128 research outputs found

    Enabling multicast slices in edge networks

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    Telecommunication networks are undergoing a disruptive transition towards distributed mobile edge networks with virtualized network functions (VNFs) (e.g., firewalls, Intrusion Detection Systems (IDSs), and transcoders) within the proximity of users. This transition will enable network services, especially IoT applications, to be provisioned as network slices with sequences of VNFs, in order to guarantee the performance and security of their continuous data and control flows. In this paper we study the problems of delay-aware network slicing for multicasting traffic of IoT applications in edge networks. We first propose exact solutions by formulating the problems into Integer Linear Programs (ILPs). We further devise an approximation algorithm with an approximation ratio for the problem of delay-aware network slicing for a single multicast slice, with the objective to minimize the implementation cost of the network slice subject to its delay requirement constraint. Given multiple multicast slicing requests, we also propose an efficient heuristic that admits as many user requests as possible, through exploring the impact of a non-trivial interplay of the total computing resource demand and delay requirements. We then investigate the problem of delay-oriented network slicing with given levels of delay guarantees, considering that different types of IoT applications have different levels of delay requirements, for which we propose an efficient heuristic based on Reinforcement Learning (RL). We finally evaluate the performance of the proposed algorithms through both simulations and implementations in a real test-bed. Experimental results demonstrate that the proposed algorithms is promising

    Virtual network function placement and routing for multicast service chaining using merged paths

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    This paper proposes a virtual network function placement and routing model for multicast service chaining based on merging multiple service paths (MSC-M). The multicast service chaining (MSC) is used for providing a network-virtualization based multicast service. The MSC sets up a multicast path, which connects a source node and multiple destination nodes. Virtual network functions (VNFs) are placed on the path so that users on the destination nodes receive their desired services. The conventional MSC model configures multicast paths for services, each of which has the same source data and the same set of VNFs in a predefined order. In the MSC-M model, if paths of different services carry the same data on the same link, these paths are allowed to be merged into one path at that link, which improves the utilization of network resources. The MSC-M model determines the placement of VNFs and the route of paths so that the total cost associated with VNF placement and link usage is minimized. The MSC-M model is formulated as an integer linear programming (ILP) Problem. We prove that the decision version of VNF placement and routing problem based on the MSC-M model is NP-complete. A heuristic algorithm is introduced for the case that the ILP problem is intractable. Numerical results show that the MSC-M model reduces the total cost required to accommodate service chaining requests compared to the conventional MSC model. We discuss directions for extending the MSC-M model to an optical domain

    Multicast Aware Virtual Network Embedding in Software Defined Networks

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    The Software Defined Networking (SDN) provides not only a higher level abstraction of lower level functionalities, but also flexibility to create new multicast framework. SDN decouples the low level network elements (forwarding/data plane) from the control/management layer (control plane), where a centralized controller can access and modify the configuration of each distributed network element. The centralized framework allows to develop more network functionalities that can not be easily achieved in the traditional network architecture. Similarly, Network Function Virtualization (NFV) enables the decoupling of network services from the underlying hardware infrastructure to allow the same Substrate (Physical) Network (SN) shared by multiple Virtual Network (VN) requests. With the network virtualization, the process of mapping virtual nodes and links onto a shared SN while satisfying the computing and bandwidth constraints is referred to as Virtual Network Embedding (VNE), an NP-Hard problem. The VNE problem has drawn a lot of attention from the research community. In this dissertation, we motivate the importance of characterizing the mode of communication in VN requests, and we focus our attention on the problem of embedding VNs with one-to-many (multicast) communication mode. Throughout the dissertation, we highlight the unique properties of multicast VNs and explore how to efficiently map a given Virtual Multicast Tree/Network (VMT) request onto a substrate IP Network or Elastic Optical Networks (EONs). The major objective of this dissertation is to study how to efficiently embed (i) a given virtual request in IP or optical networks in the form of a multicast tree while minimizing the resource usage and avoiding the redundant multicast tranmission, (ii) a given virtual request in optical networks while minimizing the resource usage and satisfying the fanout limitation on the multicast transmission. Another important contribution of this dissertation is how to efficiently map Service Function Chain (SFC) based virtual multicast request without prior constructed SFC while minimizing the resource usage and satisfying the SFC on the multicast transmission

