Search

The network-on-chip (NoC) has been introduced as an efficient communication backbone to tackle the increasing challenges of on-chip communication. Nevertheless, merely metal-based NoC implementation offers only limited performance and power scalability in terms of multicast and broadcast traffics. To meet scalability demands, this paper addresses the system-level challenges for intra-chip multicast communication in a proposed hybrid interconnects architecture. This hybrid NoC combines and utilizes both regular metal on-chip interconnects and new type of wireless-NoC (WiNoC) which is Zenneck surface wave interconnects (SWI). Moreover, this paper embeds novel multicast routing and arbitration schemes to address system-level multicast-challenges in the proposed architecture. Specifically, a design exploration of contention handling in SWI layer is considered in both centralized and decentralized manners. Consequently, the hybrid wire-SWI architecture avoids overloading the network, alleviates the formation of traffic hotspots and avoid deadlocks that are typically associated with state-of-the-art multicast handling. The evaluation is based on a cycle-accurate simulation and hardware description. It demonstrates the effectiveness of the proposed architecture in terms of power consumption (up to around $10$ x) and performance (around $22$ x) compared to regular NoCs. These results are achieved with negligible hardware overheads. This study explore promising potential of the proposed architecture for current and future NoC-based many-core processors.

For reliable multicasting, packet retransmission is an important mechanism in ensuring lossless data delivery. Existing packet retransmission methods cannot effectively address the recovery redundancy problem. This paper presents an OpenFlow-enabled elastic loss recovery solution, called ECast, for reliable multicasting. It employs a novel communication method, called elastic area multicast (EAM), to better retransmit the multicast recovery packets in OpenFlow-enabled networks. With the flexible flow-matching ability of OpenFlow switches, any subtree of a multicast tree can be used as an EAM tree. EAM approximately implements an elastic local multicast. Therefore, it can effectively alleviate the recovery redundancy with good scalability. We introduce an optimal EAM-based packet retransmission orchestration problem, named outdegree-constrained minimum-cost loss recovery (OCMCLR), which finds the EAM-based packet retransmission scheme with the minimum recovery cost. ECast uses an optimized tree-based feedback method to obtain the status of packet losses, and uses a fast cluster-based algorithm to approximately solve the OCMCLR problem based on the collected packet loss status.

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.

Networking plays a crucial role in cloud computing especially in an inter-cloud environment, where data communications among data centers located at different geographical sites form the foundation of inter-cloud federation. Data transmissions required for inter-cloud federation in the complex inter-cloud networking system are often point-to-multi points, which calls for a more effective and efficient multicast routing algorithm in complex networking systems. In this paper, we investigate the multicast routing problem in the inter-cloud context with K constraints where K U+2265 2. Unlike most of existing algorithms that are too complex to be applied in practical scenarios, a novel and fast algorithm for establishing multicast routing tree for interclouds is proposed. The proposed algorithm leverages an entropybased process to aggregate all weights into a comprehensive metric, and then uses it to search a multicast tree U+0028 MT U+0029 on the basis of the shortest path tree U+0028 SPT U+0029.We conduct complexity analysis and extensive simulations for the proposed algorithm from the approximation perspective. Both analytical and experimental results demonstrate that the algorithm is more efficient than a representative multi-constrained multicast routing algorithm in terms of both speed and accuracy, and thus we believe that the proposed algorithm is applicable to the inter-cloud environment.

Due to significant advances in wireless modulation technologies, some MAC standards such as 802.11a, 802.11b, and 802.11g can operate with multiple data rates for QoS-constrained multimedia communication to utilize the limited resources of MANETs more efficiently. In this paper, by means of measuring the busy/idle ratio of the shared radio channel, a method for estimating one-hop delay is first suggested. Then, by constructing a multicast tree, a delay-sensitive multicast protocol for real-time applications in multirate MANETs is proposed. In order to increase the network capacity, the proposed multicast protocol intends to minimize the sum of the total transmission time of the forwarders and the total blocking time of the blocked hosts, by taking the neighboring information of the forwarders into account and properly adjusting the data rates of the forwarders. Simulation results show that the proposed delay estimation method is more accurate, as compared with previous works. Besides, the proposed multicast protocol can induce higher network capacity, while satisfying the delay requirement.

Multicasting can reduce network traffic in multiuser systems by serving multiple users simultaneously. The benefits of multicasting basically come from the overlapping and synchronism of user requests. Pushing and caching are techniques that prestore content items in buffers closer to users based on the prediction of user requests, thereby providing a promising approach to eliminating the asynchronism of user requests and creating multicasting opportunities. This paper studies a multiuser wireless communication system, in which the buffers for caching are deployed in the user terminals. Based on the request delay information (RDI) which describes when the users request content items in a deterministic or statistical way, a joint pushing and caching (JPC) method is presented to schedule the content items pushed by the base station and cached in the user buffers. In this paper, multicasting JPC systems work in two modes, without or with the feedback of RDI. Furthermore, RDI is classified into three forms, namely, noncausal, statistical, and causal. Static and dynamic JPC policies are, respectively, proposed for the two work modes. In addition, the effective throughput resulting from JPC under the three forms of RDI is demonstrated via theoretical analysis and simulation.

