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Joint Optimization of Rule Placement and Traffic Engineering for QoS Provisioning in Software Defined Network
Abstract and Figures
Software-Defined Network (SDN) is a promising network paradigm that separates the control plane and data plane in the network. It has shown great advantages in simplifying network management such that new functions can be easily supported without physical access to the network switches. However, Ternary Content Addressable Memory (TCAM), as a critical hardware storing rules for high-speed packet processing in SDN-enabled devices, can be supplied to each device with very limited quantity because it is expensive and energy-consuming. To efficiently use TCAM resources, we propose a rule multiplexing scheme, in which the same set of rules deployed on each node apply to the whole flow of a session going through but towards different paths. Based on this scheme, we study the rule placement problem with the objective of minimizing rule space occupation for multiple unicast sessions under QoS constraints. We formulate the optimization problem jointly considering routing engineering and rule placement under both existing and our rule multiplexing schemes. Via an extensive review of the state-of-the-art work, to the best of our knowledge, we are the first to study the non-routing-rule placement problem. Finally, extensive simulations are conducted to show that our proposals significantly outperform existing solutions.
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... The controller converts the policies for traffic management in the form of flow rules and builds them on network devices [13,26]. Every device on the network keeps its flow rule in its Ternary Content Addressable Memory (TCAM) [6]. However, TCAM is considered expensive due to its definite size and has a high power consumption. ...
... In this section, we discussed the related work of various researchers where they have proposed different schemes to improve QoS in the SDN network. We classify the work from various points-QoS aware routing [9,10,23,38], policy management framework [2,3,24,30,32,33,39] and resource allocation [1,6,22,37]. In the QoS-aware routing, network congestion is detected and various measures are taken to reduce congestion. ...
... The proposed scheme uses the flow matrix for rescheduling the traffic flows in the SDN paradigm which resulted in reducing the congestion in the network. The authors in Huang et al. [6], introduced a rule multiplexing method that efficiently utilizes TCAM resources. However, the authors proposed approach only minimizes the rule placement in switches. ...
Growth in multimedia traffic over the Internet increases congestion in the network architecture. Software-Defined Networking (SDN) is a novel paradigm that solves the congestion problem and allows the network to be dynamic, intelligent, and it centrally controls the network devices. SDN has many advantages in comparison to traditional networks, such as separation of forwarding and control plane from devices, global centralized control, management of network traffic. We design a policy-based framework to enhance the Quality of Service (QoS) of multimedia traffic flows in a potential SDN environment. We phrase a max-flow-min-cost routing problem to determine the routing paths and presented a heuristic method to route the traffic flows in the network in polynomial time. The framework monitors the QoS parameters of traffic flows and identifies policy violations due to link congestion in the network. The introduced approach dynamically implements policy rules to SDN switches upon detection of policy violations and reroutes the traffic flows. The results illustrate that the framework achieves a reduction in end-to-end delay, average jitter, and QoS violated flows by 24%, 37%, and 25%, respectively, as compared to the Delay Minimization method. Furthermore, the proposed approach has achieved better results when compared to SDN without policy-based framework and reduced end-to-end delay, average jitter, and QoS violated flows by 51%, 62%, and 28%, respectively.
... However, the relaxation of the routing policy causes the drawback of longer paths. The researches presented in Huang et al. (2015) and Kosugiyama et al. (2017) propose heuristic algorithms to reduce the total number of flows while respecting the end-to-end QoS. Ashraf (2016) and Galan-Jimenez, Polverini & Cianfrani (2018) focus on minimizing the number of update messages through smart rule aggregation. ...
... Some of the approaches are not capable of handling wildcard or non-prefix addresses (Braun & Menth, 2014b;Rifai et al., 2017;Assefa & Özkasap, 2019). Finally, most of the proposed routing methods do not consider rule conflict issues in aggregation (Huang et al., 2015;Kosugiyama et al., 2017;Bera, Misra & Jamalipour, 2019;Zhao et al., 2020). ...
