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This research focuses on Wireless Sensor Networks (WSNs) and proposes a three-phase approach to achieve energy-efficient routing. The approach consists of node deployment using Voronoi diagrams, clustering, and Cluster Head (CH) selection using energy-efficient game theory, and a routing strategy based on Improved Pelican Optimization (ImPe) segment routing. Random deployment of sensor nodes in WSNs can lead to coverage issues, and hence, in order to address this, Voronoi-based node deployment is employed to ensure uniform and balanced coverage of the monitoring area. An energy-efficient game theory-based approach is used for CH selection by considering the energy levels to select CHs for enhancing network longevity. The proposed routing mechanism utilizes segment routing, which provides deterministic routing paths from CHs to the sink (Base Station). Segment routing eliminates the need for route discovery and maintenance, making it energy-efficient. The ImPe algorithm that works on the characteristics of pelican search agents is employed to choose the optimal segment path for information sharing. The assessment based on delay, network lifetime, packet delivery ratio, residual energy, throughput, communication overhead, and energy utilization acquired the values of 2.57, 98.59, 98.29, 0.98, 238.51, 7.71, and 0.02 respectively.

Low-Earth Orbit Satellite Constellations (LEO-SCs) provide global, high-speed, and low latency Internet access services, which bridges the digital divide in the remote areas. As inter-satellite links are not supported in initial deployment (i.e. the Starlink), the communication between satellites is based on ground stations with radio frequency signals. Due to the rapid movement of satellites, this hybrid topology of LEO-SCs and ground stations is time-varying, which imposes a major challenge to uninterrupted service provisioning and network management. In this paper, we focus on solving two notable problems in such a ground station-assisted LEO-SC topology, i.e., traffic engineering and fast reroute, to guarantee that the packets are forwarded in a balanced and uninterrupted manner. Specifically, we employ segment routing to support the arbitrary path routing in LEO-SCs. To solve the traffic engineering problem, we proposed two source routings with traffic splitting algorithms, Delay-Bounded Traffic Splitting (DBTS) and DBTS+, where DBTS equally splits a flow and DBTS ​+ ​favors shorter paths. Simulation results show that DBTS ​+ ​can achieve about 30% lower maximum satellite load at the cost of about 10% more delay. To guarantee the fast recovery of failures, two fast reroute mechanisms, Loop-Free Alternate (LFA) and LFA+, are studied, where LFA pre-computes an alternate next-hop as a backup while LFA ​+ ​finds a 2-segment backup path. We show that LFA ​+ ​can increase the percentage of protection coverage by about 15%.

Aiming to address the drawbacks in SRv6 technology, such as low network carrying efficiency caused by long packet header and inability to deploy in IPv4 networks, a segment routing technology SRv4 for IPv4 networks is proposed. The format of packets header in SRv4, the format of packet encapsulation of SRv4 in IPv4, the processing instructions and the forwarding process of SRv4 packets are designed. SRv4 is compatible with the IPv4 protocol and existing IPv4 network devices, and can be incrementally deployed in IPv4 networks. Compared to SRv6, SRv4 reduces the SID length by 75%, resulting in higher network carrying efficiency. The SRv4 module is developed in the Linux kernel using XDP technology to verify the feasibility of the SRv4. The function, performance and stability of the SRv4 module were tested using a network environment built in a server computer. The results show that the SRv4 module has the correct segment routing function and can run stably. [ABSTRACT FROM AUTHOR]

One of the critical targets of the fifth generation (5G) mobile network is supporting low latency and high reliable services at the network edge servers. Multiple service instances of the same service can be deployed on different geographically distributed edge sites for high availability purposes. However, the dynamic changes over time in edge servers’ computing capabilities and underlay infrastructure network quality might affect service performance. To avoid service performance degradation, an efficient computing-aware traffic steering (CATS) solution between different service instance locations is required. Multiple advanced traffic steering algorithms have been proposed in different existing 5G traffic steering works. However, no available works addressed the possible 5G architecture and procedure changes to convert these CATS algorithms’ decisions into 5G mobile user plane routing paths. This work aims to cover this research gap. We propose enhancing the current 5G architecture by applying the Mobile User Plane Controller (MUP-C) concept and using anycast address for multi-instance services. We discuss three implementation options to apply these enhancement features to 5G architecture: CATS Application Function (AF) traffic influence method, CATS MUP-C dummy User Plane Function (UPF) method, and CATS MUP-C non-UPF method. We implemented and evaluated the performance of our solutions against a 3GPP standard dynamic edge discovery method, which can also be used to support CATS. The results showed that our solutions had better Protocol Data Unit (PDU) session setup procedure efficiency for CATS than the standard method by reducing the setup latency from 30% to 50%.

