The Experts below are selected from a list of 1821 Experts worldwide ranked by ideXlab platform

Kwanwu Chin - One of the best experts on this subject based on the ideXlab platform.

  • power aware routing in networks with delay and Link Utilization constraints
    Local Computer Networks, 2012
    Co-Authors: Gongqi Lin, Sieteng Soh, Mihai Lazarescu, Kwanwu Chin
    Abstract:

    This paper addresses the NP-hard problem of switching off bundled Links whilst retaining the QoS provided to existing applications. We propose a fast heuristic, called Multiple Paths by Shortest Path First (MSPF), and evaluated its performance against two state-of-the-art techniques: GreenTE, and FGH. MSPF improves the energy saving on average by 5% as compared to GreenTE with only 1% CPU time. While yielding equivalent energy savings, MSPF requires only 0.35% of the running time of FGH. Finally, for Maximum Link Utilization (MLU) below 50% and delay no longer than the network diameter, MSPF reduces the power usage of the GEANT topology by up to 91%.

Andrea Baiocchi - One of the best experts on this subject based on the ideXlab platform.

  • routing perturbation for traffic matrix evaluation in a segment routing network
    IEEE Transactions on Network and Service Management, 2018
    Co-Authors: Marco Polverini, Antonio Cianfrani, Marco Listanti, Andrea Baiocchi
    Abstract:

    Traffic matrix (TM) assessment is a key issue for optimizing network management costs and quality of service. This paper presents a method to measure the intensity of ingress–egress traffic flows on an Internet service providers network that overcomes the limits of the classical measurement-based approaches. The proposed algorithm, called segment routing perturbation traffic (SERPENT), uses a routing perturbation approach enabled by the segment routing paradigm: The paths of a subset of flows are changed so that their intensities can be determined measuring the variation of the load of the network Links. The TM is measured in successive steps, called snapshots, in which sets of flows are progressively re-routed and measured, under a Maximum Link Utilization constraint. We state an integer linear programming (ILP) optimization problem to determine the flows to be rerouted in one snapshot. SERPENT is an heuristic offering an efficient solution to the stated ILP. Results show that SERPENT assesses the intensity of more than 80% of flows even when the network is highly stressed, while reducing the configuration cost with respect to classical approaches. Moreover, when used in conjunction with an estimation algorithm, SERPENT allows a reduction of the estimation error by more than 50% with fewer than 5 snapshots.

Gongqi Lin - One of the best experts on this subject based on the ideXlab platform.

  • power aware routing in networks with delay and Link Utilization constraints
    Local Computer Networks, 2012
    Co-Authors: Gongqi Lin, Sieteng Soh, Mihai Lazarescu, Kwanwu Chin
    Abstract:

    This paper addresses the NP-hard problem of switching off bundled Links whilst retaining the QoS provided to existing applications. We propose a fast heuristic, called Multiple Paths by Shortest Path First (MSPF), and evaluated its performance against two state-of-the-art techniques: GreenTE, and FGH. MSPF improves the energy saving on average by 5% as compared to GreenTE with only 1% CPU time. While yielding equivalent energy savings, MSPF requires only 0.35% of the running time of FGH. Finally, for Maximum Link Utilization (MLU) below 50% and delay no longer than the network diameter, MSPF reduces the power usage of the GEANT topology by up to 91%.

Marco Polverini - One of the best experts on this subject based on the ideXlab platform.

  • routing perturbation for traffic matrix evaluation in a segment routing network
    IEEE Transactions on Network and Service Management, 2018
    Co-Authors: Marco Polverini, Antonio Cianfrani, Marco Listanti, Andrea Baiocchi
    Abstract:

    Traffic matrix (TM) assessment is a key issue for optimizing network management costs and quality of service. This paper presents a method to measure the intensity of ingress–egress traffic flows on an Internet service providers network that overcomes the limits of the classical measurement-based approaches. The proposed algorithm, called segment routing perturbation traffic (SERPENT), uses a routing perturbation approach enabled by the segment routing paradigm: The paths of a subset of flows are changed so that their intensities can be determined measuring the variation of the load of the network Links. The TM is measured in successive steps, called snapshots, in which sets of flows are progressively re-routed and measured, under a Maximum Link Utilization constraint. We state an integer linear programming (ILP) optimization problem to determine the flows to be rerouted in one snapshot. SERPENT is an heuristic offering an efficient solution to the stated ILP. Results show that SERPENT assesses the intensity of more than 80% of flows even when the network is highly stressed, while reducing the configuration cost with respect to classical approaches. Moreover, when used in conjunction with an estimation algorithm, SERPENT allows a reduction of the estimation error by more than 50% with fewer than 5 snapshots.

