Controller Placement Problem Research Articles

Heterogeneous SDN controller placement problem—The Wi-Fi and 4G LTE-U case

The widespread deployment of 5G wireless networks has brought about a radical change in the nature of mobile data consumption. It requires the deployment of Long Term Evolution to the unlicensed spectrum (LTE-U) to alleviate the shortage of available licensed spectrum while Wi-Fi is the most dominant radio access technology in the unlicensed spectrum. This has led to suggestions concerning the coexistence of multi radio access technologies such as Wi-Fi and LTE-U. Clearly, Software Defined Networks (SDN) can utilize the LTE-U radio bandwidth efficiently. The SDN paradigm decouples the network’s control logic from the underlying routers and switches, which promotes centralization of network control. The controller placement problem is crucial to SouthBound interface optimization and involves the location of the controllers, their number and the assignment function of switches to controllers. In this paper, a novel strategy is presented to address the wireless controller placement problem, which improves the throughput, link failure probability and the transparency on the SouthBound interface in cases where hybrid providers choose either LTE-U or Wi-Fi as link layer technologies. The problem of determining the placement of LTE-U and Wi-Fi based controllers is modeled and two heuristic solutions are proposed. Simulations show that the proposed algorithms provide a fast and efficient solution.

Joint optimization of primary and backup controller placement and availability link upgrade in SDN networks

In Software-Defined Networking (SDN), the control and data planes are decoupled, leading to a more programmable and efficient network management. In this paper, the controller placement problem in SDN is addressed, jointly with the problem of exploring a high-availability tree subgraph, in order to support delay and availability requirements between the switches and the controllers. We consider that each switch connects to a primary and to a backup controller. We formulate the joint optimization model as an integer linear programming model (ILP), and propose a heuristic method when the exact model becomes impractical. Furthermore, we compare two ILP formulations, and we also compare the controller redundancy solutions with those considering path redundancy alone.

Genetic Algorithms with Variant Particle Swarm Optimization Based Mutation for Generic Controller Placement in Software-Defined Networks

To enable learning-based network management and optimization, the 5th Generation Mobile Communication Technology and Internet of Things systems usually involve software-defined networking (SDN) architecture and multiple SDN controllers to efficiently collect the big volume of runtime statistics, define network-wide policies, and enforce the policies over the whole network. To better plan the placement of controllers over SDN systems, this article proposes a generic controller placement problem (GCP) that considers the organization and placement of controllers as well as the switch attachment to optimize the delay between controllers and switches, the delay among controllers, and the load imbalance among controllers. To solve this problem without losing generality, a novel multi-objective genetic algorithm (MOGA) with a mutation based on a variant Particle Swarm Optimization (PSO) is proposed. This PSO chooses a global best position for a particle according to a pre-computed global best position set to lead the mutation of the particle. It successfully handles multiple conflicting objectives, fits the scenario of mutation, and can apply in many other flavors of MOGAs. Evaluations over 12 real Internet service provider networks show the effectiveness of our MOGA in reducing convergence time and improving the diversity and accuracy of the Pareto frontiers. The proposed approaches in formulating and solving the GCP in this article are general and can be applied in many other optimization problems with minor modifications.

A new optimization technique to solve the latency aware controller placement problem in software defined networks

AbstractSoftware defined networking (SDN) is a modern and upcoming standard in today's network as it centralizes the network intelligence by separating the control plane from the forwarding plane. Placing a controller in an appropriate location and minimizing the switch to controller (SC) latency are important factors in SDN. In this article, we proposed a mathematical algorithm to form the clusters and placed one controller in each cluster to shorten the worst‐case SC latency. We have proposed a technique called the “$‐method” by using the distance matrix of the network nodes and placed a “$” whenever we have found the matrix element is greater than a given maximum distance. Initially, the maximum distance is calculated using the center of mass method that we have developed for minimizing the average SC latency. Our method guarantees that it will generate the minimum worst‐case SC latency efficiently that one could ever achieve for a different number of controller placement. Simulation has been done under some real‐world network topologies from the dataset of Internet Topology Zoo. Our result shows that the “$‐method” performs better compared with other existing algorithms in terms of worst‐case SC latency minimization with less number of controllers. Further, we have analyzed our method for the failure mode of a controller by assigning the switches of that failed controller to its nearest controllers which shows that our method also performs better in terms of network fault tolerance and improves network resilience.

