Multicast Requests Research Articles

Provably efficient security-aware service function tree composing and embedding in multi-vendor networks

Multicast greatly benefits many emerging applications such as federated learning, metaverse, and data warehouse. Recently, due to frequent cyber-attacks, multicast services have tended to request rigorous security agreements, which likely differ among the destinations. To meet such agreements, one can employ security-aware service functions (SFs) to construct the security-aware SF tree (S-SFT) for multicast services. A security-aware SF can be provided by various vendors with diverse configurations and implementation costs. The multi-configured SFs and the various security agreements will add significant complexity to the deployment process of the security-aware multicast request. In this work, for the first time, we study how to effectively compose and embed an S-SFT over the network with multiple vendors. We formulate the problem of security-aware SFT composing and embedding. We develop a new technique called cost-security-centrality (CSC) based on the pigeonhole’ s principle and propose a heuristic algorithm called CSC-based S-SFT deployment (CSC-SD). Via thorough mathematical proofs, we show that CSC-SD is logarithm approximate. Extensive simulations show that CSC-SD significantly outperforms the benchmarks and reveal that more function sharing facilitates saving implementation cost, but more routing sharing does not indicate saving routing cost.

Coordinating Multiple Light-Trails in Multicast Elastic Optical Networks With Adaptive Modulation

Optical multicasting has been considered resource efficient for multicast services. Light-tree and light-trail are two technologies that support optical multicasting while the former requires many splitters and thus experiences significant power loss. In this paper, we consider using the light-trail technology for the accommodation of multicast requests in elastic optical networks with adaptive modulation. For better spectrum efficiency, we consider accommodating each multicast by multiple light-trails. We formulate the problem by Mixed Integer Linear Programming (MILP) and propose efficient heuristic algorithms. For the impact of accommodation sequence on the algorithm performance, apart from the traditional sequence among different requests, we consider an additional sequence among the destinations of a multicast. For efficient multicast accommodation, we propose several strategies and compare their performances through a range of cases. To avoid a destination occupying excessive resources in certain cases of joining multiple light-trails, we propose an efficient algorithm to delete some duplicated destinations. Numerical results show that the proposed heuristic algorithms significantly outperform a benchmark algorithm and one performs close to the optimal MILP. Also, the algorithm for deleting certain destination replicas largely reduces the spectrum and transmitter usages, up to 41% and 20% for the cases considered, respectively.

Link-aware distributed steiner sub-tree scheme for all-optical multicasting in elastic optical datacenter networks

The distributed sub-tree (DST) scheme in the elastic optical datacenter network (EODN) can use multiple datacenters (DCs) to jointly serve a multicast request. By allocating some suitable DCs to the multicast request, the route length can be reduced, thereby reducing resource consumption and decreasing blocking probability. However, DST scheme also has a defect that, all source nodes of multicast requests are hosted in the DCs, which leads to that links connecting the DCs nodes have higher usage than other links, and the resulting network bottleneck makes the network performance declines sharply. In this paper, we propose a link-aware cost calculation (LA-CC) formula and a link-aware distributed steiner sub-tree (LA-DSST) algorithm to make the usage of all links as balanced as possible, thus reducing the blocking probability caused by network bottlenecks. Simulation results show that our proposed algorithm significantly improves performance with the lowest blocking probability compared to existing well-performing algorithms.

Routing and Spectrum Allocation Using Elastic Optical Network.

With the rapid growth of cloud data, the internet of things, social media applications, high-end video streaming, etc WDM[3][3] is slowly becoming insufficient for all these future growths. The elastic optical network is slowly becoming the solution for these problems in the fiber-optic network. It can provide flexibility in the spectrum assignment and can even provide greater bandwidth. But with all these benefits come the problem of routing and spectrum allocation(RSA). In this problem, the frequency slots should be allocated to maintain continuity, contiguity, and nonoverlapping constraints. The paper explores the feasible way of solving the problem so that requests can be transferred through the network with minimum cost production.. algorithms that can solve RSA problem with static traffic demand. So, in this paper we incorporate a layered approach to de-sign efficiently integrated MC-RSA for serving multicast requests in EONs. This algorithm decomposes the physical structure of the graph into several layered auxiliary graphs according to the given multicast request . Then depending on the bandwidth we create a multicast light tree . It solves the routing and spectrum allocation problem by first finding the k-shortest path in the first available contiguous slots. However, the main goal is to allocate the connection request list that we have implemented only if there are available contiguous slots. We have tried to decode the algorithm and make it as efficient as possible.