This paper proposes a new load-balancing method that supports Per-Connection Consistency (PCC) by leveraging ECMP with standardized routing protocols for operational simplicity. Load balancers must consistently deliver packets of a flow to one of the backend servers, even when the backend server pool changes. Achieving this property—PCC—is not a straightforward task and usually introduces additional complexity into networks, such as special packet forwarding mechanisms, synchronizing states across load balancers, and often complicated orchestration. Our approach, VRF-shadowing, achieves PCC on ECMP of routers without additional control plane systems by exploiting Segment Routing over IPv6 (SRv6). VRF-shadowing employs the daisy-chaining concept, achieving PCC in a stateless manner with a standardized SRv6-based Layer-3 VPN (L3VPN). VRF-shadowing is composed of two components: a minimal new feature for software of SRv6 routers and a new SRv6 End behavior at servers. We implemented the former in a commercial router and the latter in Linux and evaluated VRF-shadowing on an SRv6 L3VPN network built with only standardized routing protocols. The evaluation results demonstrate that VRF-shadowing preserves connections from being disrupted when the ECMP next-hops change. In the most severe scenario, VRF-shadowing reduced the failed HTTP requests rate from 77% to 0.7% compared to traditional ECMP.

Traffic Engineering (TE) enables management of traffic in a manner that optimizes utilization of network resources in an efficient and balanced manner. However, existing TE solutions face issues relating to scalability and complexity. In recent years, Segment Routing (SR) has emerged as a promising source routing paradigm. As one of the most important applications of SR, Segment Routing Traffic Engineering (SR-TE), which enables a headend to steer traffic along specific paths represented as ordered lists of instructions called segment lists, has the capability to overcome the above challenges due to its flexibility and scalability. In this paper, we conduct a comprehensive survey on SR-TE. A thorough review of SR-TE architecture is provided in the first place, reviewing the core components and implementation of SR-TE such as SR Policy, Flexible Algorithm and SR-native algorithm. Strengths of SR-TE are also discussed, as well as its major challenges. Next, we dwell on the recent SR-TE researches on routing optimization with various intents, e.g., optimization on link utilization, throughput, QoE (Quality of Experience) and energy consumption. Afterwards, node management for SR-TE are investigated, including SR node deployment and candidate node selection. Finally, we discuss the existing challenges of current research activities and propose several research directions worth of future exploration.

In this article we introduce a preprocessing technique to solve the Segment Routing Traffic Engineering Problem optimally using significantly fewer computational resources than previously introduced methods. Segment routing is a recently developed interior gateway routing protocol to be used on top of existing protocols that introduces more flexibility in traffic engineering. In practice, segment routing allows to deviate traffic from its original path by specifying a list of intermediate nodes or links, called segments, to visit before going to its destination. The issue we tackle in this article is that the number of segment paths scales exponentially with the maximum number of segments allowed leading to scalability issues in mathematical formulations. This article introduces the notion of dominated segment paths, these are paths that can be eliminated from the solution space when searching for an optimal solution. We propose a dynamic programming algorithm eliminating dominated paths for any number of segments. Numerical results show that respectively 50%, 90%, and 97% of paths are dominated when considering up to 2, 3, and 4 segments on benchmark network topologies. [ABSTRACT FROM AUTHOR]

