Lying Your Way to Better Traffic Engineering

To optimize the flow of traffic in IP networks, operators do traffic engineering (TE), i.e., tune routing-protocol parameters in response to traffic demands. TE in IP networks typically involves configuring static link weights and splitting traffic between the resulting shortest-paths via the Equal-Cost-MultiPath (ECMP) mechanism. Unfortunately, ECMP is a notoriously cumbersome and indirect means for optimizing traffic flow, often leading to poor network performance. Also, obtaining accurate knowledge of traffic demands as the input to TE is elusive, and traffic conditions can be highly variable, further complicating TE. We leverage recently proposed schemes for increasing ECMP's expressiveness via carefully disseminated bogus information ("lies") to design COYOTE, a readily deployable TE scheme for robust and efficient network utilization. COYOTE leverages new algorithmic ideas to configure (static) traffic splitting ratios that are optimized with respect to all (even adversarially chosen) traffic scenarios within the operator's "uncertainty bounds". Our experimental analyses show that COYOTE significantly outperforms today's prevalent TE schemes in a manner that is robust to traffic uncertainty and variation. We discuss experiments with a prototype implementation of COYOTE

Segment Routing: a Comprehensive Survey of Research Activities, Standardization Efforts and Implementation Results

Fixed and mobile telecom operators, enterprise network operators and cloud providers strive to face the challenging demands coming from the evolution of IP networks (e.g. huge bandwidth requirements, integration of billions of devices and millions of services in the cloud). Proposed in the early 2010s, Segment Routing (SR) architecture helps face these challenging demands, and it is currently being adopted and deployed. SR architecture is based on the concept of source routing and has interesting scalability properties, as it dramatically reduces the amount of state information to be configured in the core nodes to support complex services. SR architecture was first implemented with the MPLS dataplane and then, quite recently, with the IPv6 dataplane (SRv6). IPv6 SR architecture (SRv6) has been extended from the simple steering of packets across nodes to a general network programming approach, making it very suitable for use cases such as Service Function Chaining and Network Function Virtualization. In this paper we present a tutorial and a comprehensive survey on SR technology, analyzing standardization efforts, patents, research activities and implementation results. We start with an introduction on the motivations for Segment Routing and an overview of its evolution and standardization. Then, we provide a tutorial on Segment Routing technology, with a focus on the novel SRv6 solution. We discuss the standardization efforts and the patents providing details on the most important documents and mentioning other ongoing activities. We then thoroughly analyze research activities according to a taxonomy. We have identified 8 main categories during our analysis of the current state of play: Monitoring, Traffic Engineering, Failure Recovery, Centrally Controlled Architectures, Path Encoding, Network Programming, Performance Evaluation and Miscellaneous...Comment: SUBMITTED TO IEEE COMMUNICATIONS SURVEYS & TUTORIAL

