ones, is already N P-complete [30,20]. Due to the typical strict requirements on the time to deliver the solution in practice (say, some 10s or 100s of milliseconds), it is natural that several efforts have been made to develop approximate approaches for the corresponding CSP (e.g., [15,33,16,13]). As an alternative, stochastic traffic models are used to compute guarantees on average QoS metrics [25].…”

Section: Introductionmentioning

confidence: 99%

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Delay-constrained routing problems: Accurate scheduling models and admission control

Frangioni

Galli

Stea

2017

Computers & Operations Research

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It has been recently shown [7] that the problem of routing a new packet flow in a computer network subject to a constraint on the worst-case end-to-end delay of its packets can be formulated as a Mixed-Integer Second-Order Cone Program (MI-SOCP), and solved with general-purpose tools on instances of realistic size in time compatible with real-time use. However, that result was obtained for only one of the classes of schedulers in use in today's networks, namely Strictly Rate-Proportional ones. Furthermore, that result relies on assuming that each link is "fully loaded", so that the reserved rate of the flow coincides with its guaranteed rate. These assumptions entail both simple latency expressions, and the fact that flows are isolated from each other as far as their end-to-end delay is concerned; that is, admitting a new flow does not increase the end-to-end delay of the existing ones. However, other classes of scheduling algorithms commonly found in current networks both yield more complex latency formulae and do not enforce strict flow independence. Furthermore, the delay actually depends on the guaranteed rate of the flow, which can be significantly larger than the reserved rate if the network is less loaded. In this paper we extend the result to other classes of schedulers and to a more accurate representation of the latency, showing that, despite the increase in complexity, the problem is still efficiently solvable, even when admission control needs to be factored in, for realistic instances, provided that the right modeling choices are made.

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Section: System Modelmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

Delay-constrained routing problems: Accurate scheduling models and admission control

Frangioni

Galli

Stea

2017

Computers & Operations Research

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“…An exact solution to this problem is known to be NP-hard (Jüttner et al, 2001). However, there exist very good heuristics for finding approximate solutions.…”

Section: Path Planningmentioning

confidence: 99%

Persistent ocean monitoring with underwater gliders: Adapting sampling resolution

Smith¹,

Schwager²,

Smith³

et al. 2011

Journal of Field Robotics

182

112

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Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data.More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show improvements in both data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

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“…In this case, all the paths that satisfy the constraint associated with one of the two metrics are computed and then the shortest path according to the second metric is selected. A straightforward method for heuristically solving the general MCP problem is via Metrics Combination (MC) [4,[14][15][16]. By combining a set of QoS metrics in a single metric, it is possible to use existing polynomial-time path computation algorithms, such as Bellman-Ford or Dijkstra.…”

Section: Algorithmic Aspects In Qos Routingmentioning

confidence: 99%

Research challenges in QoS routing

Masip-Bruin¹,

Yannuzzi

Domingo‐Pascual³

et al. 2006

Computer Communications

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Quality of Service Routing is at present an active and remarkable research area, since most emerging network services require specialized Quality of Service (QoS) functionalities that cannot be provided by the current QoS-unaware routing protocols. The provisioning of QoS based network services is in general terms an extremely complex problem, and a significant part of this complexity lies in the routing layer. Indeed, the problem of QoS Routing with multiple additive constraints is known to be NP-hard. Thus, a successful and wide deployment of the most novel network services demands that we thoroughly understand the essence of QoS Routing dynamics, and also that the proposed solutions to this complex problem should be indeed feasible and affordable. This article surveys the most important open issues in terms of QoS Routing, and also briefly presents some of the most compelling proposals and ongoing research efforts done both inside and outside the E-Next Community to address some of those issues. q

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Lagrange relaxation based method for the QoS routing problem

Cited by 251 publications

References 16 publications

Delay-constrained routing problems: Accurate scheduling models and admission control

Delay-constrained routing problems: Accurate scheduling models and admission control

Persistent ocean monitoring with underwater gliders: Adapting sampling resolution

Research challenges in QoS routing

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