Software-defined networking (SDN) enables fast service innovations through network programmability. In SDN, a logically centralized controller compiles a set of policies into the network-level rules. These rules are inserted in the TCAM memory of SDN-enabled switches enabling high-speed matching and forwarding of packets. Unfortunately, TCAMs are available in limited capacities and fall short of accommodating all intended rules, especially in networks with large distinct flows like datacenters. Rule compression is a technique that reduces the number of rules by aggregating them with some similarity factors. This paper introduces WildMinnie, a new rule compression method that aggregates rules based on their common address non-prefix wildcards derived from a group of rules with the same output port number. We explore rule conflict issues and provide solutions to resolve them. We demonstrate the capability of WildMinnie in various datacenter topologies with traffics having different diversity of source-destination addresses and show that WildMinnie outperforms the best-known compression method by 20%, on average.
... Therefore, the load of flow tables in different nodes is balanced. Huang et al. [13] proposed a rule multiplexing scheme. The sub-rules are placed along the path in an arbitrary order, and only one duplicate of the same rule is reserved in the common nodes of different paths. ...
... The sub-rules are placed along the path in an arbitrary order, and only one duplicate of the same rule is reserved in the common nodes of different paths. Based on rule multiplexing, Huang et al. [13] formulates a joint optimization problem of rule placement and TE to minimize rule space occupation. In some cases, the rules or sub-rules may be coupled with the nodes with specific functions, which adds constraint conditions to the problem. ...
In emerging scenarios such as the Internet of Things and space-and-ground integrated networks, diverse new applications bring multi-di-mensional quality of service (QoS) requirements to space information networks (SINs). As a mixed problem of routing, traffic control, and resource allocation, QoS provisioning is concentrated on providing customized QoS guarantee to SIN users. On the other hand, motivated by the recent progress in technologies such as software-defined networking and machine learning, many potential solutions for QoS provisioning have been proposed. To utilize the state-of-the-art approaches within QoS provisioning, we provide a forward-looking vision of QoS provisioning that outlines the applications, challenges, architectures, and associated solutions. In this article, we first introduce the applications in three emerging scenarios in terms of traffic characteristics and QoS requirements and identify the accompanying technical challenges for SINs. Then a QoS provisioning architecture with two differentiated transmission modes is proposed. The mirror source mode for bandwidth-tolerant flows improves the network efficiency by centralized traffic scheduling. The preemptive mode for bandwidth-sensitive flows reduces the end-to-end delay by edge node control. Furthermore, the enabling technologies and potential solutions for control logic and forwarding mechanism are analyzed. At last, future research directions are discussed.
... In [34], [35] recommended an SD-DCN related data centre EO with united contemplation of VM Placement (VMP) together with forwarding rule placement. SDN's inherent TCAM ability limitation feature was regarded particularly. ...
The concept of Software-Defined Networking (SDN) has been a fascinating and growing interest in the field of research. The programmable network component is allowed by the SDN’s promising characteristics and partitions the control plane together with the forwarding plane. Energy Efficiency (EE) turned out to be a vital design requisite for modern networking mechanisms since the energy costs supply hugely to the entire costs in networks. Nevertheless, as it is necessary to handle the trade-off betwixt EE and Network Performance (NP), designing energy-effective solutions is non-trivial. Thus, by utilizing Energy-Aware Routing (EAR) approaches, this paper reviews the methodologies of Energy Consumption (EC) on SDN. The latest research related to the traffic-aware solution, compacting TCAM solution, end-host aware solutions, rule placement solutions, heuristic approach-centric solution, and EAR routing protocol was highlighted by this review article in terms of optimal EC on SDN. Finally, centered on the EC metrics, the current research methodologies’ performance is assessed in the performance evaluation. By utilizing EAR routing, this type of research is helpful for future research in efficient EC in SDN.
... The authors in [18] suggested a method based on multiplexing, in which some of the rules can be customized for every node and hence the placement process is done for various paths in an optimized manner. By using the set of rules, occupational space is reduced providing better QoS in both unicast and multicast functions. ...