In order to solve the problems of unreasonable traffic path allocation, elephant flow collision and high overhead of controller flow table in data center networks, this paper proposed an SDN based hybrid segment routing probability flow scheduling mechanism (SRPFS). By taking advantage of SDN s centralized control feature, SRPFS initialized the traffic forwarding method by hybrid segment routing at first. Then, it utilized particle swarm optimization and redefined the internal particles optimization process to filter the traffic. Finally, SRPFS constructed the global node probability matrix and designed probability scheduling algorithm to elect the optimal path for traffic forwarding. Experimental results show that the hybrid segment routing has a greater advantage in terms of flow table overhead. Compare with other classic flow transmission mechanisms, SRPFS has certain advantages in average network throughput, link utilization and standard network throughput rate, it reduces the controller flow-table overhead and ensures better network performance. [ABSTRACT FROM AUTHOR]

As a new network architecture,the software defined network(SDN)simplifies the network management logic by separating data plane and control plane,which is one of the popular research subjects of next-generation network.However,due to frequent link failures and other factors,it is difficult to guarantee the reliability of SDN,which is a problem well recognized in the industry.The existing SDN link failure recovery models often have the problems of long recovery delay,requiring too many flow entries and ignoring link congestion after recovery from failure.To solve these problems,this paper proposes a single-link failure recovery model(LFA-CA)based on segment routing(SR).The model employs the two heuristic algorithms of BPF and BPU to calculate a loop-free backup path during network initialization and update the congestion avoiding backup path during operation,respectively,so as to achieve fast recovery from single-link failure and congestion avoidance after failure.In this paper,massive simulation experiments are carried out to evaluate the performance of our model,and the results prove that compared with some of the existing SDN single-link failure recovery models,LFA-CA consumes less forwarding rules and has better load balancing ability after failure.

Segment routing has been a novel architecture for traffic engineering in recent years. However, segment routing brings control overheads, i.e., additional packets headers should be inserted. The overheads can greatly reduce the forwarding efficiency for a large network, when segment headers become too long. To achieve the best of two targets, we propose the intelligent routing scheme for traffic engineering (IRTE), which can achieve load balancing with limited control overheads. To achieve optimal performance, we first formulate the problem as a mapping problem that maps different flows to key diversion points. Second, we prove the problem is nondeterministic polynomial (NP)-hard by reducing it to a k-dense subgraph problem. To solve this problem, we develop an ant colony optimization algorithm as improved ant colony optimization (IACO), which is widely used in network optimization problems. We also design the load balancing algorithm with diversion routing (LBA-DR), and analyze its theoretical performance. Finally, we evaluate the IRTE in different real-world topologies, and the results show that the IRTE outperforms traditional algorithms, e.g., the maximum bandwidth is 24.6% lower than that of traditional algorithms when evaluating on BellCanada topology.

Satellite networks, which have wide coverage and high throughput, are more and more important for the Internet. Low earth orbit (LEO) satellites have been more widely used than other orbiting satellites because they have lower unidirectional links (UDL) transmission delay. However, due to the variability and instability of satellite links, leading to relatively higher UDL transmission delay and more link failures for satellite networks. Thus, fast reroute (FRR) schemes, which can bypass the failure links and improve network performance, are badly needed in satellite networks. However, FRR need relatively large computing resources while satellites have limited resources. Thus, traditional routing technologies cannot be directly applied to satellite network due to frequent topology changes and poor computing performance. To meet the challenges, we propose a hybrid FRR schemes for satellite networks that combines the centralized computing with distributed segment routing (SR). With the scheme, satellites with relatively more computing resources can pre-compute the reroute paths, and distribute the routing rules to satellites that have more forwarding resources. We formulate the problem, propose a classification algorithm that can distinguish satellites according to their computing and forwarding resources. Additionally, we also propose a real-time backup path maintenance algorithm in the hybrid rerouting scheme. Finally, we conduct comprehensive simulations to evaluate the performance of the proposed algorithms, and the results show that under extreme conditions, the proposed LFR algorithm is 30.9% better than traditional algorithms in storage resource utilization; and the proposed LFA+ algorithm is 74.3% better than traditional algorithms in update time comparison.