We design and implement a practical layered multiplexed-coded decode-forward (LMDF) relaying strategy for a wide-band wireless multicast network. The proposed LMDF scheme relies on layering at the source, with the individual layers provided unequal power allocation through a simple bit-mapping operation to quadrature amplitude modulation constellations. At the relay, LMDF utilizes a multiplexed-coded approach that, with a single transmission, caters for the disparity in the number of layers decoded at different destinations. Under a practical setup of hard-decision decoding and coding across the subcarriers of orthogonal frequency division multiplexing (OFDM) modulated transmissions, we derive the information theoretic achievable rates of LMDF and use the IEEE 802.11 TGn channel model for performance evaluations. LMDF is then implemented using convolutional codes, with the relay's code optimized specifically keeping its multiplexed nature in mind. In addition to simulations, we also evaluate the performance of LMDF through a system-level implementation by using the National Instruments USRPs 2921. We conduct over-the-air experiments in an indoor office environment using an OFDM-based physical layer, and illustrate the considerable performance benefits of LMDF over benchmarks such as conventional two-hop decode-forward.

With the recent emergence of naked-eye 3D mobile devices and various 3D-enabled laptops, service providers now afford the opportunity to provide mobile 3D video streaming in LTE-Advanced networks. Differing from traditional single-view 3D videos, multi-view 3D videos allow users to choose preferred view angles and thus are promising for new applications, such as free-viewpoint television (FTV). Nevertheless, enabling multi-view 3D video services may overwhelm the network resource when transmitting all views of every video. Fortunately, Depth-Image-Based Rendering (DIBR) allows each mobile client to synthesize the desired view from a nearby left view and right view, so that not all views of a video are necessarily transmitted. A new challenge with DIBR, however, is to carefully choose the transmitted views to limit the video distortion and minimize the bandwidth consumption. In this paper, therefore, we first formulate a new optimization problem, called View and MCS Selection (VMS) Problem, to minimize the bandwidth consumption for multi-view 3D video multicast in LTE networks. An algorithm, called View and MCS Aggregation (VMAG) is proposed to find the optimal solution to VMS. For Carrier Aggregation (CA) in LTE-Advanced networks, we formulate a new View, MCS and Carrier Selection (VMCS) Problem and prove that the problem is NP-Hard. We first design a dynamic programming algorithm, called the View Assignment with MCS and Carrier (VAMC) algorithm, to find the optimal solution for small instances. We then propose the View and MCS Aggregation with Carrier (VMAGC) algorithm based on VMAG to effectively find the near-optimal solution to VMCS. The simulation results show that bandwidth consumption can be effectively reduced by over 30 percent in VMS and VMCS.

To support the massive content delivery, a novel virtualized heterogeneous network framework is proposed to enable content transcoding, caching, and multicast. In addition, a virtual multi-resources allocation problem is formulated to jointly optimize the utilities of computing, caching, and communication for the proposed framework. Simulations are conducted to show the effectiveness of the proposed scheme.

Wireless mesh networks (WMNs) connect to the Internet via access gateways. This paper studies multi-source video multicast in Internet-connected WMNs. The focus is on the design of a shareable integrated multicast that allows the multicasts of video sources to employ common Internet shortcuts or WMN paths to avoid potentially high WMN overheads and excessive Internet usage. Several algorithms are described that together form a video multicast framework running a controlled number of shareable multicasts under the constraint of Internet availability. These algorithms are the resource-efficient source group algorithm, the efficient integrated architecture algorithm, and the interference-controlled multicasting tree algorithm. These algorithms represent different approaches to overcoming various costs arising from multi-source video multicast, enabling multiple video sources to distribute delay, and throughput-guaranteed videos to receivers across large-scale areas. Simulation results are presented that quantify the performance gains that can be achieved.

This paper designs a novel non-orthogonal multiple access (NOMA) unicast–multicast system, where a number of unicast users (those who require different messages) and a group of multicast users (those who require identical message) share the same time/space/frequency resource. For the designed NOMA unicast–multicast system, an efficient two-phase cooperation strategy is proposed to improve the reliability of all users. In the first phase, the base station (BS) broadcasts a superposed message consisting of all users’ information. In the second phase, a multicast user is selected to forward the information intended by unsuccessfully decoded unicast and/or multicast users. Moreover, the multicast user selection is investigated under two different power allocation (PA) approaches: 1) fixed PA (FPA), in which the PA coefficients for both the phases are predetermined, and 2) dynamic PA (DPA), in which the PA coefficients for the first phase are predetermined, while the PA coefficients for the second phase are dynamically determined based on instantaneous channel information. Under the FPA approach, a best user selection (BUS) scheme (called F-BUS) is proposed to minimize the outage probability. Under the DPA approach, the local optimal PA coefficients for the second phase are derived in closed form first. Based on the derived PA coefficients, a BUS scheme (called D-BUS) is then proposed for outage probability minimization. To verify the reliability of the proposed cooperation strategy with employing the BUS schemes, we theoretically analyze the outage probability as well as diversity orders. It is shown that the proposed cooperation strategy achieves diversity orders equal to the number of multicast users, indicating that the inherent diversity orders offered by the multicast users are fully exploited. Finally, simulation results are presented to validate the theoretical results and demonstrate the advantages of the proposed cooperation strategy and the BUS schemes.

