Abstract: A service-function chain, or simply a chain, is an ordered sequence of service functions, e.g., firewalls and load balancers, composing a service. A chain deployment involves selecting and instantiating a number of virtual network functions (VNFs), i.e., softwarized service functions, placing VNF instances, and routing traffic through them. In the current optimization-models of a chain deployment, the instances of the same function are assumed to be identical, while typical service providers offer VNFs with heterogeneous throughput and resource configurations. The VNF instances of the same function are installed in a single physical machine, which limits a chain to the throughput of a few instances that can be installed in one physical machine. Furthermore, the selection , placement , and routing problems are solved in isolation. We present distributed service function chaining that coordinates these operations, places VNF-instances of the same function distributedly , and selects appropriate instances from typical VNF offerings. Such a deployment uses network resources more efficiently and decouples a chain’s throughput from that of physical machines. We formulate this deployment as a mixed integer programming (MIP) model, prove its NP-Hardness, and develop a local search heuristic called Kariz. Extensive experiments demonstrate that Kariz achieves a competitive acceptance-ratio of 76%–100% with an extra cost of less than 24% compared with the MIP model.

Abstract: Network Function Virtualization (NFV) is a promising technology that is receiving significant attention in both academia and the industry. NFV paradigm proposes to decouple Network Functions (NFs) from dedicated hardware equipment, offering a better sharing of physical resources and providing more flexibility to network operators. However, in such environment, efficient management mechanisms are crucial to address the problem of Placement and Chaining of Virtual Network Functions (PC-VNF). In this paper, we introduce a PC-VNF model based on a flexible resource allocation approach that takes into account service requirements in terms of latency, in addition to traditional connectivity and resource utilization. This is particularly important for emerging 5G services such as ultrareliable, low latency and massive machine type communications. The end-to-end performance needs to meet the user expectations as well as service requirements to provide the desired QoS/QoE. Our main goal is to determine the optimal VNF placement minimizing resource consumption while providing specific latency (i.e., end-to-end delay) and avoiding violation of Service Level Agreements (SLA) by constraining allocated resources to a given VNF to reach its required performance. Results show that our approach achieves the required latency with better resources utilization compared to the classical approaches, with a reduction of up to 40% of resource consumption and a higher rate of accepted requests by recovering 15 to 60 % of the rejected requests.

Abstract: Service Function Chains (SFCs) comprise a sequence of Network Functions (NFs) that are typically traversed in-order by data flows. Consequently, SFC delay grows linearly with the length of the SFC. Yet, for highly latency sensitive applications, this delay may be unacceptable---particularly when the constituent NFs are virtualized, running on commodity servers. In this paper, we investigate how SFC latency may be reduced by exploiting opportunities for parallel packet processing across NFs. We propose ParaBox, a novel hybrid packet processing architecture that, when possible, dynamically distributes packets to VNFs in parallel and merges their outputs intelligently to ensure the preservation of correct sequential processing semantics. To demonstrate the feasibility of our approach, we implement a ParaBox prototype on top of the DPDK-enabled Berkeley Extensible Software Switch. Our preliminary experiment results show that ParaBox can not only significantly reduce the service chaining latency, but also improve throughput.

Abstract: This paper addresses energy efficient VNF placement and chaining over NFV enabled infrastructures. VNF placement and chaining are formulated as a decision tree search to overcome this NP-Hard problem complexity. The proposed approach is an extension of the Monte Carlo Tree Search (MCTS) method to achieve energy savings using physical resource consolidation and sharing VNFs between multiple tenants. A real cloud testbed and extensive simulations are used to assess performance and ability to scale with problem size. Evaluation results show significant reduction in energy consumption of the proposed placement solution compared to related work. The polynomial complexity of our proposal is highlighted by the simulation results.