Nowadays, ocean networks gradually become increasingly important for communication among network entities such as maritime and sea-crossing users. However, ocean networks are highly dynamic because the communication links are composed of satellite and microwave links, which could be easily influenced by the environment such as local climate. Thus, network transmission in ocean networks faces great challenges, including low reliability and low efficiency. In this paper, we propose a smart ocean network architecture, where we use Software Defined Network (SDN) to perform unified management of the network, and Segment Routing (SR) to control data forwarding paths. In this way, we can control network flows and optimize network routing among diverse network entities in an ocean network. However, many Quality of Service (QoS) guaranteed applications in ocean networks, such as remote control, require lower delay. To guarantee the performance for such applications, we further propose QoS routing algorithms based on Fuzzy-Lagrange for the smart ocean networks architecture, where the optimization objective is to ensure service quality provided to users. According to experimental results, it is proved that, in comparison with the benchmark algorithms, the Fuzzy-Lagrange (FuzLag) algorithm proposed based on link fuzzification and Lagrangian Relaxation can improve the performance by 23% at most.

Introduction: In the future, quantum networks will be an important development direction. Quantum networks should be studied considering quantum's unique physical properties. In quantum networks with limited resources, decoherence will lead to qubits loss, which restricts the time that data qubits can be stored in memory before use. To realize the network function, it is very important to transmit data qubits as quickly as possible. In order to ensure timeliness and make use of entanglement resources as much as possible, this paper proposes a concurrent multipath entanglement routing scheme based on segment routing for quantum hybrid networks. Methods: In this scheme, centralized routing is used to calculate the "segments" of quantum relay path, and distributed routing is used to transmit control messages between the "segments". The "concurrent" mechanism is fully adopted in classical messages passing, path nodes BSM (Bell State Measurement) execution and multipath shunt transmission. Conclusion: This scheme has obvious advantages in multipath concurrent transmission, traffic diversion, reducing transmission time and providing redundancy. [ABSTRACT FROM AUTHOR]

We examine how to provide applications with dedicated bandwidth and guaranteed latency in a programmable mission-critical network. Unlike other SDN approaches such as B4 or SWAN, our system Tuneman optimizes both routes and packet schedules at each node to provide flows with sub-second bandwidth changes. Tuneman uses node-level optimization to compute node schedules in a slotted switch and does dynamic routing using a search procedure with Quality of Service– (QoS) based weights. This allows Tuneman to provide an efficient solution for mission-critical networks that have stringent QoS requirements. We evaluate Tuneman on a telesurgery network using a switch prototype built using FPGAs and also via simulations on India’s Tata Network. For mission-critical networks with multiple QoS levels, Tuneman has comparable or better utilization than SWAN while providing delay bounds guarantees. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the deployment of transmission paths in MANET(mobile ad hoc network) for SDN(software defined network) requires the controller to issue related flow entries for all nodes on the path,thereby causing that the transmission have to wait for a long-term period,a mechanism for quickly issuing forwarding rules,FDSR(fast-deployed-segment-routing),is proposed.The controller will issue data forwarding rules by adding labels corresponding to the forwarding path on the data packets in the way of segmented routing,and when dealing with the max stack depth problem,use label adhesion technology to divide the entire path into multiple label stacks by algorithm,sending to corresponding forwarding nodes that can quickly inte-ract with the controller node to reduce path configuration time.Experiments show that compared with the OpenFlow distribution method,FDSR in SD-MANET (software defined mobile ad hoc network) can reduce path deployment time and flow table overhead,and can effectively deal with the MSD problem of SR and improve the long path deployment speed of the controller.

The number of tunnels configured and state kept in IP/MPLS backbones depends on the number of flows and traffic engineering requirements. Segment routing automates tunnel configuration and reduces state in the network, based on the concept of segments: subpaths of the graph. A flow can be defined using only one segment if the route matches the shortest path computed by the IGP, while this number grows with the need for different subpaths. As a consequence, there is a trade-off between traffic engineering and the number of segments used, which translates to header overhead and state in routers. The challenge then is to have flows sharing as many segments as possible. We advance the state of the art with a two-step bi-objective optimization model to reduce the number of configured segments, considering two traffic engineering requirements, load balancing and latency. Our results show that, as we increase the number of flows in the network, the number of configured segments also increases, and then stabilizes regardless of the number of additional flows. Hence, using a real telecommunication network, we show that we can meet traffic engineering requirements with less than 22% of the total number of states as compared to the usual case of IP/MPLS backbones. [ABSTRACT FROM AUTHOR]