MT3A : A Novel Multicast Routing, Spectrum and Modulation-Level Assignment in Elastic Optical Networks

Elastic Optical Networks (EONs) were introduced to eliminate the challenges of Wavelength Division Multiplexing (WDM) networks. EONs can improve resource efficiency compared to WDM networks. The issue of resource allocation in EONs is a major challenge for the optimal use of maximum network capacity for each communication demand. On the other hand, multicasting is defined as the transfer of data from one source to multiple destinations and it is one of the most effective methods based on cost and efficiency in order to provide flow in computer networks. In this article, we present a novel Multicast Two-part Two-path Two-direction Allocation (MT3A) scheme in order to routing, spectrum and modulation-level assignment for dynamic multicast traffic in EONs. With this scheme, each sub-request related to a multicast request is divided into two parts considering the property of Sliceable Bandwidth Variable Transponders (SBVTs) and is set up in two different directions in two different light-paths. By using the MT3A scheme compared to comparative schemes, with increasing the data rate, Bandwidth Blocking Probability (BBP) is reduced, which is very important due to increasing demand for contents with high data rate.

On Efficient Delay-Aware Multisource Multicasting in NFV-Enabled Softwarized Networks

To comply with security and performance policies, multicast communication requires inline service that chains an ordered sequence of virtualized network functions (VNFs) with an emerging paradigm of network function virtualization (NFV). As many-to-many multicast pattern is widely used especially in current MEC, multimedia and big data industries, in this paper we focus on multi-source NFV-enabled multicasting in software-defined networks (SDN). By jointly investigating VNF placement and multicast tree routing strategy, it is envisioned to construct service function tree with minimum network resource expenditure while yielding lower delay. We explore this problem in static and online scenarios individually. In static situation with a bunch of multicast requests to be served, a column generation based computing model is first formulated, based on which an approximation algorithm MDNM that leverages logic of Viterbi and puts emphasis on resource optimization and segmental delay satisfaction is developed. In online situation with a single incoming request, another ILP model to enhance VNF instance reuse is established. Then, SVM algorithm giving importance to source determination and VNF instance consolidation is designed to efficiently construct a service function tree with minimum resource usage and delay. Simulation results show that the gap between each of the two proposed algorithms and their respective ILP models is marginal, and both MDNM and SVM outperform the state-of-art work.

Partial-Failure Segregated Spectrum Assignment for Multicast Traffic in Flex-Grid Optical Networks

In this paper, we propose a new algorithm called the partial-failure segregated multicasting routing and spectrum assignment (PFS MRSA) algorithm to improve the service blocking performance of the multicast transmission in flex-grid optical networks (FGONs). By segregating one failure destination leaf-node from a blocked multicast request and accommodating the failure destination leaf-node and the remaining multicast request independently, the success probability of accommodating the originally blocked multicast request can be greatly increased. In this way, the proposed PFS MRSA algorithm can effectively reduce the service blocking probability for the multicast services in FGONs. Simulation results show that the proposed PFS MRSA algorithm achieves significant reduction in service blocking probability when compared with the conventional MRSA algorithms, and such reduction can even reach 100% in some scenarios with low traffic load.