Abstract: Service Function Chaining (SFC) allows the forwarding of a traffic flow along a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT). Software Defined Networking (SDN) solutions can be used to support SFC reducing the management complexity and the operational costs. One of the most critical issues for the service and network providers is the reduction of energy consumption, which should be achieved without impact to the quality of services. In this paper, we propose a novel resource (re)allocation architecture which enables energy-aware SFC for SDN-based networks. To this end, we model the problems of VNF placement, allocation of VNFs to flows, and flow routing as optimization problems. Thereafter, heuristic algorithms are proposed for the different optimization problems, in order find near-optimal solutions in acceptable times. The performance of the proposed algorithms are numerically evaluated over a real-world topology and various network traffic patterns. The results confirm that the proposed heuristic algorithms provide near optimal solutions while their execution time is applicable for real-life networks.

Abstract: Service chaining is one of the key technologies that is used to support mobile edge computing (MEC) services for users in mobile communications radio access networks (RANs). By adapting network functions virtualization (NFV) technology to MEC, cloud-computing functionalities can be allocated near the base station of the RAN, resulting in extremely fast service access to user equipment. This letter provides a clustered NFV service chaining (cNSC) scheme that computes the optimal number of clusters to minimize the end-to-end time of MEC services. The cNSC scheme is applied to form multiple MEC clusters of NFV enabled nodes within the RAN.

Abstract: In this paper, we first introduce the NFV architecture and the use of IPv6 Segment Routing (SRv6) network programming model to support Service Function Chaining in a NFV scenario. We describe the concepts of SR-aware and SR-unaware Virtual Network Functions (VNFs). The detailed design of a network domain supporting VNF chaining through the SRv6 network programming model is provided. The operations to support SR-aware and SR-unaware VNFs are described at an architectural level and in particular we propose a solution for SR-unaware VNFs hosted in a NFV node. The proposed solution has been implemented for a Linux based NFV host and the software is available as Open Source. Finally, a methodology for performance analysis of the implementation of the proposed mechanisms is illustrated and preliminary performance results are given.

Abstract: Network services have been significantly increased in today's enterprise networks. The time and cost of deploying these services are recently considered as critical challenges for enterprise networks. Network Functions Virtualization (NFV) is a promising solution to offer cost-efficient, scalable and more rapid deployment of such services. It allows the implementation of fine-grained services as a chain of Virtual Network Functions (VNFs). These chains need to be placed in the network. The chain placement is critical since it effects on both quality of service (QoS) and the provider cost. This paper formulates the problem of VNF placement and chaining as an Integer Linear Program (ILP) and proposes a Cost-efficient Centrality-based VNF Placement and chaining algorithm (CCVP). The objective is to find the optimal number of VNFs along with their locations in such a manner that the provider cost is minimized. Apart from cost minimization, the support for large-scale environments with a large number of servers and end-users is an important feature of the proposed algorithm. Finaly, the algorithm behavior is analyzed through simulations.

Abstract: We investigate contextual online learning with nonparametric (Lipschitz) comparison classes under different assumptions on losses and feedback information. For full information feedback and Lipschitz losses, we design the first explicit algorithm achieving the minimax regret rate (up to log factors). In a partial feedback model motivated by second-price auctions, we obtain algorithms for Lipschitz and semi-Lipschitz losses with regret bounds improving on the known bounds for standard bandit feedback. Our analysis combines novel results for contextual second-price auctions with a novel algorithmic approach based on chaining. When the context space is Euclidean, our chaining approach is efficient and delivers an even better regret bound.

Abstract: Network function virtualization along with network service chaining and forwarding graphs envision a reduction in the respective cost that end users, service providers, and network operators are experiencing, while providing complete and high quality services. The allocation of these service chains in a pool of available cloud or data center resources is a challenging problem that can affect the overall performance of the offered network services. Furthermore, a number of challenges associated with the hardware capabilities and the available resources of the cloud infrastructure, along with possible collocation constraints between the components of the service chain, can exponentially increase the complexity of resource allocation. This paper examines how to improve the overall allocation performance of deploying service chains in a cloud environment satisfying server affinity, collocation, and latency constraints. The proposed method is inspired by a partitioning game, where the various components of a service chain are split in a set of partitions executed as virtual machines/containers in appropriate servers. We mathematically prove that a Nash equilibrium exists for our partitioning game corresponding to an optimal solution. By implementing the partitioning game as an iterative refinement process, we also experimentally validate that the proposed algorithm converges to the optimal solution.