With the rapid growth of fifth-generation (5G), network operators have met with difficulties in ensuring user satisfaction due to diverse service-level agreement (SLA) requirements. Application-aware routing is able to potentially address this issue in implementing differentiated routing policies corresponding to various applications. To facilitate the application-aware routing, software-defined networking (SDN) and segment routing (SR) are potential solutions with programmability property to steer network traffic into appropriate routing paths. However, application-aware SR encounters two main problems, including application identification for encrypted traffic and path identification with human intervention. Therefore, this article proposes a new SDN-based SR mechanism that could help network operators overcome these problems. This approach implements reinforcement learning to adapt to dynamic networks in order to optimize the quality of experience (QoE) that network operators must guarantee. The proposal also considers the application class to implement corresponding routing policies for various applications to meet the stringent SLA requirements. Identifying the applications is sometimes complicated due to encrypted network traffic. Hence, our proposal implements a traffic classification approach to classify encrypted traffic into different kinds of applications. Obtained results under considered conditions illustrate that our proposal outperforms the standard SR mechanism related to QoE and decreases up to 64.39% of overhead compared to several benchmarks. [ABSTRACT FROM AUTHOR]

To solve the problem that existing methods are difficult to achieve efficient deployment and service protection in deterministic network (DetNet), a DetNet service protection architecture based on SRv6 was proposed.By leveraging this architecture, a service-oriented DetNet protection scheme was designed and the share protection policy was formulated.With the aid of backup bandwidth share, the proposed heuristic based on shortest path optimized network resource utilization and delay.The simulation results show that the share protection algorithm achieves better performance than non-share algorithm.

Applications such as virtual reality and online gaming require low delays for acceptable user experience. A key task for over-the-top (OTT) service providers who provide these applications is sending traffic through the networks to minimize delays. OTT traffic is typically generated from multiple data centers which are multi-homed to several network ingresses. However, information about the path characteristics of the underlying network from the ingresses to destinations is not explicitly available to OTT services. These can only be inferred from external probing. In this paper, we combine network tomography with machine learning to minimize delays. We consider this problem in a general setting where traffic sources can choose a set of ingresses through which their traffic enter a black box network. The problem in this setting can be viewed as a reinforcement learning problem with strict linear constraints on a continuous action space. Key technical challenges to solving this problem include the high dimensionality of the problem and handling constraints that are intrinsic to networks. Evaluation results show that our methods achieve up to 60% delay reductions in comparison to standard heuristics. Moreover, the methods we develop can be used in a centralized manner or in a distributed manner by multiple independent agents.

SRv6 is a routing architecture that can provide hybrid cooperation between a centralized network controller and network nodes: IPv6 routers maintain the multi-hop ECMP-aware segments, whereas the controller, responsible for the Traffic Engineering policy, combines them to form a source-routed path through the network. Since the state of the flow is defined at the ingress to the network and then is contained in a specific packet header, called Segment Routing Header (SRH), the importance of such a header itself is vital. Motivated by the increasing success and widespread deployment of such approaches and technologies, this paper introduces the context and discusses some of the issues tied to possible tampering with the Segment Routing Header content. Finally, some details of an experimental testbed aimed at evaluating the above issues are provided. [ABSTRACT FROM AUTHOR]

The emergence of CubeSats as a viable means for realizing satellite networks at low costs has given rise to ubiquitous cyber-physical systems spanning air, ground, and space, in what is being recognized as the Internet of Space Things (IoST). IoST is expected to serve a wide variety of applications ranging from monitoring and reconnaissance to in-space backhauling, i.e., the network architecture must serve a plethora of application scenarios with differing service-level agreement (SLA) requirements over the same physical infrastructure in an end-to-end manner. At the same time, since the different use cases might belong to a variety of different stakeholders, IoST must support multi-tenancy and functional isolation of services. Consequently, a network slicing framework is vital to the success of IoST. To this end, an automatic network slicing framework for space-ground integrated networks is presented in this paper. The proposed framework has been designed to address the dual objectives of route computation and resource allocation with minimal SLA violations. Different from the existing state-of-the-art, the framework presented herein is purpose-built for ultra-dense CubeSat networks, and is fully automated. In other words, the framework is purely SLA-based, and does not require prior information concerning the resource requirements associated with a slice. Other key innovations introduced through this framework include a robust SLA model for slice customization, a novel topology construction mechanism, and a unique segment routing-based online admission control solution. Furthermore, the flexibility and efficacy of the proposed framework have been evaluated through a comprehensive use case driven evaluation scenario. [ABSTRACT FROM AUTHOR]