An efficient approach to robust controller placement for link failures in Software-Defined Networks

In Software-Defined Networks (SDN), one of the critical research challenges for large-scale deployment of SDN is controller placement problem (CPP). However, link failures are critical security issues in networks and greatly impact SDN’s robustness. The CPP for link failures is still challenging today. To this end, we study the CPP for multi-link failures (CPP-MLF). Firstly, we investigate the real link data of today’s networks to analyze the characteristics of link failures and formalize the link failure rate. Next, we formulate minimizing the number of controllers and worst-case delay as the optimization objectives of CPP-MLF and develop a heuristic algorithm based on improved NSGA-II to solve CPP-MLF efficiently. Specifically, we improve the non-dominated set and crowding distance for the NSGA-II by dynamic competition mechanism and even distribution operator, respectively, thereby quickly obtaining the Pareto-optimal solutions of CPP-MLF. Afterwards, we introduce controller load variance to evaluate them to make a satisfactory decision on controller placement. We conduct simulations with real network topologies, and the results show that the proposed heuristic algorithm performs well on the number of controllers, worst-case delay and robustness, while producing acceptable runtime overheads.

Multi-criteria decision-making for controller placement in software-defined wide-area networks

Software-defined networks have many benefits such as more control over the control plane and reduced operating costs through separating the control plane from the data plane in network equipment. One of the most critical problems in software-defined networks is a controller placement problem, which significantly influences its overall performance. The purpose of this problem is to determine the number of controllers required and how to assign switches. This paper attempts to solve this problem, aiming to reduce the network's operational cost and to improve their survivability and load balancing. Hence, we have tried to divide the network into several subdomains using segmentation. Then, we used multi-criteria decision-making methods to solve the controller placement in each subdomain. For this purpose, we considered criteria such as reliability rate, cost, delay, and processing capacity. To assign switches to controllers, we used the proposed mathematical model to minimize the objective function while observing the defined constraints. Furthermore, according to the proposed architecture, we used distance to the central controller, adjacent neighborhood, and controller memory to select the cluster head controller for each subdomain to communicate with the central controller. Finally, we performed experiments on topologies Uran, SwitchL3, and Sinet of the Internet Topology Zoo to evaluate the proposed method. In these experiments, we compared the results of the proposed method with our work-related methods, including Controller Placement Analytic Hierarchy Process (CPAHP) and Controller Placement Modified Density Peak (CPMDP), in terms of criteria such as cost, survivability, number of controllers, connection failure probability, average delay, and controller load-balancing rate. The results show that the proposed method outperforms CPMDP and CPAHP. Thus, the proposed method has a 24.97% and 19.76% improvement in reducing network implementation costs than CPMDP and CPAHP, respectively.

A novel controller placement algorithm based on network portioning concept and a hybrid discrete optimization algorithm for multi-controller software-defined networks

Software defined network (SDN) has shown significant advantages in numerous real-life aspects with separating the control plane from the data plane that provides programmable management for networks. However, with the increase in the network size, a single controller of SDN imposes considerable limitations on various features. Therefore, in networks with immense scalability, multiple controllers are essential. Specifying the optimal number of controllers and their deployment place is known as the controller placement problem (CPP), which affects the network's performance. In the present paper, a novel controller placement algorithm has been introduced using the advantages of nature-inspired optimization algorithms and network portioning. Firstly, the Manta Ray Foraging Optimization (MRFO) and Salp Swarm Algorithm (SSA) have been discretized to solve CPP. Three new operators comprising a two-point swap, random insert, and half points crossover operators were introduced to discretized the algorithms. Afterward, the resulting discrete MRFO and SSA algorithms were hybridized in a promoting manner. Next, the proposed discrete algorithm has been evaluated on six well-known software-defined networks with a different number of controllers. In addition, the networks have been chosen from various sizes to evaluate the scalability of the proposed algorithm. The proposed algorithm has been compared with several other state-of-the-art algorithms regarding network propagation delay and convergence rate in experiments. The findings indicated the effectiveness of the contributions and the superiority of the proposed algorithm over the competitor algorithms.

A Novel Cost-Effective Controller Placement Scheme for Software-Defined Vehicular Networks

Energy costs have dramatically increased in data center networks as an increasing number of large-scale Internet applications are used. In software-defined vehicular networks (SDVN), the communication delay between two vehicles and between vehicles and the controller will dramatically climb up as the number of vehicles increases. This requires more controllers to provide communication service to minimize the latency. More controllers lead to high energy costs. Therefore, the number of controllers and their placement, the so-called controller placement problem (CPP), should be addressed. The appropriate placement of controllers can decrease the energy cost, enabling green communication in SDVN. Although CPP has been studied for static networks, it has not been effectively solved in highly dynamic and complex networks. In this article, a novel cost-effective CPP scheme for SDVN is proposed. First, our proposed minimum controller selection mechanism (MOSA) can reduce the number of controllers and guarantee the coverage of the area. Besides, an improved multiobjective artificial bee colony algorithm (IMABC) is proposed based on the original artificial bee colony algorithm. The IMABC can judge which controller should be switched on for data transmission based on real-time traffic flow. A route computation mechanism is proposed to evaluate the performance of our CPP scheme. The experimental results confirm that compared to other existing CPP schemes, our scheme can achieve a higher packet delivery ratio while greatly reducing energy consumption and latency.