Abstract: The virtualized network functions placement and chaining problem is formulated as a decision tree to reduce significantly the complexity of service function chaining (SFC) in clouds. Each node in the tree corresponds to a virtual resource embedding and each tree branch to the mapping of a client request in some physical candidate. This transforms the placement problem to a decision tree search. We devise a new algorithm based on the Monte Carlo Tree Search (MCTS) to incrementally build and search within the decision tree. Thanks to the proposed SFC-MTCS strategy, an optimized solution is computed in a reasonable time. Extensive simulations assess the performance and show that SFC-MCTS outperforms state of the art strategies in terms of: i) acceptance rate, ii) providers revenue and iii) execution time.

Abstract: Nowadays, network and telecommunication operators require flexible and dynamic models to deploy new services in a fast, reliable and cost saving way. The Service Function Chaining (SFC) design is particularly suited to meet such needs, especially in conjunction with the Network Function Virtualization (NFV) paradigm that adds a noteworthy elasticity during the SFC deployment phase. Accordingly, SFC is realized by means of a composition of Virtualized Network Functions (VNFs) aimed at providing some specific services. We consider, from an availability point of view, an SFC-based architecture with an aim to find out the optimal configuration guaranteeing the so-called “five nines” availability requirement, as demanded in the telecommunication systems. The availability analysis is carried out by exploiting a hierarchical model where a Reliability Block Diagram describes high level dependencies in the SFC implementation, while Stochastic Reward Nets are adopted to model the probabilistic behavior of single blocks. In particular, the SFC availability has been evaluated by performing a steady-state analysis, while a sensitivity analysis of some critical parameters allowed us to analyze in depth the whole system robustness.

Abstract: Software Defined Networking and Network Function Virtualization are two paradigms that offer flexible software-based network management. Service providers are instantiating Virtualized Network Functions - e.g., firewalls, DPIs, gateways - to highly facilitate the deployment and reconfiguration of network services with reduced time-to-value. They employ Service Function Chaining technologies to dynamically reconfigure network paths traversing physical and virtual network functions. Providing a cost-efficient virtual function deployment over the network for a set of service chains is a key technical challenge for service providers, and this problem has recently caught much attention from both Industry and Academia. In this paper, we propose a formulation of this problem as an Integer Linear Program that allows one to find the best feasible paths and virtual function placement for a set of services with respect to a total financial cost, while taking into account the (total or partial) order constraints for Service Function Chains of each service and other constraints such as end-to-end latency, anti-affinity rules between network functions on the same physical node and resource limitations in terms of network and processing capacities. Furthermore, we propose a heuristic algorithm based on a linear relaxation of the problem that performs close to optimum for large scale instances.

Abstract: In this paper, we present a systemic approach to provide deterministic delay guarantee for dynamic service chaining in software defined networking (SDN) The delay performance of service chaining in SDN is affected by signaling message exchange in control plane and packet transmissions in data plane, respectively First, we develop an analytical method to characterize the delay performance of control plane when handling traffic with different priorities according to network calculus (NC) and queuing theory Second, taking into account the estimated delay in control plane, we propose a novel service traversal mechanism to calculate the optimal traversal path for the service chain We demonstrate that NC delay analysis can provide deterministic quality of service (QoS)-guaranteed service chaining for any specified delay requirements, whereas theoretical queueing delay analysis can only provide statistical QoS guarantee In summary, the proposed NC delay analysis can help to understand the network design for a future delay sensitive Internet in which deterministic latency must be guaranteed

Abstract: Enterprise networks deploy a variety of security devices to protect the network, hosts and endpoints. Network security devices, both hardware and virtual, operate at all OSI layers with scanning and analysis capabilities for application content. Multiple specific devices are often deployed together for breadth and depth of defense. This document describes use cases of Service Function Chaining (SFC) when deploying network security devices in the manner described above and also puts forth requirements for their effective operation.