IPv6-based segment routing (SRv6) is a new technology addressed by IETF in recent years.In draft-ietf-spring-srv6-network-programming,the 128-bit segment identifier (SID) was structured,and how to be processed in one node was described.The SID structure defined by the draft was improved.A field named “network”was defined in the SID to identify different virtual sub-networks.It was also pointed out that the SID list in the segment routing header (SRH) did not carry the “Network”,and only carried the locator,function and argument,which could effectively reduce the requirements of the multi-layer SRv6 segment identifier list requirements on the chip processing capability and reduce the overhead in SRv6 networks.To improve the effective utilization of network bandwidth,and at the same time lay a solid foundation for the use of SRv6 network slicing,and promote the large-scale use of SRv6.

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In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods. [ABSTRACT FROM AUTHOR]

It is still a challenging task to provide satisfactory quality of experience (QoE) to users by traditional routing mechanism in current public Internet for real-time multimedia services with high bandwidth and strict end-to-end latency constraint. Multipath transmission is a promising way to improve the performance of data delivery, due to its advantage in bandwidth aggregation capacity over multiple paths to speed up high volume transfers between endpoints. However, existing multipath transmission has many disadvantages such as the requirements for end-host support (i.e. the necessary multi-homed network setting, and operating system or upper applications updates of user devices), and blindingly pursuing maximum of transmission throughput. Path allocation and end-to-end transmission control are two important factors affecting the quality of multipath transmission. As an emerging network architecture, software-defined networking (SDN) is flexible, manageable, and responsive to rapid changes in traffic requirements. In this paper, we propose a multipath transport scheme based on SDN with segment routing (SR) which can meet the bandwidth and low end-to-end transmission latency requirements of real-time interactive multimedia services. The centralized SDN controller is extended to allocate multiple disjoint paths meeting bandwidth requirement meanwhile balancing the network load. The proprietary multipath media server (MMS) dynamically controls the assignment between subflows and routing paths to reduce the end-to-end transmission latency and thus improve QoE of end-users. To show the feasibility of our approach, we construct an SDN platform using Mininet. Simulation results show that our approach performs better compared to the conventional approaches in terms of traffic balancing and end-to-end transmission delay.

First of all,the main issues in current operator metro network were analyzed,the background of why intelligent metro network and the main technologies of the application were introduced.Then the network deployment plans and service organization plans according to the scale of the metro network and the timeline for introduction of all related technologies were introduced.At last,a stage-by-stage exposition regarding to the fusion mode of communication cloud and intelligent converged metro network during deployment process was presented.Based on a series of analysis,it was pointed out that the construction of intelligent metro network played a very important role in the process of SDN/NFV network reconfiguration and cloud network fusion.It’s of great value to bear existing metro network services synthetically and cope with future services on the collaboration of cloud,network and edge.It’s necessary to accumulate operation experiences continuously in the deployment process.

Segment routing (SR) is a highly implementable approach for traffic engineering (TE) with high flexibility, high scalability, and high stability, which can be established upon existing network infrastructure. Thus, when a network failure occurs, it can leverage the existing rerouting methods, such as rerouting based on Interior Gateway Protocol (IGP) and fast rerouting with loop-free alternates. To better exploit these features, we propose a high-performance and easy-to-deploy method SRUF (Segment Routing under Uncertain Failures). The method is inspired by the Value-at-Risk (VaR) theory in finance. Just as each investment risk is considered in financial investment, SRUF also considers each traffic distribution scheme's risk when forwarding traffic to achieve optimal traffic distribution. Specifically, SRUF takes into account that every link may fail and therefore has inherent robustness and high availability. Also, SRUF considers that a single link failure is a low-probability event; hence it can achieve high performance. We perform experiments on real topologies to validate the flexibility, high-availability, and load balancing of SRUF. The results show that when given an availability requirement, SRUF has greater load balancing performance under uncertain failures and that when given a demand requirement, SRUF can achieve higher availability. [ABSTRACT FROM AUTHOR]