    On the Orchestration and Provisioning of NFV-enabled Multicast Services

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    The paradigm of network function virtualization (NFV) with the support of software-defined networking has emerged as a prominent approach to foster innovation in the networking field and reduce the complexity involved in managing modern-day conventional networks. Before NFV, functions, which can manipulate the packet header and context of traffic flow, used to be implemented at fixed locations in the network substrate inside proprietary physical devices (called middlewares). With NFV, such functions are softwarized and virtualized. As such, they can be deployed in commodity servers as demanded. Hence, the provisioning of a network service becomes more agile and abstract, thereby giving rise to the next-generation service-customized networks which have the potential to meet new demands and use cases. In this thesis, we focus on three complementary research problems essential to the orchestration and provisioning of NFV-enabled multicast network services. An NFV-enabled multicast service connects a source with a set of destinations. It specifies a set of NFs that should be executed at the chosen routes from the source to the destinations, with some resources and ordering relationships that should be satisfied in wired core networks. In Problem I, we investigate a static joint traffic routing and virtual NF placement framework for accommodating multicast services over the network substrate. We develop optimal formulations and efficient heuristic algorithms that jointly handle the static embedding of one or multiple service requests over the network substrate with single-path and multipath routing. In Problem II, we study the online orchestration of NFV-enabled network services. We consider both unicast and multicast NFV-enabled services with mandatory and best-effort NF types. Mandatory NFs are strictly necessary for the correctness of a network service, whereas best-effort NFs are preferable yet not necessary. Correspondingly, we propose a primal-dual based online approximation algorithm that allocates both processing and transmission resources to maximize a profit function that is proportional to the throughput. The online algorithm resembles a joint admission mechanism and an online composition, routing, and NF placement framework. In the core network, traffic patterns exhibit time-varying characteristics that can be cumbersome to model. Therefore, in Problem III, we develop a dynamic provisioning approach to allocate processing and transmission resources based on the traffic pattern of the embedded network service using deep reinforcement learning (RL). Notably, we devise a model-assisted exploration procedure to improve the efficiency and consistency of the deep RL algorithm

    Resilient scalable internet routing and embedding algorithms

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    Efficient NFV-Enabled Multicasting in SDNs

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    IEEE Multicasting is a fundamental functionality of many network applications, including online conferencing, event monitoring, video streaming, and so on. To ensure reliable, secure and scalable multicasting, a service chain that consists of network functions (e.g., firewalls, Intrusion Detection Systems (IDSs), and transcoders) usually is associated with each multicast request. We refer to such a multicast request with service chain requirement as an NFV-enabled multicast request. In this paper, we study NFV-enabled multicasting in a Software- Defined Network (SDN) with an aim to maximize network throughput while minimizing the implementation cost of admitted NFV-enabled multicast requests, subject to network resource capacity, where the implementation cost of a request consists of its computing resource consumption cost in servers and its network bandwidth consumption cost when routing and processing its data packets in the network. To this end, we first formulate two NFV-enabled multicasting problems with and without resource capacity constraints and one online NFV-enabled multicasting problem.We then devise two approximation algorithms with an approximation ratio of 2M for the NFV-enabled multicasting problems with and without resource capacity constraints, if the number of servers for implementing the service chain of each request is no greater than a constant M (≥1). We also study dynamic admissions of NFV-enabled multicast requests without the knowledge of future request arrivals with the objective to maximize the network throughput, for which we propose an efficient heuristic, and for a special case of dynamic request admissions, we devise an online algorithm with a competitive ratio of O(log n) for it when M = 1, where n is the number of nodes in the network. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed algorithms are promising and outperform existing heuristics

    QoE management of HTTP adaptive streaming services

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