Dynamic Metric OSPF-Based Routing Protocol for Software Defined Networks

[EN] Routing protocols are needed in networking to find the optimal path to reach the destination. However, networks are changing both their use finality and their technology. Paradigms like Software Defined Networks (SDNs) introduce the possibility and the necessity to improve the routing protocols. In this paper, a modification of the Open Shortest Path First (OSPF) routing protocol is proposed in order to allow the protocol to change the metric calculation dynamically according to the network requirements. Experiments, which compare our proposal against the OSPF protocol, are performed in five different scenarios. In these scenarios, the performance of the multimedia traffic has been increased 33% in terms of bandwidth utilization, 80% of loss rate reduction and delay reduction on VoIP communications.This work has been partially supported by the "Ministerio de Educacion, Cultura y Deporte", through the "Ayudas para contratos predoctorales de Formacion del Profesorado Universitario FPU (Convocatoria 2015)". Grant No. FPU15/06837, by the "Ministerio de Economia y Competitividad", through the "Convocatoria 2014. Proyectos I+D - Programa Estatal de Investigacion Cientifica y Tecnica de Excelencia" in the "Subprograma Estatal de Generacion de Conocimiento", project TIN2014-57991-C3-1-P, through the "Convocatoria 2016 - Proyectos I+D+I - Programa Estatal De Investigacion, Desarrollo e Innovacion Orientada a los retos de la sociedad" (Project TEC2016-76795-C6-4-R) and through the "Convocatoria 2017 - Proyectos I+D+I - Programa Estatal de Investigacion, Desarrollo e Innovacion, convocatoria excelencia" (Project TIN2017-84802-C2-1-P).Rego Mañez, A.; Sendra, S.; Jimenez, JM.; Lloret, J. (2019). Dynamic Metric OSPF-Based Routing Protocol for Software Defined Networks. Cluster Computing. 22(3):705-720. https://doi.org/10.1007/s10586-018-2875-7S705720223Coltun, R., Ferguson, D., Moy, J.: OSPF for IPv6, RFC 5340. https://doi.org/10.17487/rfc5340 , July 2008. https://rfc-editor.org/rfc/rfc5340.txtSoftware-Defined Networking (SDN) Definition. https://www.opennetworking.org/sdn-definition/ . Accessed 15 Dec 2017Jimenez, J.M., Romero, O., Rego, A., Dilendra, A., Lloret, J.: Study of multimedia delivery over software defined networks. Netw. Protoc. Algorithms 7(4), 37–62 (2015). https://doi.org/10.5296/npa.v7i4.8794Egea, S., Rego, A., Carro, B., Sanchez-Esguevillas, A., Lloret, J.: Intelligent IoT traffic classification using novel search strategy for fast based-correlation feature selection in industrial environments. IEEE Internet Things J. 5(3), 1616–1624 (2018). https://doi.org/10.1109/JIOT.2017.2787959Rego, A., Sendra, S., Jimenez, J.M., Lloret J.: OSPF routing protocol performance in software defined networks. In: Fourth International Conference on Software Defined Systems (SDS 2017), 8–11 May 2017, Valencia, Spain, https://doi.org/10.1109/SDS.2017.7939153Sendra, S., Fernández, P.A., Quilez, M.A., Lloret, J.: Study and performance of interior gateway IP routing protocols. Netw. Protoc. Algorithms 2(4), 88–117 (2010). https://doi.org/10.5296/npa.v2i4.547Rakheja, P., Kaour, P., Gupta, A., Sharma, A.: Performance analysis of RIP, OSPF, IGRP and EIGRP routing protocols in a network. Int. J. Comput. Appl. 48(18), 6–11 (2012). https://doi.org/10.5120/7446-0401Sendra, S., Rego, A., Lloret, J., Jimenez, J.M., Romero, O.: Including artificial intelligence in a routing protocol using software defined networks. In: IEEE International Conference on Communications Workshops (ICC Workshops 2017), 21–25 May 2017, Paris, France. https://doi.org/10.1109/ICCW.2017.7962735Barbancho, J., León, C., Molina, J., Barbancho, A., SIR: a new wireless sensor network routing protocol based on artificial intelligence. In: Advanced Web and Network Technologies, and Applications. APWeb 2006. Lecture Notes in Computer Science (LNCS), vol. 3842, pp. 271–275. https://doi.org/10.1007/11610496_35Barbancho, J., León, C., Molina, F.J., Barbancho, A.: Using artificial intelligence in wireless sensor routing protocols. In: Knowledge-Based Intelligent Information and Engineering Systems. (KES 2006). Lecture Notes in Computer Science, vol. 4251, pp. 475–482. Springer, New York. https://doi.org/10.1007/11892960_58Arabshahi, P., Gary, A., Kassabalidis, I., Das, A., Narayanan, S., Sharkawi, M.E., Marks, R.J.: Adaptive routing in wireless communication networks using swarm intelligence. In: AIAA 19th Annual Satellite Communications System Conference, Toulouse, France, April 17, 2001Gunes, M., Sorges, U., Bouazizi I.: ARA-the ant-colony based routing algorithm for MANETs. In: International Conference on Parallel Processing Workshops, Vancouver, BC, Canada, 21–21 Aug 2002. https://doi.org/10.1109/ICPPW.2002.1039715Ducatelle, F., Di Caro, G.A., Gambardella, L.M.: Principles and applications of swarm intelligence for adaptive routing in telecommunications networks. Swarm Intell. 4(3), 173–198 (2010). https://doi.org/10.1007/s11721-010-0040-xRajagopalan, S., Shen, C.: ANSI: a swarm intelligence-based unicast routing protocol for hybrid ad hoc networks. J. Syst. Archit. 52(8–9), 485–504 (2006). https://doi.org/10.1016/j.sysarc.2006.02.006RFC 3561 Ad hoc On-Demand Distance Vector (AODV) Routing, July 2003. https://www.rfc-editor.org/info/rfc3561 . Accessed 08 may 2018Zungeru, A.M., Ang, L., Seng, K.P.: Classical and swarm intelligence based routing protocols for wireless sensor networks: a survey and comparison. J. Netw. Comput. Appl. 35(5), 1508–1536 (2012). https://doi.org/10.1016/j.jnca.2012.03.004Karaboga, D., Okdem, S., Ozturk, C.: Cluster based wireless sensor network routing using artificial bee colony algorithm. Wirel. Netw. 18(7), 847–860 (2012). https://doi.org/10.1007/s11276-012-0438-zGinsberg, L., Litkowski, S., Previdi, S.: IS-IS route preference for extended IP and IPv6 reachability, RFC 7775. https://doi.org/10.17487/rfc7775 , February 2016. https://www.rfc-editor.org/rfc/rfc7775.txtRekhter, Y., Li, T., Hares, S.: A border gateway protocol 4 (BGP-4), RFC 4271. https://doi.org/10.17487/rfc4271 . Jan 2006. https://rfc-editor.org/rfc/rfc4271.txtCaria, M., Das, T., Jukan, A.: Divide and conquer: partitioning OSPF networks with SDN. In: IFIP/IEEE International Symposium on Integrated Network Management (IM 2015), 11–15 May, Ottawa (ON), Canada, 2015. https://doi.org/10.1109/INM.2015.7140324Rothenberg, C.E., Nascimento, M.R., Salvador, M.R., Corrêa, C.N.A., Cunha de Lucena, S., Raszuk, R.: Revisiting routing control platforms with the eyes and muscles of software-defined networking. In: HotSDN ‘12 Proceedings of the first workshop on Hot topics in software defined networks, August 13–17 (2012), Helsinki (Finland), pp. 13–18. https://doi.org/10.1145/2342441.2342445Zhu, M., Cao, J., Pang, D., He, Z., Xu, M.: SDN-based routing for efficient message propagation in VANET, In: Wireless Algorithms, Systems, and Applications (WASA 2015), Lecture Notes in Computer Science, vol. 9204, pp. 788–797. https://doi.org/10.1007/978-3-319-21837-3_77Ye, T., Hema, T.K., Kalyanaraman, S., Vastola, K.S, Yadav S.: Minimizing packet loss by optimizing OSPF weights using online simulation. 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Dynamic Adaptation of Software-defined Networks for IoT Systems: A Search-based Approach