The emergence of Segment Routing (SR) provides a novel routing paradigm that uses a routing technique called source packet routing. In SR architecture, the paths that the packets choose to route on are indicated at the ingress router. Compared with shortest-path-based routing in traditional distributed routing protocols, SR can realize a flexible routing by implementing an arbitrary flow splitting at the ingress router. Despite the advantages of SR, it may be difficult to update the existing IP network to a full SR deployed network, for economical and technical reasons. Updating partial of the traditional IP network to the SR network, thus forming a hybrid SR network, is a preferable choice. For the traffic is dynamically changing in a daily time, in this paper, we propose aWeight Adjustment algorithmWASAR to optimize routing in a dynamic hybrid SR network. WASAR algorithm can be divided into three steps: firstly, representative Traffic Matrices (TMs) and the expected TM are obtained from the historical TMs through ultrascalable spectral clustering algorithm. Secondly, given the network topology, the initial network weight setting and the expected TM, we can realize the link weight optimization and SR node deployment optimization through a Deep Reinforcement Learning (DRL) algorithm. Thirdly, we optimize the flow splitting ratios of SR nodes in a centralized online manner under dynamic traffic demands, in order to improve the network performance. In the evaluation, we exploit historical TMs to test the performance of the obtained routing configuration inWASAR. The extensive experimental results validate that our proposed WASAR algorithm has superior performance in reducingMaximum Link Utilization (MLU) under the dynamic traffic. [ABSTRACT FROM AUTHOR]

Service Function Chaining (SFC) is an emerging paradigm aiming to provide flexible service deployment, lifecycle management, and scaling in a micro-service architecture. SFC is defined as a logically connected list of ordered Service Functions (SFs) that require high availability to maintain user experience. The SFC protection mechanism is one way to ensure high availability, and it is achieved by proactively deploying backup SFs and installing backup paths in the network. Recent studies focused on ensuring the availability of backup SFs, but overlooked SFC unavailability due to network failures. This paper extends our previous work to propose a Hybrid Protection mechanism for SFC (HP-SFC) that divides SFC into segments and combines the merits of local and global failure recovery approaches to define an installation policy for backup paths. A novel labeling technique labels SFs instead of SFC, and they are stacked as per the order of SFs in a particular SFC before being inserted into a packet header for traffic steering through segment routing. The emulation results showed that HP-SFC recovered SFC from failure within 20–25 ms depending on the topology and reduced backup paths' flow entries by at least 8.9% and 64.5% at most. Moreover, the results confirmed that the segmentation approach made HP-SFC less susceptible to changes in network topology than other protection schemes. [ABSTRACT FROM AUTHOR]

In view of the low flow entry utilization rate caused by the current SDN network when dealing with a large number of flows, the slow forwarding response and the current network scheduling algorithms may cause local network congestion and load imbalance, a multi-path scheduling based on segment routing is proposed. Algorithm SRMF. First, the SDN controller sends the initial flow entries according to the network topology links information; then, comprehensively considers the remaining bandwidth of the network links, the packet loss rate and the estimated bandwidth requirements of the flow to calculate the path weight; finally, selects the optimal path according to the path weight and install the segment flow entries to the edge switches. Experimental results show that the segment routing technology has obvious advantages in terms of flow entries overhead compared with general forwarding under multiple network topologies. Compared with Hedera and ECMP, the SRMF algorithm has certain advantages in terms of end-to-end delay and delay jitter, network throughput, and packet loss rate. [ABSTRACT FROM AUTHOR]

