Multicast Path Research Articles

A Distributed Multicast QoS Routing Construction Approach in Information-Centric Networking

Many applications suitable for multicast transmission, such as video conferencing and live e-commerce, demand high Quality of Service (QoS) and require data delivery to be completed within specified delay constraints. Some methods have been proposed for constructing delay-constrained multicast routing based on network state. However, obtaining precise network latency can be challenging, resulting in inaccuracies in delay-constrained routing calculations and, ultimately, the inability to meet application requirements. Additionally, many methods engage in an indiscriminate exploration of potential paths in the network, causing significant message processing overhead. This paper proposes an Information-Centric Networking (ICN)-based approach for delay-constrained multicast routing. Our method dynamically constructs multicast paths from tree nodes to receivers based on real-time path status detection during the join message propagation phase. Additionally, we present a method for acquiring neighborhood state information to facilitate real-time routing decisions. To curtail indiscriminate path exploration, our approach uses the ICN Name Resolution System (NRS) to obtain and select potential optimal tree nodes. For this purpose, we design a multicast service registration and resolution mechanism using the ICN Name Resolution System (NRS). Simulation results indicate that our approach exhibits a higher success ratio and concurrently incurs lower message processing overhead than some other methods, particularly in situations with stringent delay constraints.

AC-SDVN: An Access Control Protocol for Video Multicast in Software Defined Vehicular Networks

The way to use limited bandwidth resources to achieve high-quality video services in vehicular networks is an important research topic. A large number of studies have shown that the fast-growing field of software defined networking (SDN) can provide solutions to the problems encountered by traditional IP networks when implementing video multicasting. However, there is no research addressing the security issues for this scenario. In this paper, we explore the application scenarios of video multicast in software defined vehicular networks (SDVN), and propose a secure and effective access control protocol to solve multicast security issues. This protocol realizes the authentication of multicast video requesting vehicles and RSUs. According to the authentication results, the SDN controller constructs multicast paths that only reach legitimate RSUs and vehicles, and only the vehicle passing the authentication can obtain video decryption keys. The protocol resists common attacks and satisfies the security requirements in vehicular networks. In addition, the scheme supports batch verification, which reduces the time cost of authentication, and adopts broadcast encryption technology to effectively reduce the communication load. Compared with related schemes, our protocol performs better in terms of computation and communication cost, packet loss rate, and time delay.

Policy Gradient-Based Core Placement Optimization for Multichip Many-Core Systems.

As many deep neural network models become deeper and more complex, processing devices with stronger computing performance and communication capability are required. Following this trend, the dependence on multichip many-core systems that have high parallelism and reasonable transmission costs is on the rise. In this work, in order to improve routing performance of the system, such as routing runtime and power consumption, we propose a reinforcement learning (RL)- based core placement optimization approach, considering application constraints, such as deadlock caused by multicast paths. We leverage the capability of deep RL from indirect supervision as a direct nonlinear optimizer, and the parameters of the policy network are updated by proximal policy optimization. We treat the routing topology as a network graph, so we utilize a graph convolutional network to embed the features into the policy network. One step size environment is designed, so all cores are placed simultaneously. To handle large dimensional action space, we use continuous values matching with the number of cores as the output of the policy network and discretize them again for obtaining the new placement. For multichip system mapping, we developed a community detection algorithm. We use several datasets of multilayer perceptron and convolutional neural networks to evaluate our agent. We compare the optimal results obtained by our agent with other baselines under different multicast conditions. Our approach achieves a significant reduction of routing runtime, communication cost, and average traffic load, along with deadlock-free performance for inner chip data transmission. The traffic of interchip routing is also significantly reduced after integrating the community detection algorithm to our agent.

A Reverse Shortest Path Tree-Based Multicast Joining Node Selection Method

Network layer multicast is a powerful method for transmitting data from sources to multiple group members. When joining a multicast group, a group member first sends a request to a designated router (DR). Then, the DR selects a node in the existing multicast tree (known as a multicast joining node, or MJN) to establish a multicast distribution path from the MJN to itself. The MJN selection method runs on the DR and has a significant impact on the distribution of the multicast tree, that directly affects the load distribution in the network. However, the current MJN selection method cannot effectively detect the load status of the downlink multicast path in the case of asymmetric routing, leading to network congestion and limiting the number of multicast groups that the network can accommodate (multicast capacity). To solve this problem, we propose an MJN selection method based on the reverse shortest path tree (RSPT). RSPT can effectively detect the load status of downlink multicast paths in case of routing asymmetry. Based on the detection results of RSPT, DR can select the MJN with the lowest path load to join the multicast tree. Our experimental results indicate that compared to existing multicast methods, our method has a lower cost and delay, and can effectively balance the network load in the case of asymmetric routing, increasing multicast capacity by more than two times.