Abstract: Mobile networks have urgent demands of fine-grained, cost-effective and flexible service provision for diversified user traffic. To cope with these demands, researchers have proposed various Service Function Chaining (SFC) solutions with the rise of Software Defined Networking (SDN) and Network Function Virtualization (NFV) technologies. However, most of them are performed based on MAC address and/or OpenFlow protocols without Network Service Header (NSH) support, having drawbacks in complexity, scalability and flexibility. NSH-based approaches are more promising for mobile networks, since they support metadata-based packet information sharing and policy enforcement. Moreover, a hierarchical SFC (hSFC) architecture is proposed to alleviate the scalability and management problems in large-scale networks. Nevertheless, how to realize application awareness and on-demand service provision has not been investigated thoroughly in the hSFC environment. Thus, in this paper, we propose a proactive-based branching approach for application-aware and dynamic security function chaining, where application features are analyzed at first, and then carried in the metadata of NSHs for subsequent processes by the relevant security functions. In this way, the data plane is able to redirect traffic based on metadata without the participation of control plane. Besides, we verify the proposed approach through our prototype system via two typical use cases, the application-aware traffic control and lawful interception, and the related experiment results confirm its feasibility and elasticity.

Abstract: Studying trip chaining behavior has been a challenging endeavor which requires the support of microscopic travel data. New insights into trip chaining can be gained from real-time GPS travel data. This research introduces a framework that considers two-destination choice in the context of home-based trip chains. We propose and empirically compare three alternatives of building choice sets where we consider various relationships of the two destinations (such as major–minor destinations, selecting one first, and selecting two concurrently). Our choice set formation alternatives use survival models to determine the selection probability of a destination. Our results reveal that trip chaining behavior is shaped by the features of retail clusters, spatial patterns of clusters, transportation networks, and the axis of travel. This research reveals that not only the spatial relationship but also the land use relationship of the destinations in a trip chain affect the decision making process.

Abstract: In one embodiment, a device in a network receives a packet that includes one or more forwarding labels and a service function chaining (SFC) header. The device removes the one or more forwarding labels from the packet. The device inserts an indication of the one or more forwarding labels into metadata of the SFC header. The device forwards the packet with the inserted indication of the one or more forwarding labels to a service function.

Abstract: An example device in accordance with an aspect of the present disclosure includes identifying a service and/or management function among multiple functions based on an available capacity. Tables are updated to cause the packet to be forwarded to the identified function accordingly.

Abstract: In this paper, we present ICN-FC, which is an Information-Centric Networking (ICN) based framework for efficient functional chaining (FC). The key enabling techniques for ICN-FC includes naming semantics, Interest & Data processing and an efficient FC forwarding strategy. By using the proposed solutions, a functional chaining request, which consists of the name of raw data and an ordered set of functions, can be executed seamlessly, dynamically and flexibly in the network. In addition, the novel FC forwarding strategy can be used to improve the forwarding efficiency for functional chaining requests. The overall feasibility and efficiency of the proposed solutions are validated by using both experimental prototype and network simulation. The results show that the proposed solutions outperform previous works such as named function networking to support functional chaining applications.

Abstract: Cloud databases provide facilities for large scale data storage and retrieval of distributed data. However, the current access control techniques provided in database systems for maintaining security are not sufficient to secure the private data stored in public cloud databases. In this paper, a new secured data storage algorithm for effective maintenance of confidential data is proposed. To perform storage and retrieval operations of data in the cloud data storage effectively, map reduce algorithms are developed in this work which performs data reduction and fast processing. In order to consider the temporal nature of documents to be retrieved, we propose a new algorithm called Temporal Secured Cloud Map Reduced Algorithm which integrates temporal constraints with map reduce algorithms and also the chaining Hill Cipher encryption algorithms which is proposed newly in this work. The main advantages of the proposed algorithm is that they reduce the processing time and maintains security effectively. The experimental results obtained from this work depict that the proposed model is optimizing cost and it ensures data security.