Segment Routing over IPv6 (SRv6 in short) is a networking architecture suitable for both IP backbones and datacenters. The research, standardization and implementation of this architecture are actively progressing and SRv6 is already adopted in a number of large scale deployments. Effective solutions for Performance Monitoring (PM) of SRv6 networks are strongly needed and there is a lot of activity in this area. A full blown Performance Monitoring solution needs to include: i) Data Plane (as needed to measure metrics such as packet loss and delay); ii) Control Plane (to send commands to the monitoring entities in the nodes); iii) Management Plane (e.g., to collect the measured metrics). Moreover, Big-Data tools and solutions can be applied inside or above the traditional Management Plane boundaries to store and analyze the collected data. In this article we describe SRv6-PM, a solution for Performance Monitoring of SRv6 networks that deals with all the aspects discussed above. SRv6-PM features a cloud-native architecture that supports: i) the ingestion, processing, storage and visualization of PM data using Big-Data tools; ii) the SDN-based control of network routers to drive the performance monitoring operations. In particular, we focus on Loss Monitoring and consider a solution capable of tracking single packet loss events operating in near-real time (e.g., with a time granularity in the order of 10-20 seconds). SRv6-PM is released as open source. We offer a re-usable and extensible platform that can be automatically deployed in different environments, from a single host to multiple servers on private/public clouds and includes a set of Big-Data tools and the SDN control plane. We also provide a reproducible Data Plane environment for PM experiments in SRv6 networks based on the Mininet emulator. [ABSTRACT FROM AUTHOR]

Cloud architectures achieve scaling through two main functions: (i) load-balancers, which dispatch queries among replicated virtualized application instances, and (ii) autoscalers, which automatically adjust the number of replicated instances to accommodate variations in load patterns. These functions are often provided through centralized load monitoring, incurring operational complexity. This article introduces a unified and centralized-monitoring-free architecture achieving both autoscaling and load-balancing, reducing operational overhead while increasing response time performance. Application instances are virtually ordered in a chain, and new queries are forwarded along this chain until an instance, based on its local load, accepts the query. Autoscaling is triggered by the last application instance, which inspects its average load and infers if its chain is under- or over-provisioned. An analytical model of the system is derived, and proves that the proposed technique can achieve asymptotic zero-wait time with high (and controlable) probability. This result is confirmed by extensive simulations, which highlight close-to-ideal performance in terms of both response time and resource costs. [ABSTRACT FROM AUTHOR]

Segment routing (SR) is a new network paradigm to optimize network performance. Through leveraging source routing, SR is able to achieve more fine-grained control of data flow in the SR domain. However, it is difficult to introduce large-scale full SR network into existing traditional network due to the economic constraints and immature operation technology. Thus, incrementally deploying SR nodes into an existing network is preferred, which forms the hybrid IP/SR scenario. In the hybrid network, with SR enabled devices, the routing path of flow can be dynamically adjusted. Network utility is an important factor to reflect the user's satisfaction with the allocated bandwidth. In this paper, we propose a bandwidth allocation algorithm to maximize network utility in hybrid IP/SR network and thus improve customer's satisfaction. The simulation results show that the bandwidth allocation algorithm proposed is able to improve the utility of network significantly, and the utility of network will increase with the number of SR nodes deployed in the network.

The unprecedented growth of network traffic has brought excessive challenges to network operators. To prevent network congestion, network operators conduct traffic engineering (TE) for their routing optimization. In recent years, segment routing traffic engineering (SRTE) has emerged as one of the promising approaches for its high scalability and low control overheads. However, conventional SRTE approaches in large-scale networks are computationally prohibitive, which may lead to delayed system operations and unsatisfactory service qualities. In this paper, we formulate a bi-objective mixed-integer nonlinear program (BOMINLP) to investigate the trade-off between link utilization and computation time in SRTE. Due to the difficulty in solving the original problem directly, we decompose it into two sequential sub-problems. The first sub-problem is to minimize computation time through node selection, and the second one is to minimize maximum link utilization via flow assignment. To this end, we first employ randomized sampling based on stretch bounding to obtain a reduced solution space and then solve a linear program (LP) using existing software tools for the sub-problems. To evaluate our proposed solution, we employ network topologies and traffic matrices from publicly available datasets. Our simulation results show that our proposed solution can effectively reduce computation time while retaining comparable maximum link utilization as compared with several comparison approaches.