Multirate multicast service provisioning II: a tâtonnement process for rate allocation

In multirate multicast different users in the same multicast group can receive services at different rates depending on their own requirements and the congestion level of the network. In this two-part paper we present a general framework for addressing the optimal rate control problem in multirate multicast where the objective is the maximization of a social welfare function expressed by the sum of the users’ utility functions. In Part II we present a market based mechanism and an adjustment process that have the following features. They satisfy the informational constraints imposed by the nature of multirate multicast; and when they are combined with the results of Part I they result in an optimal solution of the corresponding centralized multirate multicast problem.     

以太无源光网络中面向多播业务的节能算法(英文)

在面向多播业务的以太无源光网络中引入光网络单元混合休眠模式,提出面向多播业务的节能算法和改进的面向多播业务的节能算法,使光网络单元空闲组件能够得到充分休眠,并通过约束条件降低光网络单元的唤醒次数,从而降低光网络单元能耗.改进的面向多播业务的算法与面向多播业务的算法相比,增加了光网络单元唤醒的约束条件,进一步降低了光网络单元的唤醒次数.仿真结果表明,与现有算法相比,所提算法在保证数据包时延的前提下更加节能.改进的面向多播业务的算法节能效果优于面向多播业务的算法,表明增加的约束条件有助于降低光网络单元的唤醒次数和能耗.     

PHY modulation/rate control for fountain codes in 802.11a/g WLANs

In this paper we consider the joint performance of fountain codes and 802.11a/g PHY modulation/coding. We consider optimality both in terms of maximizing goodput and minimizing energy, and results are presented for both theoretical and experimental channel models. In contrast to studies in cellular networks, we find that in 802.11a/g WLANs the cross-layer approach of a higher-layer fountain coding with a PHY layer modulation and FEC coding can yield very limited gains, and the PHY modulation/rate that optimizes the uncoded multicast performance is also close to that for fountain-coded multicast traffic over a wide-range of network conditions. This is potentially an important observation as it indicates that in 802.11a/g WLANs cross-layer design for multicast rate control would bring few benefits and PHY layer rate control can be carried out without regard to the use of fountain coding at higher layers.     

Minimum power multicasting problem in wireless networks

In this paper we deal with the minimum power multicasting (MPM) problem in wireless ad-hoc networks. By using an appropriate choice of the decision variables and by exploiting the topological properties of the problem, we are able to define an original formulation based on a Set Covering model. Moreover, we propose for its solution two exact procedures that include a preprocessing technique that reduces the huge number of the model’s constraints. We also report some experimental results carried out on a set of randomly generated test problems.     

A multicast routing algorithm based on searching in directed graph

Aiming at constructing a delay and delay variation bounded Steiner tree in the real-time streaming media communication, in this paper, we discuss a multicast routing algorithm based on searching a directed graph (MRASDH). During the process of the construction of the multicast tree, some nodes and links in the network topology do not affect the outcome of the constructed tree. Therefore, based on the thought of shrinking the search space through deleting these non-relative nodes and edges to the utmost, the ant algorithm is utilized to generate a directed sub-graph of the network topology for each destination node, in which each node owns a bounded out-degree. And all these sub-graphs can be merged into a new directed graph that serves as the new search space. In the new space, the simulated annealing algorithm is applied to obtain a multicast tree that satisfies the condition for the optimization. The performance analysis and simulation results demonstrate that this algorithm can effectively construct a delay and delay variation bounded multicast tree. They also show that the algorithm have lower time complexity than the current ones, which means a much better result would be achieved when the system scale rises greatly.     

DRL-M4MR: An intelligent multicast routing approach based on DQN deep reinforcement learning in SDN

