Marcelo Caggiani Luizelli

Piecing together the NFV provisioning puzzle: Efficient placement and chaining of virtual network functions

Network Function Virtualization (NFV) is a promising network architecture concept, in which virtualization technologies are employed to manage networking functions via software as opposed to having to rely on hardware to handle these functions. By shifting dedicated, hardware-based network function processing to software running on commoditized hardware, NFV has the potential to make the provisioning of network functions more flexible and cost-effective, to mention just a few anticipated benefits. Despite consistent initial efforts to make NFV a reality, little has been done towards efficiently placing virtual network functions and deploying service function chains (SFC). With respect to this particular research problem, it is important to make sure resource allocation is carefully performed and orchestrated, preventing over- or under-provisioning of resources and keeping end-to-end delays comparable to those observed in traditional middlebox-based networks. In this paper, we formalize the network function placement and chaining problem and propose an Integer Linear Programming (ILP) model to solve it. Additionally, in order to cope with large infrastructures, we propose a heuristic procedure for efficiently guiding the ILP solver towards feasible, near-optimal solutions. Results show that the proposed model leads to a reduction of up to 25% in end-to-end delays (in comparison to chainings observed in traditional infrastructures) and an acceptable resource over-provisioning limited to 4%. Further, we demonstrate that our heuristic approach is able to find solutions that are very close to optimality while delivering results in a timely manner.

Survivor: An enhanced controller placement strategy for improving SDN survivability

In SDN, forwarding devices can only operate correctly while connected to a logically centralized controller. To avoid single-point-of-failure, controller architectures are usually implemented as distributed systems. In this context, recent literature identified fundamental issues, such as device isolation and controller overload, and proposed controller placement strategies to tackle them. However, current proposals have crucial limitations: (i) device-controller connectivity is modeled using single paths, yet in practice multiple concurrent connections may occur; (ii) peaks in the arrival of new flows are only handled on-demand, assuming that the network itself can sustain high request rates; and (iii) failover mechanisms require predefined information, which, in turn, has been overlooked. This paper proposes Survivor, a controller placement strategy that addresses these challenges. The strategy explicitly considers path diversity, capacity, and failover mechanisms at network design. Comparisons to the state-of-the-art on survivable controller placement show that Survivor is superior because (a) path diversity increases the survivability significantly; and (b) capacity-awareness is essential to handle overload during both normal and failover states.

Constant Time Updates in Hierarchical Heavy Hitters

Monitoring tasks, such as anomaly and DDoS detection, require identifying frequent flow aggregates based on common IP prefixes. These are known as hierarchical heavy hitters (HHH), where the hierarchy is determined based on the type of prefixes of interest in a given application. The per packet complexity of existing HHH algorithms is proportional to the size of the hierarchy, imposing significant overheads. In this paper, we propose a randomized constant time algorithm for HHH. We prove probabilistic precision bounds backed by an empirical evaluation. Using four real Internet packet traces, we demonstrate that our algorithm indeed obtains comparable accuracy and recall as previous works, while running up to 62 times faster. Finally, we extended Open vSwitch (OVS) with our algorithm and showed it is able to handle 13.8 million packets per second. In contrast, incorporating previous works in OVS only obtained 2.5 times lower throughput.

Characterizing the impact of network substrate topologies on virtual network embedding

Network virtualization is a mechanism that allows the coexistence of multiple virtual networks on top of a single physical substrate. One of the research challenges addressed recently in the literature is the efficient mapping of virtual resources on physical infrastructures. Although this challenge has received considerable attention, state-of-the-art approaches present, in general, a high rejection rate, i.e., the ratio between the number of denied virtual network requests and the total amount of requests is considerably high. In this work, we investigate the relationship between the quality of virtual network mappings and the topological structures of the underlying substrates. Exact solutions of an online embedding model are evaluated under different classes of network topologies. The obtained results demonstrate that the employment of physical topologies that contain regions with high connectivity significantly contributes to the reduction of rejection rates and, therefore, to improved resource usage.

A fix-and-optimize approach for efficient and large scale virtual network function placement and chaining

Network Function Virtualization (NFV) is a novel concept that is reshaping the middlebox arena, shifting network functions (e.g. firewall, gateways, proxies) from specialized hardware appliances to software images running on commodity hardware. This concept has potential to make network function provision and operation more flexible and cost-effective, paramount in a world where deployed middleboxes may easily reach the order of hundreds. In spite of recent research activity in the field, little has been done towards efficient and scalable placement & chaining of virtual network functions (VNFs) a key feature for the effective success of NFV. More specifically, existing strategies have either neglected the chaining aspect of NFV, focusing on efficient placement only, or failed to scale to hundreds of network functions. In this paper, we approach VNF placement and chaining as an optimization problem, and propose a fix-and-optimize-based heuristic algorithm for tackling it. Our algorithm incorporates a Variable Neighborhood Search (VNS) meta-heuristic, for efficiently exploring the placement and chaining solution space. The goal is to minimize required resource allocation, while meeting network flow requirements and constraints. We provide evidence that our algorithm is able to find feasible, high quality solutions efficiently, even in scenarios scaling to hundreds of VNFs.