QoS Aware Multicast Routing Protocol for Video Transmission in Smart Cities

In recent years, Software Defined Networking (SDN) has become an important candidate for communication infrastructure in smart cities. It produces a drastic increase in the need for delivery of video services that are of high resolution, multiview, and large-scale in nature. However, this entity gets easily influenced by heterogeneous behaviour of the user's wireless link features that might reduce the quality of video stream for few or all clients. The development of SDN allows the emergence of new possibilities for complicated controlling of video conferences. Besides, multicast routing protocol with multiple constraints in terms of Quality of Service (QoS) is a Nondeterministic Polynomial time (NP) hard problem which can be solved only with the help of metaheuristic optimization algorithms. With this motivation, the current research paper presents a new Improved Black Widow Optimization with Levy Distribution model (IBWO-LD)-based multicast routing protocol for smart cities. The presented IBWO-LD model aims at minimizing the energy consumption and bandwidth utilization while at the same time accomplish improved quality of video streams that the clients receive. Besides, a priority-based scheduling and classifier model is designed to allocate multicast request based on the type of applications and deadline constraints. A detailed experimental analysis was carried out to ensure the outcomes improved under different aspects. The results from comprehensive comparative analysis highlighted the superiority of the proposed IBWO-LD model over other compared methods.

Nonblocking conditions for a multicast WSW architecture based on subtree scheme for elastic optical networks

Elastic optical networks (EONs) are a promising solution for future high-speed optical communication, and multicasting in EONs can efficiently support many emerging services. Different schemes, such as path, tree and subtree schemes, serve multicast services. In this paper, we consider a three-stage wavelength-space-wavelength (WSW) node architecture, which adopts wavelength switches in the first and last stages and space switches in the middle stage, and uses the path scheme to accommodate multicast requests, as proposed in an earlier work for elastic optical networks. We also enhance the WSW architecture to serve multicast requests in a more spectrum-efficient way, namely, using the subtree scheme, by making each switch support multicast capacity, and we term the resulting architecture M-WSW. To the best of our knowledge, this is the first study of the WSW architecture using the subtree scheme to support multicast capacity. We prove the sufficient and necessary conditions, in terms of the number of middle switches, of the M-WSW architecture for being strictly nonblocking (SNB) and wide-sense nonblocking (WSNB) under the two routing algorithms proposed in this paper. Our results show that the number of middle switches required for the architecture to be WSNB under each of the two proposed routing algorithms is much less than the number of middle switches required for SNB, especially when the SNB results meet the boundary condition.

Cost-adaptive multi-class multicast service aggregation based on distributed sub-trees in elastic optical data center networks

Multicast provisioning is important for supporting applications such as data backup and cloud computing in elastic optical data center networks (EODCNs). As the traffic demand from these applications is quickly increasing, it is important to reduce the resource usage and implement cost-effective multicasting. By mapping multiple traffic flows into a single light-tree, the light-tree-based multicast service aggregation can reduce the number of required transceivers while accommodating many multicast requests. However, it may increase the spectrum usage, and it is not always feasible because some subscription-based or secure multicast services in the network should be sent only to authorized users. In this paper, we focus on the problem of routing, modulation level selection, spectrum, and transceiver assignment for multicast services with different security levels. We study potential performance gains resulting from applying a distributed sub-tree scheme to multi-class multicast service aggregation, realizing reduced overall cost. By formulating the mathematical models using an integer linear program (ILP), we obtain results for a small-scale network. We also propose a heuristic algorithm for large-scale networks, and results show that our proposed algorithm can be beneficial in terms of both spectrum and transceiver utilization in EODCNs.

Delay-Sensitive Multi-Source Multicast Resource Optimization in NFV-Enabled Networks: A Column Generation Approach