URMP: using reconfigurable multicast path for NoC-based deep neural network accelerators

URMP: using reconfigurable multicast path for NoC-based deep neural network accelerators

QoS-VNS-CS: QoS constraints Core Selection Algorithm based on Variable Neighborhood Search Algorithm

Within the development of network multimedia technology, more and more real-time multimedia applications arrive with the need to transmit information using multicast communication. Multicast IP routing is an important topic, covering both theoretical and practical interest in different networks layers. In network layer, there are several multicast routing protocols using multicast routing trees different in the literature. However PIM-SM and CBT protocols remains the most used multicast routing protocols; they propose using a shared Core-based Tree CBT. This kind of tree provides efficient management of multicast path in changing group memberships, scalability and performance. The prime problem concerning construction of a shared tree is to determine the best position of the core. QoS-CS’s problem (QoS constraints core Selection) consists in choosing an optimal multicast router in the network as core of the Shared multicast Tree (CBT) within specified QoS constraints associated. The choice of this specific router, called RP in PIM-SM protocol and core in CBT protocol, affects the structure of multicast routing tree, and therefore influences performances of both multicast session and routing scheme. QoS-CS is an NP complete problem need to be solved through a heuristic algorithm, in this paper, we propose a new core Selection algorithm based on Variable Neighborhood Search algorithm and new CMP fitness function. Simulation results show that good performance is achieved in multicast cost, end-to-end delay, tree construction delay and others metrics.

An Identity-Based Encryption Method for SDN-Enabled Source Routing Systems

In this study, we consider endpoints communicating over a software-defined networking (SDN)-based architecture using source routing, i.e., packets are routed through a path selected by the packet sender, and we provide a security solution that enforces the selected path. In particular, our solution allows a sender to select the path that a packet should go through using a constant-size cryptographic construction which is referred to as the authenticator. A recipient can examine an authenticator and verify that the received packet has followed the path selected by the sender. Additionally, any intermediate “programmable” switch can verify whether or not it is included in the path of a packet. Our solution can be used even for paths that include multiple recipients (e.g., multicast paths), as well as multiple parallel paths (e.g., multipath transmissions). We implement our solution by leveraging identity-based encryption (IBE), so it can be used by any sender that knows the identifiers of the links that compose the desired path, i.e., information that the sender usually already knows as part of the source routing protocol. Our solution is realistic since it can be implemented over a variety of platforms with tolerable overhead.

Fault-tolerant multicast routing in infocommunication network with path and bandwidth protection

The article presents and investigates a flow-based mathematical model of fault-tolerant multicast routing. Under the proposed mathematical model, the technical task of fault-tolerant multicast routing was reduced to the Boolean programming optimization problem. The mathematical model was based on linear optimality criterion and constraints represented by the conditions of single-path routing, flow conservation, multicast connectivity, and prevention of overload and looping. The routing variables that guided the multicast routing process were Boolean. The optimal primary and backup paths are calculated by implementing path and bandwidth protection schemes within the model for each multicast flow. The restrictions on routing variables introduced into the model were responsible for protecting the route and bandwidth. The optimality criterion in determining the optimal and backup multicast paths at the level of routing metrics considered the network topology and links bandwidth. The additive nature of the criterion focused on finding paths that included a minimum number of communication links. According to the selected routing metric, a feature of the model is to ensure priority in assigning the primary route of the path that had a shorter «length» than the backup path. The analysis of the obtained solutions confirmed their operability under the specified protection scheme’s implementation and their optimality according to variants of the used routing metrics. The proposed mathematical model can be used to develop the fault-tolerant multicast routing protocols of multimedia flows.

Multicast tree construction algorithm for dynamic traffic on software defined networks

Dynamic traffic of multicast communication in the Software Defined Network environment focused less though it is more natural and practical. In multicast communication, the traffic is dynamic due to the dynamic group memberships (i.e., participants join and leave the group anytime), which are not explored much in the previous research works. The multicast in dynamic traffic requires a method to handle dynamic group membership and minimum tree alteration for every join and leave of participants from the multicast group. This paper proposes a multicast tree construction algorithm, which considers receiving devices and network capability as base parameters to construct the multicast path. The proposed routing method uses Dijkstra’s Shortest Path algorithm for initial tree formation, identifies a multicast path, and processes the Shortest Path Tree to reduce the overall hop count and path cost. The multicast tree generated by the proposed enables the dynamic join and leaves of participating devices with reduced tree alteration using more common paths to reach the devices. The implementation and results show that the proposed method works efficiently in resource utilization with a reduced hop count and quality for multicast communication in static and dynamic scenarios. Also, the results demonstrate that the proposed method generates a stable common path for multicast communication.