Mobile-edge computing-based delay minimization controller placement in SDN-IoV

Internet of Vehicles (IoV) plays a fundamental role in the rapid development of intelligent transportation systems and smart cities by the way of facilitating data access. However, traditional routing protocols-based data forwarding cannot guarantee reliable services for low-latency applications in IoV. Motivated by the promising technologies of Software-defined networking (SDN) and Mobile-edge computing, this paper aims at enhancing the performance of IoV with the assistance of these two. Specifically, we first propose a three-layer hierarchy control framework for SDN-IoV based on the MEC. Under this framework, we investigate a controller placement problem with the objective of minimizing the delay between the switch and the controller. Then, we propose a Louvain algorithm-based controller placement policy to obtain the optimal location of controllers subject to load balance index and buffer size. Further, we put forward a controller replacement policy to adapt to the dynamic topology of IoV. Numerical results show that the proposed methods achieve a better performance than two baselines, in terms of the delay and load balance index.

Near-Optimal Robust Virtual Controller Placement in 5G Software Defined Networks

Fifth generation (5G) wireless networksare characterized by applying the software defined networking (SDN) and network function virtualization (NFV) concepts to provide higher reliability and scalability, and lower latency for advent data-hungry services. In the initial version of SDN based 5G, a centralized architecture for SDN controller has been proposed, which inherently cannot fulfill those requirements simultaneously. This observation has led us toward distributed architectures, where multiple SDN controllers across the network constitute the control layers. Furthermore, to fully achieve the network flexibility and agility offered by SDN, and also improve resource utilization and consequently to reduce network cost, we incorporate virtualized SDN (vSDN) controllers, enabled through the NFV technology. In vSDN with distributed architecture, controller placement is one of the main challenges, which is an NP-hard combinatorial optimization problem with conflicting objectives: 1) maximizing the reliability of network with low latency; 2) minimizing the total cost of implementation, which can be interpreted as reducing the number of vSDN controllers. In order to achieve such a compromise, in this work, we formulate the problem of vSDN controller placement and introduce some performance metrics to model the latency of communication between controller-switch pairs and also robustness against vSDN controller failures in a network. The introduced formulation is some sorts of submodular optimization, which is exploited to develop several algorithms. Simulations results demonstrate that, with a negligible performance loss, a significant reduction in the number of vSDN controllers is achievable. Finally, latency, cost, and robustness trade-offs are investigated.

Controller placement optimization for Software Defined Wide Area Networks (SDWAN)

Software Defined Networking (SDN) has emerged as a promising solution to revolutionize network deployment, operations and economic growth. This paradigm aims to address management and configuration complexities in legacy networks so as to reduce the total cost associated with deploying and running telecommunication infrastructures. At the heart of SDN is a controller which oversees orchestration of resources. An important problem that must be addressed during the initial design of an SDN-based network deployment is to find the optimal number of controllers and their locations, to achieve desired operational efficiency. This problem constitutes competing objectives such as latency, load balancing, and reliability. We apply Silhouette Analysis, Gap Statistics and the Partition Around Medoids (PAM) algorithms and, unlike previous work, we add a new method for solving the controller placement problem using an emulation orchestration platform. Our approach aims to optimize controller-to-node latency, alleviate control-plane signalling overhead and ensure control-plane resiliency. Our results for South African national research network (SANReN) reveal that deploying two controllers yields the lowest latency, reduces control-plane signalling overhead and guarantees control-plane resiliency. Our approach can be used by network operators as a guideline to start integrating SDN or plan a new SDN deployment, by helping them make quick automatic decisions regarding optimal controller placement.