Software Defined Networking (SDN) is a smart architecture which enables a network to be controlled in a centralized manner. It plays a vital role in several real-time applications and has three planes- the data plane, control plane and application plane. The architecture of SDN is simple and is inbuilt with a centralized controller at the control plane. SDN operates efficiently on Mobile Adhoc NETworks (MANET) in various environments and applications. Due to the mobility of nodes, several research issues are faced by SDN-MANET. Some of the challenges include a large overhead and less packet delivery ratio. To overcome these challenges, a Hybrid Improved Whale optimization with Particle Swarm Optimization algorithm (HIW-PSO) is proposed with Directed Acyclic Graphs (DAG) topology. This algorithm enhances the data transmission by reducing the energy hole issue. The Directed Acyclic Graphs (DAG) topology is constructed by calculating the polynomial-time for lining of all participant nodes through its edges. The proposed algorithm is evaluated for packet delivery ratio, throughput, delay, network lifetime and energy consumption. Furthermore, the performance of HIW-PSO is evaluated against other standard contemporary optimization algorithms EHO and M-LWO. As a result, the proposed method achieves an energy consumption of 35.8%, PDR of 53.2 %, a throughput of 84.8%, network lifetime of 75.4% and delay of 23.8%.
Quality of service provisioning in modern networks requires traffic to be classified as quickly as possible according to its requirements and service type. However, traffic classification (TC) becomes increasingly challenging as traffic encryption evolves. The Encrypted ClientHello (ECH) amendment to the most widespread encryption protocol, Transport Layer Security (TLS), conceals the most sensitive metadata of the TLS-encrypted flows including the Server Name Indication (SNI), which provides ground-truth early TC. Nevertheless, the backward compatibility and protocol limitations leave some non-random TLS metadata open. This paper designs a new early traffic classifier called hybrid Random Forest Traffic Classifier (hRFTC) that utilizes unencrypted TLS metadata together with the statistical features of the traffic flows extracted before the arrival of any application data from the server side. The paper collects an up-to-date diversified traffic dataset in various countries of North America, Europe, and Asia, which is available online and is one of the largest, most detailed, and diversified open-source TC datasets. The paper evaluates the performance of the state-of-the-art TC algorithms on the collected dataset. The results reveal that unencrypted in ECH scenario TLS settings are similar for many multimedia services. Consequently, the TC algorithms that rely solely on the TLS features achieve as low as 38.4% classification F-score. Meanwhile, the hybrid approach of the hRFTC dramatically enhances the TC efficacy. hRFTC achieves up to a 94.6% F-score on the collected dataset, which is superior to the best state-of-the-art algorithms.
After the global financial crisis in 2008, IBM introduced the notion of smart earth for the first time, which aims to fully utilize the new generation of information and communication technologies in the sustainable development of the earth. The concept of smart city comes from smart earth, which refers to utilizing information and communication technology (ICT) to improve the quality and performance of urban services, such as energy, transportation and public utilities, reducing resource consumption, waste and overall cost. With the rapid evolution of network communication technologies, networks are of paramount importance to provide ubiquitous connectivity for lots of critical applications in daily life. In recent years, the wireless broadcast system has gained wide attention, and it has been applied in many fields, such as entertainment services, environmental monitoring and military surveillance. However, individual privacy is one of the serious challenges in smart industrial applications since a large amount of confidential information (e.g., credit card information, physiological information for e-health) is transferred over the open wireless channels. In this chapter, we use three parts to introduce the ground network security, including mobile communication network security, Internet of Things security and Internet of Vehicles security.
Traditional routing schemes usually use fixed models for routing policies and thus are not good at handling complicated and dynamic traffic, leading to performance degradation (e.g., poor quality of service). Emerging Deep Reinforcement Learning (DRL) coupled with Software-Defined Networking (SDN) provides new opportunities to improve network performance with automatic traffic analysis and policy generation. However, existing DRL-based routing solutions usually rely on all node information to make routing decisions for the network and hence are both hard to converge in large networks and vulnerable to topology changes. In this paper, we propose ScaleDeep, a scalable DRL-based routing scheme for SDN, which improves the routing performance and is resilient to topology changes. Essentially, ScaleDeep takes advantage of partial control on network nodes and DRL. We select a set of critical nodes from a network as driver nodes, which can simulate the entire network operation, based on the control theory. By observing the traffic variation on the driver nodes, DRL dynamically adjusts some link weights for a weighted shortest path algorithm to change the routing paths and improve the routing performance. Limiting the control on driver nodes improves the convergence ability of DRL and reduces the dependency of the DRL agent on the fixed network topology. To validate the performance of ScaleDeep, we conduct packet-level simulations on different topologies. The results show that ScaleDeep outperforms existing DRL-based schemes by reducing the average flow completion time by up to 36% and exhibiting better robustness against minor topology changes.