Brain Storm Water Optimisation-Driven Secure Multicast Routing and Route Maintenance in IoT

In several Internet of Things (IoT) applications, messages are disseminated to some objects or nodes based on multicast transmissions. However, previous multicast routing schemes in IoT focussed mainly on the ad-hoc sensor network, but they are not robust and responsive in the IoT environment. Hence, this paper introduces the multicast routing protocol based on the proposed optimisation algorithm, named Brain Storm Water Optimisation (BSWO), in the IoT network. By the multicast routing protocol, the multicast path is designed from a multicast source node to various destinations. The multicast source node forwards packet to multiple destinations simultaneously. Initially, the nodes in the IoT network are simulated together and perform the multicast routing process effectively using the proposed optimisation framework. The multicast routing protocol performs the multicast routing mechanism using the multiobjective factors, such as distance, delay, energy, link-quality factor and trust. The multicast routing path is effectively chosen based on the developed BSWO through fitness measures. The proposed BSWO is designed by integrating the Brain Storm Optimisation (BSO) and Water Wave Optimisation (WWO), respectively. The path with the minimum distance is selected as an optimal path using the fitness parameters like delay, distance, trust, energy and link-quality factor. The proposed optimisation algorithm effectively performs the multicast routing mechanism by integrating the parametric features from both the optimisation algorithms. Once the multicast routing mechanism is done, the route maintenance process is carried out in the simulated IoT network to recover the link breakage. The proposed BSWO outperformed other methods with the minimal delay of 0.0682[Formula: see text]s, minimal average routing distance of 178.4[Formula: see text]m, maximal energy of 39.59[Formula: see text]J, maximal throughput of 87.75% and maximal trust of 90%, respectively.

Delay-Optimized Multicast Tree Packing in Software-Defined Networks

In traditional networks, the multicast tree packing solutions usually aim to minimize the overall multicast tree cost, which can effectively improve network accommodation capacity but is disadvantageous to fully use network resources. In this paper, we propose a delay-optimized multicast tree packing problem called delivery delay minimized multicast tree packing (DDMMTP), which aims to minimize the average source-destination delay, under constraints on the bandwidth and maximum source-destination delay, according to available network resources. A low source-destination delay is desirable because it improves the service quality, especially for time-sensitive applications. In practice, the DDMMTP is highly valuable for the software-defined network (SDN) mainly because this new network paradigm has the ability to rapidly rearrange multicast routes on demand. The DDMMTP problem is NP-hard. We solve it approximately by a batched multicast tree packing algorithm and a network accommodation capacity improvement algorithm that adjusts existing multicast paths on demand. We also propose a source-destination delay improvement algorithm to further reduce source-destination delays based on new available network resources.

Multicast routing strategy for SDN-cluster based MANET

The energy limitation and frequent movement of the mobile Ad hoc network (MANET) nodes (i.e., devices) make the routing process very difficult. The multicast routing problem is one of the NP-complete problems. Therefore, the need for a new power-aware approach to select an optimum multicast path with minimum power consumption that can enhance the performance and increase the lifetime of MANET has become urgent. Software defined network (SDN) is a new technique that can solve many problems of the traditional networks by dividing the architecture into data part and control part. This paper presents three power-aware multicast routing strategies for MANET. First one called a Reactive Multicast routing strategy for cluster based MANET by using SDN (RMCMS), second one called proactive multicast routing strategy for cluster based MANET by using SDN (PMCMS) and third one represents modification of PMCMS called M-PMCMS. Moreover, it produces a new mathematical model to build a multicast tree with minimum power consumption and takes into account the remaining power in each node. All proposed multicast strategies operate based on this mathematical model and aim to maximize the MANET lifetime by exploiting the advantages of SDN and clustering concepts. They consider the multicast tree with minimum power consumption as an optimal one. The simulation results illustrated that RMCMS is better than PMCMS, M-PMCMS, and MAODV in terms of power consumption and network overhead while M-PMCMS is the best one in terms of dropped packets ratio (DPR) and average end to end (E2E) delay.

A deadlock-free physical mapping method on the many-core neural network chip

Many-core neural network chip is widely developed and used for both the deep learning and neuromorphic computing applications. Many-core architecture brings high parallelism while makes the model-to-core mapping intractable. In order to decrease the routing time, transmission packets amount and energy consumption, along with deadlock-free performance for inter-core data movement, we formulate an optimization problem for the physical mapping under the routing strategies with point-to-point and multicast paths. The Weighted Communication of Application(WCA) is defined as the objective function and simulated annealing algorithm incorporated with two deadlock-free constraints is designed to solve the mapping problem. Multi-layer perceptron(MLP) and convolutional neural network(CNN) applications are used for evaluation. Experimental results show that the proposed algorithm is quite efficient saving the routing time and power comsumption for inter-core communication, and the routing diversity has been significantly improved, the hotspot paths are greatly reduced after optimization, compare with the baseline of zigzag and neighbor mapping.

