In multicasting routing, the main objective is to send data from one or more source to multiple destinations, while at the same time minimizing the usage of resources. Examples of resources which can be minimized include bandwidth, time and connection costs. In this paper we survey applications of combinatorial optimization to multicast routing. We discuss the most important problems considered in this area, as well as their models. Algorithms for each of the main problems are also presented.

Abstract—Wireless link layer multicast is an important service primitive for emerging applications, such as live video, streaming audio, and other content telecasts. The broadcast nature of the wireless channel is amenable to multicast because a single packet transmission may be received by all clients in the multicast group. However, in view of diverse channel conditions at different clients, the rate of such a transmission is bottlenecked by the rate of the weakest client. Multicast throughput degrades severely. Attempts to increase the data rate result in lower reliability and higher unfairness. This paper utilizes smart beamforming antennas to improve multicast performance in wireless LANs. The main idea is to satisfy the stronger clients with a high-rate omnidirectional transmission, followed by highrate directional transmission(s) to cover the weaker ones. By selecting an optimal transmission strategy (using dynamic programming), we show that the multicast throughput can be maximized while achieving a desired delivery ratio at all the clients. We use testbed measurements to verify our main assumptions. We simulate our protocol in Qualnet, and observe consistent performance improvements over a range of client topologies and time-varying channel conditions. bottleneck identification may not be trivial. (3) Even if bottleneck rate is suitably identified, packet losses are still possible due to fading and interference. The protocol will need to recover from such losses so that clients achieve an application-specified reliability. This paper aims to design a link layer multicast service that addresses these challenges in the context of WiFi networks. A practical solution is of interest that can accomplish high multicast throughput, while meeting a required per-node delivery ratio. Increasing transmission rates does not resolve the challenges, since some weak clients will fail to receive transmissions at higher data rates, and thus, be “left behind”. We believe smart antennas offer new opportunities to augment the state of the art in link layer multicast. We motivate the applicability of smart antennas, and present our main ideas next.

ABSTRACT. Multicasting is a technique for data routing in networks that allows multiple destinations to be addressed simultaneously. The implementation of multicasting requires, however, the solution of difficult combinatorial optimization problems. In this chapter, we discuss combinatorial issues occurring in the implementation of multicast routing, including multicast tree construction, minimization of the total message delay, center-based routing, and multicast message packing. Optimization methods for these problems are discussed and the corresponding literature reviewed. Mathematical programming as well as graph models for these problems are discussed. 1.

Abstract. Current methods of routing are based on network information in the form of routing tables, in which routing protocols determine how to update the tables according to the network changes. Despite the variability of data in routing tables, node addresses are constant. In this paper, we first introduce the new concept of variable addresses, which results in a novel framework to cope with routing problems using heuristic solutions. Then we propose a heuristic routing mechanism based on the application of genes for determination of network addresses in a variable address network and describe how this method flexibly solves different problems and induces new ideas in providing integral solutions for variety of problems. The case of ad-hoc networks is where simulation results are more supportive and original solutions have been proposed for issues like mobility.

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As the internet developing rapidly, new requirements, such as video on demand and video conference are emerging. We present multicast routing protocol for providing efficient and flexible multicast services over the Internet. The Master routers handle most of the multicast-related tasks A Master router handles many to many communications efficiently; restrict the end to end delay using intra-domain multicast protocol called Service-Oriented Multicast Protocol (SOMP). SOMP builds a shared multicast tree rooted at the Master router for each group. The multicast tree is computed in the master router by employing the Delay Restricted Dynamic Multicast (DRDM) algorithm, which dynamically builds a delay-restricted multicast tree and minimizes the tree cost as well. The physical construction of the multicast tree over the Internet is performed by a special type of self-routing packets in order to minimize the protocol overhead.

Abstract—We introduce a novel feedback protocol, called SMART, for wireless broadcast networks that use linear network coding. We consider transmission of packets from a single source to many receivers over a single-hop broadcast erasure channel with heterogeneous links. We propose a predictive model to minimize feedback as well as extraneous data transmissions by the source. In addition, we use the method of types to provide a lower bound for the expected total transmission time, and use simulations to show that our protocol operates close to this lower bound. We show that with SMART, counter to conventional wisdom, the average user’s QoE improves slightly as the number of users increases. We demonstrate that SMART’s algorithmic simplicity enables multicast transmissions that on average take fewer than 2 feedback rounds to complete. We show the favorable scalability of our technique with the number of users, which enables reliable quality of experience. We also show the robustness of this scheme to uncertainty in the number of receiving nodes, and packet erasure probability, as well as to partial loss of the feedback. Furthermore, we show that SMART performs nearly as well as an omniscient transmitter that requires no feedback. Index Terms—Feedback, multicast, wireless, network coding. I.

Video conferencing is now widely used both in wired and wireless network. Quality of Service (QoS) depends upon the efficient utilization of the network bandwidth. Internet Protocol (IP) multicasting is simultaneous transmission of data to multiple destination. IP multicast uses one-to-many technique, wherein a single packet is sent to multiple destinations in a multicast group identified by a single IP destination group address. Core failure is a serious issue in multicast networks with the QOS diminishing even if alternative routes are available. This paper investigates the performance of streaming data which require stringent QOS using unicast and multicast communication with Protocol Independent Multicasting – Sparse Mode (PIM-SM). An intermediate core is failed and the performance of the network measured. Results obtained show the degradation due to core failure affects the QOS for streaming data.