  • incremental deployment of segment routing into an isp network a traffic engineering perspective
    IEEE ACM Transactions on Networking, 2017
    Co-Authors: Antonio Cianfrani, Marco Listanti, Marco Polverini
    Abstract:

    Segment routing (SR) is a new routing paradigm to provide traffic engineering (TE) capabilities in an IP network. The main feature of SR is that no signaling protocols are needed, since extensions of the interior gateway protocol routing protocols are used. Despite the benefit that SR brings, introducing a new technology into an operational network presents many difficulties. In particular, the network operators consider both capital expenditure and performance degradation as drawbacks for the deployment of the new technology; for this reason, an incremental approach is preferred. In this paper, we face the challenge of managing the transition between a pure IP network to a full SR one while optimizing the network performances. We focus our attention on a network scenario where: 1) only a subset of nodes are SR-capable and 2) the TE objective is the minimization of the Maximum Link Utilization. For such a scenario, we propose an architectural solution, named SR domain (SRD), to guarantee the proper interworking between the IP routers and the SR nodes. We propose a mixed integer linear programming formulation to solve the SRD design problem, consisting in identifying the subset of SR nodes; moreover, a strategy to manage the routing inside the SRD is defined. The performance evaluation shows that the hybrid IP/SR network based on SRD offers TE opportunities comparable to the one of a full SR network. Finally, a heuristic method to identify nodes to be inserted in the set of nodes composing the SRD is discussed.

Benjamin Baran - One of the best experts on this subject based on the ideXlab platform.

  • solving multiobjective multicast routing problem with a new ant colony optimization approach
    Proceedings of the 3rd international IFIP ACM Latin American conference on Networking, 2005
    Co-Authors: Diego Pinto, Benjamin Baran
    Abstract:

    This work presents two multiobjective algorithms for Multicast Traffic Engineering. The proposed algorithms are new versions of the Multi-Objective Ant Colony System (MOACS) and the Max-Min Ant System (MMAS), based on Ant Colony Optimization (ACO). Both ACO algorithms simultaneously optimize Maximum Link Utilization and cost of a multicast routing tree, as well as average delay and Maximum end-to-end delay, for the first time using an ACO approach. In this way, a set of optimal solutions, know as Pareto set is calculated in only one run of the algorithms, without a priori restrictions. Experimental results show a promising performance of both proposed algorithms for a multicast traffic engineering optimization, when compared to a recently published Multiobjective Multicast Algorithm (MMA), specially designed for Multiobjective Multicast Routing Problems.

  • multiobjective multicast routing algorithm for traffic engineering
    International Conference on Computer Communications and Networks, 2004
    Co-Authors: Jorge Crichigno, Benjamin Baran
    Abstract:

    This paper presents a new version of a multiobjective multicast routing algorithm (MMA) for traffic-engineering, based on the strength Pareto evolutionary algorithm (SPEA), which simultaneously optimizes the Maximum Link Utilization, the cost of the tree, the Maximum end-to-end delay and the average delay. In this way, a set of optimal solutions, known as Pareto set, is calculated in only one run, without a priori restrictions. Simulation results show that MMA is able to find Pareto optimal solutions. They also show that for dynamic multicast routing, where the traffic requests arrive one after another, MMA outperforms other known algorithms

  • multiobjective multicast routing algorithm
    International Conference on Telecommunications, 2004
    Co-Authors: Jorge Crichigno, Benjamin Baran
    Abstract:

    This paper presents a new multiobjective multicast routing algorithm (MMA) based on the Strength Pareto Evolutionary Algorithm (SPEA), which simultaneously optimizes the cost of the tree, the Maximum end-to-end delay, the average delay and the Maximum Link Utilization. In this way, a set of optimal solutions, known as Pareto set, is calculated in only one run, without a priori restrictions. Simulation results show that MMA is able to find Pareto optimal solutions. They also show that for the constrained end-to-end delay problem in which the traffic demands arrive one by one, MMA outperforms the shortest path algorithm in Maximum Link Utilization and total cost metrics.