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

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.

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.

Device-to-Device Communications Enabled Multicast Scheduling with the Multi-level Codebook in mmWave Small Cells

To keep up with the rapid growth of mobile data, there are increasing interests to deploy small cells in millimeter wave (mmWave) bands to underlay the conventional homogeneous macrocell network as well as in exploiting device-to-device (D2D) communications to improve the efficiency of the multicast service that supports content-based mobile applications. To compensate for high propagation loss in the mmWave band, high-gain directional antennas have to be employed, while it is critical to optimize multicast service in order to improve the network performance. In this paper, we develop an efficient multicast scheduling scheme for small cells in the mmWave band, called MD2D, where both D2D communications in close proximity and multi-level antenna codebook are utilized. Specifically, a user partition and multicast path planning algorithm is proposed to partition the users in the multicast group into subsets and to determine the transmission node for each subset, so as to achieve optimal utilization of D2D communications and multi-level antenna codebook. Then a multicast scheduling algorithm schedules the transmission for each subset. Furthermore, in order to optimize the network performance, the optimal choice of user partition thresholds is analyzed. Extensive simulations demonstrate that the MD2D achieves the best performance, in terms of network throughput and energy efficiency, compared with other existing state-of-the-art schemes. MD2D improves the network throughput compared with the second-best scheme by about 27%.

Controllable Multicast for Adaptive Scalable Video Streaming in Software-Defined Networks

Scalable video coding is a promising technique to enable flexible video transmission for heterogeneous terminals and varying channel throughput. However, it is challenging to perform in-network adaptation in conventional networks because the network nodes are uncontrollable and transparent for media streaming applications. Software-defined networking (SDN) is an attractive network technology that supports the applications to collaborate with network nodes to achieve intelligent and dynamic service provisioning. Against this changing network landscape, we redesign the scalable multimedia multicast streaming by exploiting the complete network knowledge of the SDN controller to enable intelligent scalable video transmission. The proposed scalable multimedia multicast streaming framework is capable of in-network identifying, processing, and manipulating the media streams. In order to achieve the in-network adaptation, we apply equivalent bandwidth theory to estimate the affordable video layers that a link may accommodate, and apply finite-state machine to implement adaptive enhancement layer switching for multicast paths. In contrast to IP multicast, the proposed method is a controllable multicast scheme, which provides admission control in a multicast context, in-network adaptation, and supporting heterogeneous devices having different display capability. We further implement a prototype for illustrating the success of the proposed solution. The experimental results are also presented to show the effectiveness of the proposed equivalent bandwidth based adaptive enhancement layer switching algorithm.

A New IPTV Multicast Fast Reroute Method

This document proposes an IP multicast fast convergence method based on differentiating primary and backup PIM(Protocol Independent Multicast) join. The multicast stream is only sent along one of the multicast primary and backup path, which enables the efficient multicast delivery under both normal and abnormal conditions. The Single stream FRR(Fast Re-Route) solution has the advantages of implementing fast multicast protection and of avoiding double multicast bandwidth occupation in both normal and abnormal situations.

Network Multicast Routing Optimization Based on Immune Memetic Algorithm

In order to obtain the minimum cost network multicast path, a new optimization method based on immune Memetic algorithm is proposed. In the algorithm, a variety of immune operators are designed to fit the multicast routing problem, and the convergence speed of the algorithm is also designed. Experimental results show that this algorithm can find the optimal path quickly without the need of alternative path set, and the algorithm is simpler.

BEAM: branch-based efficient and adaptive multicast for wireless sensor networks

Multicast has been largely used for one-to-many distribution in wireless sensor networks (WSNs). However, existing multicast protocols have various overhead issues such as large forwarding states, control messages, packet header sizes, computation time, and energy consumption. In this paper, we propose a resilient and efficient branch-based multicast protocol, branch-based efficient and adaptive multicast for wireless sensor networks (BEAM) that reduces forwarding states and control messages by building efficient multicast paths on-demand using branch-based membership establishment, and that efficiently decreases packet header and computation overhead using branch-based data forwarding. Furthermore, for long-lived WSNs, BEAM resiliently keeps maintaining efficient multicast path with low overhead on continuous membership establishments based on quality of branches. Extensive evaluation results show that BEAM has less overhead complexity, packet overhead by 40%, and energy consumption by 30% than existing stateless multicast protocols.