Abstract: This document defines data plane functionality required to implement service segments and achieve service chaining in SR-enabled MPLS and IP networks, as described in the Segment Routing architecture.

Abstract: Ethernet Powerlink (EPL) is an industrial Ethernet networking solution commonly used as a communication network in distributed control and automation systems ranging from simple I/O to highly complex motion control applications. The PollResponse Chaining (PRC) mechanism is a new EPL standard feature aimed at increasing the network performance when nodes exchange small amount of data, especially if they are connected in line topology. In this paper, we present a theoretical model suitable for assessing the real-time performance of the EPL protocol operating in both the standard and PRC mode for two basic topologies commonly found in real installations, line, and star. Moreover, we carried out a series of experiments on prototype networks in order to acquire the relevant timing parameters of the EPL network components required for the development of an OMNeT++ simulation model, which can be further exploited to evaluate the EPL protocol in the case of more complex scenarios. Finally, we propose a modification of the original PRC solution to improve its flexibility while allowing the same (or even higher) performance level. The feasibility of the proposed approach was demonstrated on a real prototype, whereas a certain performance gain over the original PRC mechanism was proved through simulations conducted on a more complex network structure.

Abstract: Virtualized network function (VNF) service chaining in optical datacenter networks (DCN) is a more complex problem than that in packet-switched networks, as it introduces additional constraints related to the optical network. For example, in an optical DCN one needs to make sure that optical network resources are efficiently utilized, which requires multiplexing of several VNF chains to fill the optical pipes. In this paper, we first propose a novel and flexible DCN architecture based on optical circuit switching technology supporting service chaining in the optical domain. Then, we formulate the problem of VNF service chaining in the proposed optical DCN using integer linear problem (ILP) formulation and heuristic methods. We also numerically investigate the performance of the proposed architecture and the service chaining methods using a set of examples.

Abstract: We investigate contextual online learning with nonparametric (Lipschitz) comparison classes under different assumptions on losses and feedback information. For full information feedback and Lipschitz losses, we design the first explicit algorithm achieving the minimax regret rate (up to log factors). In a partial feedback model motivated by second-price auctions, we obtain algorithms for Lipschitz and semi-Lipschitz losses with regret bounds improving on the known bounds for standard bandit feedback. Our analysis combines novel results for contextual second-price auctions with a novel algorithmic approach based on chaining. When the context space is Euclidean, our chaining approach is efficient and delivers an even better regret bound.

Abstract: In distributed network function virtualization (NFV) environments, the latency can be significantly increased as the length of service function chain (SFC) increases. To reduce the latency, the order dependency allowing parallel processing of service functions (SFs) can be exploited. In this paper, we propose an order dependency-aware SF placement scheme and analyze its advantages and challenges compared with conventional ones.

Abstract: In this paper, we show how to theoretically compute the step differential probability of RIPEMD-160 under the condition that only one internal variable contains difference and the difference is a power of 2. Inspired by the way of computing the differential probability, we can do message modification such that a step differential hold with probability 1. Moreover, we propose a semi-free-start collision attack on 48-step RIPEMD-160, which improves the best semi-free start collision by 6 rounds. This is mainly due to that some bits of the chaining variable in the i-th step can be computed by adding some conditions in advance, even though some chaining variables before step i are unknown. Therefore, the uncontrolled probability of the differential path is increased and the number of the needed starting points is decreased. Then a semi-free-start collision attack on 48-step RIPEMD-160 can be obtained based on the differential path constructed by Mendel et al. at ASIACRYPT 2013. The experiments confirm our reasoning and complexity analysis.

Abstract: We present the SPN OS, a Network-as-a-Service orchestration platform for NFV/SDN integrated service provisioning across multiple datacenters over packet/optical networks. Our prototype showcases template-driven service function chaining and high-level network programming-based optical networking.