The concept of Internet of Things (IoT) has led to the development of many complex and critical systems such as smart emergency management systems. IoT-enabled applications typically depend on a communication network for transmitting large volumes of data in unpredictable and changing environments. These networks are prone to congestion when there is a burst in demand, e.g., as an emergency situation is unfolding, and therefore rely on configurable software-defined networks (SDN). In this paper, we propose a dynamic adaptive SDN configuration approach for IoT systems. The approach enables resolving congestion in real time while minimizing network utilization, data transmission delays and adaptation costs. Our approach builds on existing work in dynamic adaptive search-based software engineering (SBSE) to reconfigure an SDN while simultaneously ensuring multiple quality of service criteria. We evaluate our approach on an industrial national emergency management system, which is aimed at detecting disasters and emergencies, and facilitating recovery and rescue operations by providing first responders with a reliable communication infrastructure. Our results indicate that (1) our approach is able to efficiently and effectively adapt an SDN to dynamically resolve congestion, and (2) compared to two baseline data forwarding algorithms that are static and non-adaptive, our approach increases data transmission rate by a factor of at least 3 and decreases data loss by at least 70%

Simulative Analysis with QRED to Decrease Packet Loss

Communication networks are facing packet loss at routers, where different approaches are used to reduce. Similarly RED is one of them, that existing RED [1] [2] algorithm and its variants are found in flow controlling. For minimizing dropping of packets and reducing buffer overflow. This paper propose a new routing algorithm in which additional FIFO controlled queue buffer before existing RED algorithm, to increases performance and throughput of the router. It is experimented and improvements in results are shown with help of OMNet++

R2L: Routing With Reinforcement Learning

In a packet network, the routes taken by traffic can be determined according to predefined objectives. Assuming that the network conditions remain static and the defined objectives do not change, mathematical tools such as linear programming could be used to solve this routing problem. However, networks can be dynamic or the routing requirements may change. In that context, Reinforcement Learning (RL), which can learn to adapt in dynamic conditions and offers flexibility of behavior through the reward function, presents as a suitable tool to find good routing strategies. In this work, we train an RL agent, which we call R2L, to address the routing problem. The policy function used in R2L is a neural network and we use an evolution strategy algorithm to determine its weights and biases. We tested R2L in two different scenarios: static and dynamic networks conditions. In the first, we used a 16-node network and experimented with different reward functions, observing that R2L was able to adapt its routing behavior accordingly. Finally, in the second experiment, we used a 5-node network topology where a given link's transmission rate changed during the simulation. In this scenario, we observed that R2L was able to deliver a competitive performance, compared to heuristic benchmarks, with changing network conditions