Telecommunication networks are currently realizing more-huge-than-ever data demands from subscribers all over the world. Due to the ongoing pandemic, nearly all businesses have adapted working models with remote operations. People engaged with major industries, e.g., academia, health and municipalities are utilizing online platforms to carryout their routine tasks. This indeed shifts the attention from one-to-one (unicast) communication to one-to-many (multicast) and many-to-many (multi-source multi-destination) communications. Network operators are facing increased pressure to provide quick responses in order to satisfy the bandwidth hungry and time sensitive user demands. This can only be done by enhancing deployability as well as manageability of the services. Network Function Virtualization (NFV) provides a transformation of traditional proprietary network designs to a more agile and software based environment in order to achieve flexible deployments, reduced setup costs and less-time-to-market for the new services which is very much needed in the current scenarios. Previous studies on NFV-enabled multicast problem either proposed Integer Linear Program (ILP) models, that are pretty unscalable, or heuristic-based techniques that do not guarantee good quality of the solutions obtained. In this article, we propose an NFV multicast resource optimization model exploiting the use of multiple sources and considering the end-to-end delay and bandwidth requirements. Herein, we propose a novel Dantzig-Wolfe (DW) decomposition model that tackles the complexity of the problem by breaking it down into a master problem and several pricing problems. We compare the DW approach with the ILP and heuristic methods and demonstrate that our approach achieves near to optimal solution (in comparison to heuristic based methods) much faster than ILP. We also study the dynamic admission of NFV-enabled multicast requests by solving the problem in an online manner using the batch processing of requests. We then evaluate the performance of the proposed algorithms through extensive simulations and demonstrate that proposed algorithms are promising and outperform existing solutions.

Multicast Routing Model to Minimize Number of Flow Entries in Software-Defined Network

Software-defined network (SDN) is a network that the centralized SDN controller stores flow entries in the flow table of each SDN switch and controls packet flows as instructed by the stored flow entries. When a multicast service is provided in an SDN, the SDN controller stores a multicast entry dedicated for a multicast group in each SDN switch. It is necessary to suppress the number of flow entries required to set up a multicast tree due to the limited capacity of the flow table. In a conventional research, a multicast routing model that suppresses the number of multicast entries in one multicast request by replacing a part of them with unicast entries has been devised. However, since this conventional model individually determines a multicast tree route for each request, unicast entries configured for the same receiver are distributed in various SDN switches when multiple multicast services are requested. As a result, there is still the possibility of improving the reduction of the number of flow entries. In this paper, we propose a multicast routing model for multiple multicast requests that minimizes the number of flow entries. This proposed model determines multiple multicast tree routes simultaneously so that a unicast entry configured for the same receiver and stored in the same SDN switch is shared by multicast trees. We formulate the proposed model as an Integer Linear Programming (ILP) problem. Numerical results show that the proposed model reduces the required number of flow entries compared to the conventional model.

Dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network

Aiming at the problem of dynamic multicast service protection in multi-domain optical network, this paper proposes a dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network. The algorithm uses the minimum cost spanning tree strategy and fuzzy game theory. First, it virtualizes two planes to calculate the multicast tree and the multicast protection tree respectively. Then, it performs a fuzzy game to form a cooperative alliance to optimize the path composition of each multicast tree. Finally, it generates a pair of optimal multicast work tree and multicast protection tree for dynamic multicast services. The time complexity of the algorithm is O(k3m2n), where n represents the number of nodes in the networks, k represents the number of dynamic multicast requests, and m represents the number of destination nodes for each multicast request. The experimental results show that the proposed algorithm reduces significantly the blocking rate of dynamic multicast services, and improves the utilization of optical network resources within a certain number of dynamic multicast request ranges.

Efficient Algorithms for Delay-Aware NFV-Enabled Multicasting in Mobile Edge Clouds With Resource Sharing

Stringent delay requirements of many mobile applications have led to the development of mobile edge clouds, to offer low latency network services at the network edges. Most conventional network services are implemented via hardware-based network functions, including firewalls and load balancers, to guarantee service security and performance. However, implementing hardware-based network functions usually incurs both a high capital expenditure (CAPEX) and operating expenditure (OPEX). Network Function Virtualization (NFV) exhibits a potential to reduce CAPEX and OPEX significantly, by deploying software-based network functions in virtual machines (VMs) on edge-clouds. We consider a fundamental problem of NFV-enabled multicasting in a mobile edge cloud, where each multicast request has both service function chain and end-to-end delay requirements. Specifically, each multicast request requires chaining of a sequence of network functions (referred to as a service function chain) from a source to a set of destinations within specified end-to-end delay requirements. We devise an approximation algorithm with a provable approximation ratio for a single multicast request admission if its delay requirement is negligible; otherwise, we propose an efficient heuristic. Furthermore, we also consider admissions of a given set of the delay-aware NFV-enabled multicast requests, for which we devise an efficient heuristic such that the system throughput is maximized, while the implementation cost of admitted requests is minimized. We finally evaluate the performance of the proposed algorithms in a real test-bed, and experimental results show that our algorithms outperform other similar approaches reported in literature.