Traditional multicast routing methods have some problems in constructing a multicast tree. These problems include limited access to network state information, poor adaptability to dynamic and complex changes in the network, and inflexible data forwarding. To address these defects, the optimal multicast routing problem in software-defined networking (SDN) is tailored as a multiobjective optimization problem, and DRL-M4MR, an intelligent multicast routing algorithm based on the deep Q network (DQN) deep reinforcement learning (DRL) method is designed to construct a multicast tree in a software-defined network. First, combining the characteristics of SDN global network-aware information, the multicast tree state matrix, link bandwidth matrix, link delay matrix and link packet loss rate matrix are designed as the state space of the reinforcement learning agent to solve the problem in that the original method cannot make full use of network status information. Second, the action space of the agent is all the links in the network, and the action selection strategy is designed to add the links to the current multicast tree in four cases. Third, single-step and final reward function forms are designed to guide the agent to make decisions to construct the optimal multicast tree. The double network architectures, dueling network architectures and prioritized experience replay are adopted to improve the learning efficiency and convergence of the agent. Finally, after the DRL-M4MR agent is trained, the SDN controller installs the multicast flow entries by reversely traversing the multicast tree to the SDN switches to implement intelligent multicast routing. The experimental results show that, compared with existing algorithms, the multicast tree constructed by DRL-M4MR can obtain better bandwidth, delay, and packet loss rate performance after training, and it can make more intelligent multicast routing decisions in a dynamic network environment. Code and DRL model are available at https://github.com/GuetYe/DRL-M4MR.     

Optimal multicast route packing

This paper considers the hop-constrained multicast route packing problem with a bandwidth reservation to build QoS-guaranteed multicast routing trees with a minimum installation cost. Given a set of multicast sessions, each of which has a hop limit constraint and a bandwidth requirement, the problem is to determine the set of multicast routing trees in an arc-capacitated network with the objective of minimizing the cost. For the problem, we propose a branch-and-cut-and-price algorithm, which can be viewed as a branch-and-bound method incorporating both the strong cutting plane algorithm and the column generation method. We implemented and tested the proposed algorithm on randomly generated problem instances with sizes up to 30 nodes, 570 arcs, and 10 multicast sessions. The test results show that the algorithm can obtain the optimal solution to practically sized problem instances within a reasonable time limit in most cases.     

智能光网络组播梳理协议设计与分析

为了节约网络成本和提高网络性能,将RSVP协议和OSPF协议进行扩展,提出了一个支持业务梳理的智能光网络组播协议,给出了消息类型,信令流程及状态机模型,并通过仿真验证协议性能.仿真表明,业务梳理可以一定程度降低组播业务阻塞率,但业务建立时延却大于不存在梳理的情况.梳理的存在使业务建立时延随着业务量的增大有一个由小变大再减小的过程.     

Two-level-enforced security with hybrid precoding for multicast massive MIMO wiretap systems

Multicast hybrid precoding reaches a compromise among hardware complexity, transmission performance and wireless resource efficiency in massive MIMO systems. However, system security is extremely challenging with the appearance of eavesdroppers. Physical layer security (PLS) is a relatively effective approach to improve transmission and security performance for multicast massive MIMO wiretap systems. In this paper, we consider a transmitter with massive antennas transmits the secret signal to many legitimate users with multiple-antenna, while eavesdroppers attempt to eavesdrop the information. A fractional problem aims at maximizing sum secrecy rate is proposed to optimize secure hybrid precoding in multicast massive MIMO wiretap system. Because the proposed optimized model is an intractable non-convex problem, we equivalently transform the original problem into two suboptimal problems to separately optimize the secure analog precoding and secure digital precoding. Secure analog precoding is achieved by applying singular value decomposition (SVD) of secure channel. Then, employing semidefinite program (SDP), secure digital precoding with fixed secure analog precoding is obtained to ensure quality of service (QoS) of legitimate users and limit QoS of eavesdroppers. Complexity of the proposed SVD-SDP algorithm related to the number of transmitting antennas squared is lower compared with that of constant modulus precoding algorithm (CMPA) which is in connection with that number cubed. Simulation results illustrate that SVD-SDP algorithm brings higher sum secrecy rate than those of CMPA and SVD-SVD algorithm.     

Biclique completion problems for multicast network design

This paper considers the problem of aggregating several multicast sessions. A multicast session is defined as a subset of clients requiring the same information. Besides, each client can require several multicast sessions. A telecommunication network cannot manage many multicast sessions at the same time. It is hence necessary to group the sessions into a limited number of clusters. The problem then consists in aggregating the sessions into clusters to limit the number of unnecessary information sent to clients. The strong relationship of the problems with biclique problems in bipartite graph is established. We then model the problems using integer quadratic and linear programming formulations. We investigate some properties to strengthen the models. Several algorithms are provided and compared with a series of numerical experiments.