On-Demand Dynamic Controller Placement in Software Defined Satellite-Terrestrial Networking

Software defined satellite-terrestrial networking has been identified as a promising approach to support the diversity of network services. As the fundamental issue to improve the flexibility of network management, the controller placement problem has been attracted increasing attentions for the integration of satellite and terrestrial networking. However, the impact of the dynamic coverage demands on the controller placement have not been well investigated in existed works, which makes them fail to adjust the coverage dynamically according to the actual demands, and leads to an obvious increase of networking response latency to the terminals. Aiming to address this issue, we propose a novel on-demand dynamic controller placement scheme, which can optimize the placement of controllers to improve networking response latency while meeting the dynamic coverage demands. Firstly, to optimize the number of controllers and meet the dynamic coverage demands, we define the coverage redundancy and propose the redundancy-based satellite subnet division method to establish the reliable satellite subnets. Secondly, we quantify the networking response latency of the distributed satellite subnet, and build an optimization mathematical model to optimize the number and location of controllers. Then, we formulate the controller placement problem into the capacitated facility location problem and build the mathematical model for it. Moreover, the on-demand dynamic approximation algorithm is proposed to obtain the approximation solution. Finally, the simulation results demonstrate that the proposed algorithm can effectively optimize the network latency compared with related algorithms.

A Novel Controller Placement Using Petri-Nets for SDNs

Software defined networking (SDN) separates the control and the data planes. This separation brings flexibility to the network. But the decoupling has some drawbacks such as the controller placement problem (CPP). Controller placement is a crucial task which affects the overall networks’ performance. This paper proposes a novel controller placement model that is based on petri-nets to place the SDN’s controllers. The proposed model is called controller placement using petri-nets for SDNs (CPPNSDN). CPPNSDN aims to reduce the average propagation latency among switches and their associated controllers. CPPNSDN divides the network into sub-networks. Each sub-network is governed by a controller. Experiments were conducted on the Internet2/OS3E topology to evaluate the performance of CPPNSDN. Experiments show that CPPNSDN reduces the average latency significantly compared to two reference models. The first reference model is the Modified Density Peaks Clustering (MDPC) and the Optimized Kmeans model. In terms of the overall average latency, the CPPNSDN has shown promising results as it outperformed the MDPC and optimized Kmeans reference models by 7% and 17% respectively. Confidence Interval (CI) used was 90%. This is an ongoing work and the results are promising for more future investigation.

Controller placement problem in software‐defined networking: A survey

AbstractA distinctive feature of software‐defined networking (SDN) is a logically centralized control plane realized using multiple physical controllers. The placement of the controllers, the so‐called controller placement problem (CPP), is a crucial design issue. It influences network performance parameters such as latency, flow setup time, network availability, load balance of the controllers, and energy consumption. In this article, we illustrate the formulation of these CPP objectives. We categorize the CPP design solutions as either static or adaptive. In adaptive CPP, the solutions proposed dynamically adapt to the number of controllers required and the switch to controller mapping to varying network traffic. We further differentiate adaptive CPP as wired or wireless. The optimization strategies adopted by the papers are analyzed and grouped into five categories: exact, heuristic, meta‐heuristic, clustering, and game theory. The merits and demerits of each approach are discussed. In conclusion, we outline the research challenges worth investigating.

SDN Controller Placement With Availability Upgrade Under Delay and Geodiversity Constraints

An inherent problem in Software-Defined Networking (SDN) is the Controller Placement Problem, which addresses how many controllers to deploy in the network, and where to place them. Several variants of this problem have been addressed and researched to find the placements that adapt best to different contexts. In this article, we address a more complex variant of this problem, to satisfy QoS requirements and to offer robustness against disaster-based failures. We address the joint optimization problem of controller placement and finding a tree subgraph which can be upgraded to have enhanced availability, in order to satisfy delay and availability constraints. Additionally, we consider geodiversity constraints as a way to enhance robustness to disaster-based failures.

Taxonomy of controller placement problem (CPP) optimization in Software Defined Network (SDN): a survey

The new network requirements are rising with internet scalability and expansion of its coverage. The traditional network cannot support recent needings, so a new architecture has been proposed for the future networks called Software Defined Network (SDN). This architecture makes the network more programmable, flexible, and controllable, though the scalability is the most important challenge on which the researchers are working in SDN. Multiple controllers are a necessity of current SDN, so the optimum number of controllers and their placement is a problem called controller placement problem (CPP). There are defined different functions to optimize scalability, reliability, and others in SDN which consider various metrics in recent research papers. This optimization problem is NP-hard. In this paper, we survey the CPP optimization in recent well-known papers to extract optimization strategies, objective functions, and solutions. We finally reveal a new taxonomy of cutting-edge studies about solutions of CPP optimization in the SDN from different dimensions. CPP solutions based on objective functions, metrics and traits are classified in this article. Furthermore, we put forward the new challenges and metrics which can be reckoned in CPP to be optimized. This paper can be useful for those working on CPP optimization in SDN to expose the objective functions, variables and metrics.