Constant Time Weighted Frequency Estimation for Virtual Network Functionalities

Monitoring flow volumes is a fundamental capability in network measurement. Sampling is often used to cope with the line speed and the applied methods typically rely on uniform packet sampling. However, it is inaccurate when there is a large variance in packet sizes. In this work we introduce Byte Uniform Sampling (BUS), a sampling method for estimating flow volumes. We show that BUS can be combined with existing unweighted estimation algorithms and that the result is a weighted algorithm. BUS enables an asymptotic update time improvement as existing weighted algorithms are slower. We formally analyze BUS and evaluate it on five Internet traces. Finally, we extend the DPDK version of Open vSwitch to support BUS and demonstrate similar throughput when compared to uniform packet samples

How physical network topologies affect virtual network embedding quality: A characterization study based on ISP and datacenter networks

Abstract Network virtualization is a mechanism that allows the coexistence of multiple virtual networks on top of a single physical substrate. Due to its well-known potential benefits (e.g., lower CAPEX/OPEX expenditures), it has been embraced by the IT sector, specially by Internet Service Providers (ISPs) and cloud computing/datacenter companies. One of the research challenges addressed recently in the literature is the efficient mapping of virtual resources on physical infrastructures. Although this challenge has received considerable attention, state-of-the-art approaches present, in general, a high rejection rate, i.e., the ratio between the number of denied virtual network requests and the total amount of requests is considerably high. In this work, we investigate the relationship between the quality of virtual network mappings and the topological structures of the underlying substrates. Exact solutions of an online embedding model are evaluated under different classes of ISP and datacenter network topologies. The obtained results demonstrate that the employment of physical topologies that contain regions with high connectivity significantly contributes to the reduction of rejection rates and, therefore, to improved resource usage. Additionally, through an extensive analysis of denied requests, we assess the main rejection causes related to both ISP and datacenter networks and provide strong evidence of each one. In summary, through the embedding of virtual requests, available resources in ISP networks tend to be more partitioned in comparison to datacenter networks. Such differences on partitioning levels lead to a different percentage of rejection causes in each topology class.

Reconnecting Partitions on Physical Infrastructures: Towards an Expansion Strategy for Efficient Virtual Network Embedding

One of the research challenges approached recently in the literature is the efficient mapping of virtual networks on top of physical infrastructures. Although there have been efforts to solve it, we observe that a number of virtual network requests are rejected due to the exhaustion of resources only in key points of the infrastructure. In this paper, we propose an expansion strategy based on the reconnection of strongly connected components (partitions) of the infrastructure in order to suggest adjustments that lead to higher virtual network acceptance and, in consequence, to improved physical resource utilization. The obtained results evidence that an expansion of 10% to 20% of the infrastructure resources using the proposed strategy leads to a sustained increase of up to 30% in the number of accepted virtual networks and of up to 45% in resource usage compared to the original network.

The actual cost of software switching for NFV chaining

Network Function Virtualization (NFV) is a novel paradigm that enables flexible and scalable implementation of network services on cloud infrastructure. An important enabler for the NFV paradigm is software switching, which should satisfy rigid network requirements such as high throughput and low latency. Despite recent research activities in the field of NFV, not much attention was given to understand the costs of software switching in NFV deployments. Existing approaches for traffic steering and orchestration of virtual network functions either neglect the cost of software switching or assume that it can be provided as an input, and therefore real NFV deployments of network services are often suboptimal. In this work, we conduct an extensive and in-depth evaluation that examines the impact of service chaining deployments on Open vSwitch - the de facto standard software switch for cloud environments. We provide insights on network performance metrics such as throughput, CPU utilization and packet processing, while considering different placement strategies of a service chain. We then use these insights to provide an abstract generalized cost function that accurately captures the CPU switching cost of deployed service chains. This cost is an essential building block for any practical optimized placement management and orchestration strategy for NFV service chaining.

HIPER: Heuristic-based infrastructure expansion through partition reconnection for efficient Virtual Network Embedding

As research in the area of network virtualization continues to advance, there have been numerous efforts to solve the challenge of efficiently mapping virtual networks on top of physical structures. Despite these efforts, current state-of-the-art proposals still suffer from significant amount of rejection of virtual network requests in circumstances where overall resource availability would be sufficient to embed them. This is caused by the exhaustion of resources in certain key points of the infrastructure. In this paper, we propose HIPER - a strategy for expanding physical networks that suggests infrastructure upgrades with the objective of maximizing the acceptance of virtual network requests (and, as a consequence, physical resource utilization). This is achieved through the reconnection of strongly connected components (i.e., recurring partitions) of the infrastructure. Evaluated under realistic workloads, HIPER led to promising results. After the expansion of 10% to 20% of infrastructure resources, HIPER sustained an increase of up to 30% in virtual network acceptance, allowing an additional 52% in resource utilization.