Software-defined IoT (SDIoT) is a promising approach to address the requirements of the Internet of Things (IoT), such as network management, Quality of Service (QoS), and resource utilization. The advantages of SDIoT are facilitated by the separation of the data- and the control-planes using
flow-rules
, that allow fine-grained control over individual flows. However, the number of flow-rules that can be placed at the switches is limited, leading to scalability issues in SDIoT. Existing approaches to flow-rule management either do not consider the impact on QoS or are applicable only to a particular topology. In this article, we propose a QoS-aware flow-rule aggregation scheme for generic network topologies, which aims to achieve a satisfactory tradeoff among flow-rule compression and its impact on the QoS of IoT traffic flows. Specifically, the proposed scheme adaptively aggregates flow-rules while considering different QoS requirements of IoT applications in the network, and the flow-rule capacity of the switches. The proposed scheme consists of the following components—1) a path selection heuristic to increase the total number of flow-rules that can be accommodated in the network and 2) a multiarm bandit-based flow-rule aggregation scheme capable of reducing the number of flow-rules, while maintaining adequate performance in terms of QoS. Experimental results using IoT traffic show that, on average, the proposed scheme is capable of reducing the average end-to-end delay and QoS-violated flows in the network by 22% and 30%, respectively, compared to the state-of-the-art schemes.
Service provisioning has been widely regarded as a critical issue to quality-of-service (QoS) of cloud services in datacenters. Conventional studies on service provisioning mainly focus on task mapping, i.e., how to distribute the service-oriented tasks onto the servers to achieve different goals, e.g., makespan minimization. In distributed datacenters, a task is usually routed from its generation point (i.e., control room) to the designated server within a datacenter network. Since the routing delay also has a deep influence on the task makespan, we are motivated to study how to minimize the maximum makespan of all tasks in a duty period by joint optimization of both task mapping and routing. It is formulated as an integer programming with quadratic constraints (IPQC) problem and proved as NP-hard. To tackle the computational complexity of solving IPQC, a heuristic algorithm with polynomial time is proposed. Extensive simulation results show that it performs close to the optimal one and outperforms existing algorithms significantly.
Software-Defined Networking (SDN) enables fine-grained policies for firewalls, load balancers, routers, traffic monitoring, and other functionality. While Ternary Content Addressable Memory (TCAM) enables OpenFlow switches to process packets at high speed based on multiple header fields, today's commodity switches support just thousands to tens of thousands of rules. To realize the potential of SDN on this hardware, we need efficient ways to support the abstraction of a switch with arbitrarily large rule tables. To do so, we define a hardware-software hybrid switch design that relies on rule caching to provide large rule tables at low cost. Unlike traditional caching solutions, we neither cache individual rules (to respect rule dependencies) nor compress rules (to preserve the per-rule traffic counts). Instead we ``splice'' long dependency chains to cache smaller groups of rules while preserving the semantics of the network policy. Our design satisfies four core criteria: (1) elasticity (combining the best of hardware and software switches), (2) transparency (faithfully supporting native OpenFlow semantics, including traffic counters), (3) fine-grained rule caching (placing popular rules in the TCAM, despite dependencies on less-popular rules), and (4) adaptability (to enable incremental changes to the rule caching as the policy changes).
We present Dionysus, a system for fast, consistent network updates in software-defined networks. Dionysus encodes as a graph the consistency-related dependencies among updates at individual switches, and it then dynamically schedules these updates based on runtime differences in the update speeds of different switches. This dynamic scheduling is the key to its speed; prior update methods are slow because they pre-determine a schedule, which does not adapt to runtime conditions. Testbed experiments and data-driven simulations show that Dionysus improves the median update speed by 53--88% in both wide area and data center networks compared to prior methods.