A fault tolerance metaheuristic‐based scheme for controller placement problem in wireless software‐defined networks

SummarySoftware‐defined networking (SDN) paradigm has become the master solver for traditional network restrictions. The fundamental concept of SDN is moving the control plane into one or more servers called controllers and confining the data plane to several forwarding network elements allowing dynamic and flexible network management. A critical challenging issue in SDN‐based network architecture is the controller placement problem (CPP) that is an NP‐hard problem. Trends of researches try solving the CPP based on evolutionary algorithms focusing on either propagation delay or balancing the load among distributed controllers. In this paper, we have proposed a fault tolerance metaheuristic‐based scheme for CPP in wireless software‐defined networks, named FTMBS. The aim of our proposed FTMBS scheme is as follows: maximizing the network connectivity, maximizing the load balance among controllers, minimizing the worst‐case latency between controllers and associated nodes and between controllers themselves, and maximizing the network lifetime. When dealing with a multi‐objective‐based scheme, a trade‐off exists mainly when these multi‐objective metrics compete with each other, and it will be up to the decision maker to decide on this trade‐off. We have considered a network of 500 randomly distributed sensor nodes and demonstrated various simulations for different network performance metrics and concluded that three controllers are enough for such networks. For performance evaluation, we have verified our solutions to be close to Pareto optimal ones provided by non‐dominated sorting genetic algorithm‐II (NSGA‐II).

Assessment of Connectivity-Based Resilience to Attacks Against Multiple Nodes in SDNs

In Software Defined Networks (SDNs), the control plane of a network is decoupled from its data plane. For scalability and robustness, the logically centralized control plane is implemented by physically placing different controllers throughout the network. The determination of the number and placement of controllers is known as the Controller Placement Problem (CPP). In the regular (i.e., failure-free) state, the control plane must guarantee a given maximum delay between every switch and its primary controller and a given maximum delay between every pair of controllers. In general, these delay bounds allow multiple solutions and, so, other goals can be used to determine the best CPP solution. In this paper, we assess the connectivity-based resilience to malicious attacks against multiple network nodes of the CPP solutions obtained with three different aims: the regular state delay optimization without any concern about attacks, the regular state delay optimization taking into consideration the worst-case attacks and the resilience optimization to attacks against multiple nodes. We assess the CPP solutions considering attacks of targeted nature (when the attacker has complete knowledge of the data plane) and attacks of non-targeted nature (i.e., random and epidemic attacks). We present computational results providing an analysis of the CPP solutions to the different types of attacks. The main conclusion is that the connectivity-based resilience between the different CPP solutions strongly depends on the network topology, the regular state delay bounds and the type of attacks. Finally, we provide insights on how SDN operators can consider the conducted assessment when deciding the controller placements in their networks.

Cost-Effective Survivable Controller Placement in Software-Defined Networks

One of the problems raised in software-defined networks (SDN) is to determine the number and installation location of controllers so that the implementation cost reduced, and the survivability of the network against link or node failure increased. The current investigations in SDN focus on directly linking controllers to each other in the design of control plane. This approach, while incurring a considerable installation cost, does not carefully consider network survivability requirements. In this paper, we introduce integer-programming formulations to address controller placement problems and demonstrate through careful computational studies that the proposed method is capable of increasing network survivability while reducing the cost of network implementation. Also, due to the conditions of the environment implementation, the degree of survivability can be received as input parameter. The proposed method was implemented on different topologies and then was analyzed and compared to the optimal model for the controller placement problem (OMCPP) and reliable capacitated controller placement problem (RCCPP). Experiment results show that the proposed method has an improvement of 18.33% and 22.40% in terms of implementation costs compared to OMCPP and RCCPP methods.

SDN Wireless Controller Placement Problem-The 4G LTE-U Case

To cope with the shortage of available licensed spectrum, 4th Generation Long Term Evolution (4G LTE) is expected to be deployed also in the unlicensed spectrum. This raises the problem of the coexistence of multiple operators. Obviously, a Software Defined Networking (SDN) based control approach can utilize the radio bandwidth by coordinating between multiple LTE-Unlicensed (LTE-U) operators. Within SDN control plane, there is a well-known issue namely the Controller Placement Problem (CPP) which has a major impact on the efficiency of the control plane. This paper addresses the Wireless Controller Placement Problem (WCPP) when the SouthBound interface (SBi) is based on 4G LTE unlicensed. The proposed solution improves the throughput, link failure probability and the transparency on the SBi from concurrent transmissions on the control plane. Two heuristic solutions are considered, one is a simulated annealing based and the other is a ray-shooting based. The simulation results show that they are fast and efficient and the ray-shooting based heuristic out-performs the simulated annealing based heuristic. In addition, it is shown that the transparency improves in bigger networks.