Time based resource-consumption-aware spectrum assignment for multicast traffic in elastic optical networks

Abstract Given the importance of multicast traffic in current optical networks, many effective multicast routing and spectrum assignment (MRSA) algorithms have been proposed to achieve efficient multicast transmission in elastic optical networks (EONs). However, most of these MRSA algorithms were focus on optimizing only the spectrum resources allocated to multicast service requests, but ignored some fragmented spectrum resources remained after spectrum allocation. Although some fragment-aware MRSA algorithms were proposed for EONs to restrain the fragmented spectrum generated in provisioning multicast transmission, they could hardly precisely compute the amount of the fragmented resources while optimizing the allocated resources for the multicast transmission in EONs. This is because that the fragmented and the allocated spectrum resources always have different duration characteristics. In this paper, we propose a time-based composite-consumption-aware (TCCA) MRSA algorithm to optimize both the fragmented and the allocated resources consumed by the multicast transmission in EONs. By additionally taking the holding time of each multicast service request into account, the proposed algorithm can comprehensively optimize both the fragmented and the allocated resource consumption for the multicast transmission in EONs. Since the comprehensive resource consumption, including both the fragmented and the allocated resource consumption, is optimized by the proposed TCCA algorithm, more available resources can be remained for the subsequent multicast requests, which can increase the request blocking performance in EONs. Simulation results verify that the proposed algorithm can reduce the comprehensive resource consumption for the multicast transmission in EONs with low request blocking probability.

A Virtual Network Customization Framework for Multicast Services in NFV-Enabled Core Networks

The paradigm of network function virtualization (NFV) with the support of software defined networking (SDN) emerges as a promising approach for customizing network services in fifth generation (5G) networks. In this paper, a multicast service orchestration framework is presented, where joint traffic routing and virtual network function (NF) placement are studied for accommodating multicast services over an NFV-enabled physical substrate network. First, we investigate a joint routing and NF placement problem for a single multicast request accommodated over a physical substrate network, with both single-path and multipath traffic routing. The joint problem is formulated as a mixed integer linear programming (MILP) problem to minimize the function and link provisioning costs, under the physical network resource constraints, flow conservation constraints, and NF placement rules; Second, we develop an MILP formulation that jointly handles the static embedding of multiple service requests over the physical substrate network, where we determine the optimal combination of multiple services for embedding and their joint routing and placement configurations, such that the aggregate throughput of the physical substrate is maximized, while the function and link provisioning costs are minimized. Since the presented problem formulations are NP-hard, low complexity heuristic algorithms are proposed to find an efficient solution for both single-path and multipath routing scenarios. Simulation results are presented to demonstrate the effectiveness and accuracy of the proposed heuristic algorithms.

Throughput Maximization of NFV-Enabled Multicasting in Mobile Edge Cloud Networks

Mobile Edge Computing (MEC) reforms the cloud paradigm by bringing unprecedented computing capacity to the vicinity of end users at the mobile network edge. This provides end users with swift and powerful computing and storage capacities, energy efficiency, and mobility- and context-awareness support. Furthermore, Network Function Virtualization (NFV) is another promising technique that implements various network functions for many applications as pieces of software in servers or cloudlets in MEC networks. The provisioning of virtualized network services in MEC can improve user service experiences, simplify network service deployment, and ease network resource management. However, user requests arrive dynamically and different users demand different amounts of resources, while the resources in MEC are dynamically occupied or released by different services. It thus poses a significant challenge to optimize the performance of MEC through efficient computing and communication resource allocations to meet ever-growing resource demands of users. In this paper, we study NFV-enabled multicasting that is a fundamental routing problem in an MEC network, subject to resource capacities on both its cloudlets and links. Specifically, we first devise an approximation algorithm for the cost minimization problem of admitting a single NFV-enabled multicast request. We then develop an efficient algorithm for the throughput maximization problem for the admissions of a given set of NFV-enabled multicast requests. We third devise an online algorithm with a provable competitive ratio for the online throughput maximization problem when NFV-enabled multicast requests arrive one by one without the knowledge of future request arrivals. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising.

