An overview of routing optimization for internet traffic engineering

Wang, Ning; Ho, K.H.; Pavlou, George; Howarth, Michael

doi:10.1109/comst.2008.4483669

Cited by 238 publications

(149 citation statements)

References 108 publications

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“…SDN traffic is measured and analyzed in order to enhance the performance of an operational network at both the traffic and resource levels. Recently, several works are done in routing over the SDNs [1]. Several recent works have exploited the global visibility offered by SDN controllers to distribute traffic across pre-computed paths in optimal and suboptimal manners such as Software-driven wide area network (SWAN) [2] and B4 [3] that the former one uses k-shortest paths for routing across the SDN switches while the latter one presents a greedy heuristic to ensure fairness; however, both of them lack sufficient flexibility and path diversity to handle unexpected situations, i.e., traffic bursts, link failures.…”

Section: Related Workmentioning

confidence: 99%

Joint QoS and Congestion Control Based on Traffic Prediction in SDN

et al. 2017

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Due to the various network requirements of applications, quality of service (QoS)-aware routing plays an important role in the networks. Recently proposed resource allocation algorithms focus on the current traffic matrix, which is not applicable for dynamic networks. In this paper, we exploit an estimation of flow matrix that gives our scheme the ability to sufficiently reduce the total packet loss and simultaneously raise the network throughput. In this way, we mathematically formulate the QoS-aware resource reallocation in software-defined networking (SDN) networks based on the traffic prediction. To solve this optimization problem, two schemes are proposed: (i) exact solution; and (ii) fast suboptimal one. The proposed schemes are compared with the accuracy perspective. Moreover, the impact of prediction on resource reallocation is discussed. In this regard, it is shown that, compared with the conventional scheme, the proposed scheme decreases the packet loss and increases the throughput significantly.

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Section: Related Workmentioning

confidence: 99%

Joint QoS and Congestion Control Based on Traffic Prediction in SDN

et al. 2017

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“…The result of this method is the best route for the transmission of the data stream. [14], [15] 3.3. Adaptively power on or off nodes to provide localized capacity according to user demands When SC nodes get powered off, re-routing might be required, as the given SC node might be used to relay traffic originated from other SC node.…”

Section: Network Optimization By Analyzing Statisticsmentioning

confidence: 99%

Calculation Functions of SDN Controller for Wireless Backhaul Infrastructure

Skulysh¹,

Globa²

2017

AEI

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Rapidly increasing traffic demands set up much higher requirements for data rates in the upcoming 5G mobile networks. The most promising approach for capacity enhancement is optimal reuse of network resources by deploying a large number of small cells. In order to maintain the efficiency and performance of new heterogeneous infrastructure, new approached are required to ensure optimal traffic transmission with high capacity. In this paper, we systematize mathematical methods for SDN-controller optimization. The paper contains all main computational methods ensuring the smooth operation of network applying SDN technology. Proposed approach allows to increase the efficiency of network resources utilization, provide the fault-tolerance of infrastructure and high bandwidth of the transport network.

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“…Protection Routing with Traffic Engineering: Various traffic engineering approaches have been proposed in the past to distribute load across a network [33]. One of the recent proposals attempts to assign link weights such that the load remains balanced even after a failure [34], but it does not ensure forwarding continuity during convergence.…”

Section: Single or Correlated Failuresmentioning

confidence: 99%

Handling Multiple Failures in IP Networks through Localized On-Demand Link State Routing

Robertson

Nelakuditi

2012

IEEE Trans. Netw. Serv. Manage.

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Abstract-It has been observed that transient failures are fairly common in IP backbone networks and there have been several proposals based on local rerouting to provide high network availability despite failures. While most of these proposals are effective in handling single failures, they either cause loops or drop packets in the case of multiple independent failures. To ensure forwarding continuity even with multiple failures, we propose Localized On-demand Link State (LOLS) routing. Under LOLS, each packet carries a blacklist, which is a minimal set of failed links encountered along its path, and the next hop is determined by excluding the blacklisted links. We show that the blacklist can be reset when the packet makes forward progress towards the destination and hence can be encoded in a few bits. Furthermore, blacklist-based forwarding entries at a router can be precomputed for a given set of failures requiring protection. While the LOLS approach is generic, this paper describes how it can be applied to ensure forwarding to all reachable destinations in case of any two link or node failures. Our evaluation of this failure scenario based on various real network topologies reveals that LOLS needs 6 bits in the worst case to convey the blacklist information. We argue that this overhead is acceptable considering that LOLS routing deviates from the optimal path by a small stretch only while routing around failures.

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An overview of routing optimization for internet traffic engineering

Cited by 238 publications

References 108 publications

Joint QoS and Congestion Control Based on Traffic Prediction in SDN

Joint QoS and Congestion Control Based on Traffic Prediction in SDN

Calculation Functions of SDN Controller for Wireless Backhaul Infrastructure

Handling Multiple Failures in IP Networks through Localized On-Demand Link State Routing

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