The fundamental feature of an OpenFlow network is that the controller is responsible for the initial establishment of every flow by contacting related switches. Thus the performance of the controller could be a bottleneck. This paper shows how this fundamental problem is addressed by parallelism. The state of the art OpenFlow controller, called NOX, achieves a simple programming model for control function development by having a single-threaded event-loop. Yet NOX has not considered exploiting parallelism. We propose Maestro which keeps the simple programming model for programmers, and exploits parallelism in every corner together with additional throughput optimization techniques. We experimentally show that the throughput of Maestro can achieve near linear scala-bility on an eight core server machine.
Software Defined Networks (SDNs) support diverse network policies by offering direct, network-wide control over how switches handle traffic. Unfortunately, many controller platforms force applications to grapple simultaneously with end-to-end connectivity constraints, routing policy, switch memory limits, and the hop-by-hop interactions between forwarding rules. We believe solutions to this complex problem should be factored in to three distinct parts: (1) high-level SDN applications should define their end-point connectivity policy on top of a "one big switch" abstraction; (2) a mid-level SDN infrastructure layer should decide on the hop-by-hop routing policy; and (3) a compiler should synthesize an effective set of forwarding rules that obey the user-defined policies and adhere to the resource constraints of the underlying hardware. In this paper, we define and implement our proposed architecture, present efficient rule-placement algorithms that distribute forwarding policies across general SDN networks while managing rule-space constraints, and show how to support dynamic, incremental update of policies. We evaluate the effectiveness of our algorithms analytically by providing complexity bounds on their running time and rule space, as well as empirically, using both synthetic benchmarks, and real-world firewall and routing policies.
In many modern networks, such as datacenters, optical networks, and multiprotocol label switching (MPLS), the delivery of a traffic flow with a certain bandwidth demand over a single network path is either not possible or not cost-effective. In these cases, it is very often possible to improve the network's bandwidth utilization by splitting the traffic flow over multiple efficient paths. While using multiple paths for the same traffic flow increases the efficiency of the network, it consumes expensive forwarding resources from the network nodes, such as TCAM entries of Ethernet/MPLS switches and wavelengths/lightpaths of optical switches. In this paper, we define several problems related to splitting a traffic flow over multiple paths while minimizing the consumption of forwarding resources, and present efficient algorithms for solving these problems.
In Software Defined Networking (SDN) the control plane is physically separate from the forwarding plane. Control software programs the forwarding plane (e.g., switches and routers) using an open interface, such as OpenFlow. This paper aims to overcomes two limitations in current switching chips and the OpenFlow protocol: i) current hardware switches are quite rigid, allowing ``Match-Action'' processing on only a fixed set of fields, and ii) the OpenFlow specification only defines a limited repertoire of packet processing actions. We propose the RMT (reconfigurable match tables) model, a new RISC-inspired pipelined architecture for switching chips, and we identify the essential minimal set of action primitives to specify how headers are processed in hardware. RMT allows the forwarding plane to be changed in the field without modifying hardware. As in OpenFlow, the programmer can specify multiple match tables of arbitrary width and depth, subject only to an overall resource limit, with each table configurable for matching on arbitrary fields. However, RMT allows the programmer to modify all header fields much more comprehensively than in OpenFlow. Our paper describes the design of a 64 port by 10 Gb/s switch chip implementing the RMT model. Our concrete design demonstrates, contrary to concerns within the community, that flexible OpenFlow hardware switch implementations are feasible at almost no additional cost or power.
Software defined networks (SDNs) depart from traditional network architectures by explicitly allowing third-party software access to the network's control plane. Thus, SDN protocols such as OpenFlow give network operators the ability to innovate by authoring or buying network controller software independent of the hardware. However, this split design can make planning and designing large SDNs even more challenging than traditional networks. While existing network emulators allow operators to ascertain the behavior of traditional networks when subjected to a given workload, we find that current approaches fail to account for significant vendor-specific artifacts in the SDN switch control path. We benchmark OpenFlow-enabled switches from three vendors and illustrate how differences in their implementation dramatically impact latency and throughput. We present a measurement methodology and emulator extension to reproduce these control-path performance artifacts, restoring the fidelity of emulation.