Scheduling Dynamic Multicast Requests in Advance Reservation Environment for Enterprise Video Conferencing Systems

In an enterprise video conferencing system, the enterprise network can be shared by hundreds of video conferences. On the other hand, participants may not arrive at the same time and stay until the end of the conference. The abilities to reserve resources in advance, as well as effective dynamic multicast when participants can join and leave the conference at any time, are essential in the distributed multi-party video conferencing systems. However, the effective advance reservation strategies of the dynamic multicast requests for a heavy traffic case still remains open. In this paper, we investigate the problem of Maximizing the number of admitted Dynamic Multicast requests in the Advance Reservation environment (MDMAR) for the enterprise video conferencing system. We take two path schemes of a fixed path and variable paths, as well as a heterogeneous bandwidth reservation model into account. Firstly, we prove that the MDMAR problem is NP-complete and formulate it mathematically as an integer linear program (ILP) for small networks. Then, we develop greedy algorithms and simulated annealing (SA) algorithms for enterprise networks. Comparative simulations are performed to evaluate the heuristic algorithms for both small networks and enterprise networks. We find that the SA algorithms can provide within 6% lower optimal solutions than the ILP algorithms for our small network, and up to 10% improvement over the greedy algorithms for the large campus or enterprise network.

A Delay and Energy Efficient Multicast Routing Protocol using IWO and MOLO Algorithm for Vehicular Networks

Vehicular networks are significantly improving wireless communication network which provides an intelligent transportation system services among faster moving vehicles with internet and brings safety and comfort drive. From a single source vehicle the multicast routing protocols delivers multicast messages to all members of the multicast group by means of multi-hop communication. Increasing the density of vehicles results in channel overload, which increases the probability of data collision; hence reduction in successful received data will increase the delay. Therefore, delay and energy consumption are the major constraints that should affect the performance of routing. In this paper we suggest a delay and energy efficient multicast routing (DEMR) protocol for vehicular network using a hybrid machine learning algorithm. The DEMR protocol consists of four layers; are vehicle layer, fog layer, OpenFlow switch layer, and SDN controller layer. Moreover, to partition the vehicle layer, and select the optimal multicast path based on multiple constraints improved weed optimization (IWO) algorithm is proposed. IWO algorithm separates the multicast request into emergency, common and police requests. We design a multi-objective lion optimization (MOLO) algorithm among fog nodes for resource management, which increases the utilization of resources in fog layer and decrease the response time of multicast session request. MOLO algorithm removes the unnecessary flow table and session table entries in the controller. The DEMR protocol is implemented in Network Simulator (NS3) tool and simulation results are compared with the protocols as EEMSFV, MABC, and CVLMS. From the simulation results we conclude that the DEMR algorithm is better than EEMSFV, MABC and CVLMS in terms of transmission ratio, overhead load, average end to end delay, packet loss ratio and, energy consumption.

Virtual network mapping for multicast requests over elastic optical networks

Virtualization is becoming a promising method for supporting various emerging applications, and achieving efficient embedding of virtual requests in elastic optical networks (EONs) has become a popular issue in network virtualization research. Meanwhile, multicast request mapping of EONs has become more challenging than that of conventional optical networks. Since the problem of minimizing the embedding cost and redundant transmission in multicast request embedding is NP-hard, we propose an efficient heuristic algorithm, called the virtual optical multicast-tree embedding algorithm based on the node correlation degree (VOME-NCD) to address the problem of low transmission redundancy. When embedding the virtual optical multicast request, it is based on the mapping of the correlation degree of each virtual node. Through extensive simulations, we demonstrate that VOME-NCD outperforms other embedding solutions in terms of the embedding cost, blocking probability, redundancy cost, and router hop count.