eXplicit multicasting (Xcast) is a protocol to send data to multiple receivers in an efficient way. Compared with traditional stateful multicast, Xcast is based on a stateless approach that scales better in number of groups. Unfortunately, the original Xcast brings up new challenges such as the scalability of group size and efficiency issue. Therefore, Multiple Xcast (MXcast) and Generalized Xcast (GXcast) were proposed to retard the limitation of the group size by reconstructing the multicast group into multiple subgroups and transferring multiple Xcast packets to different subgroups, respectively. In this paper, we propose various subgrouping schemes and evaluate their performance based on hybrid simulation experiments. The results show that it can save up to 36.7% bandwidth consumption from Xcast to our proposed Optimal GXcast in Voice over Internet Protocol (VoIP). The results reflect that the proposed scheme can improve the scalability of group size, achieve minimal packet delivery latency, reduce both network bandwidth consumption and source loading compared with the unicast and original Xcast, MXcast, and GXcast.

Multicast is an important way to diffuse data in duty-cycled wireless sensor networks (WSNs), where nodes can receive data only in active state. The communication delay can be extremely large if inappropriate schedules are adopted. Unfortunately, most previous methods do not consider controlling multicast delay energy-efficiently. This paper studies the minimum active time slot augmentation for delay-bounded multicast (MAADM) problem in duty-cycled WSNs. The MAADM problem is proved to be NP-hard even under the node-exclusive interference model. An optimal algorithm is proposed for the MAADM problem when $K=2$ and a heuristic latency bounding algorithm is proposed for source-to-all communications, where $K$ denotes the number of the destination nodes. When $K>2$ , two ( $K$ −1)-approximation algorithms are designed for the MAADM problem. In addition, a low computation-complexity distributed algorithm is proposed. To the best of our knowledge, this is the first work that develops a series of efficient centralized and distributed algorithms for the MAADM problem in duty-cycled WSNs. The theoretical analysis and experimental results verify that all the proposed algorithms have high performance in terms of delivery delay and energy consumption.

We consider the multicast scheduling problem in the heterogeneous network using a half-duplex relay station (RS). Our goal is to minimize the delay of transmitting a block of packets to users over time-varying channels using rateless codes. Due to half-duplex operation, at each time slot, the RS can choose to either multicast a packet to the users, or fetch a packet from the macro base station. We formulate a fluid relaxation for the optimal decision problem, and reveal that the optimal policy has a threshold-based structure so as to exploit the opportunism of multicast channel: the RS should multicast only when the channel quality is sufficiently “high”. We propose an online policy based on the relaxation which does not require the knowledge of channel distribution. When the channel distribution is symmetric across users, we provide a closed-form expression of the asymptotic performance of our policy. For two-user systems, we prove that our scheme is asymptotically optimal. When the users’ channels are independent, we derive a performance bound based on water-filling rate allocation which approximates the optimal policy well. Simulation results show that our scheme performs close to theoretical bounds, under correlated as well as independent fading channels.

© 1967-2012 IEEE. Multicasting is emerging as an efficient method to deliver the same data to a group of users, thereby saving network resources. The fairness between different multicast groups is an important quality-of-service (QoS) indication, but it has not been given significant attention. In this paper, we propose a normalized signal-To-noise ratio (SNR)-based fair scheduling for multiple multicast groups in multicast systems. The system fairness and capacity are then analyzed and compared for both fair scheduling and greedy scheduling over independent but non-identically distributed (i.n.d.) fading channels. Closed-form expressions in terms of the system spectral efficiency, outage probability, system fairness, and average bit error rate (BER) are derived in an uncoded/coded M-Ary quadrature amplitude modulation based adaptive transmission multicast system over i.n.d. Rayleigh fading channels. Numerical results show that compared with greedy scheduling, fair scheduling achieves considerably high fairness at the cost of slight system capacity loss, regardless of the number of multicast groups. Our focus is on the physical layer without rate loss, but we also briefly discuss applications of the proposed scheduling in a cross-layer design subject to the loss rate QoS constraint.

The 60-GHz bands target multi-gigabit rate applications, such as high definition video streaming. Unfortunately, to provide multicast service, the strong directionality required at 60 GHz precludes serving all clients in a multicast group with a single transmission. Instead, a multicast transmission is comprised of a sequence of beam-formed transmissions (a beam group) that together cover all multicast group members. In this paper, we design, implement, and experimentally evaluate scalable directional multicast (SDM) as a technique to 1) train the access point with per-beam per-client RSSI measurements via partially traversing a codebook tree. The training balances the objectives of limiting overhead with collecting sufficient data to form efficient beam groups. 2) Using the available training information, we design a scalable beam grouping algorithm that approximates the minimum multicast group data transmission time. We implement the key components of SDM and evaluate with a combination of over-the-air experiments and trace-driven simulations. Our results show that the gains provided by SDM increase with group size and provide near-optimal group selection with significantly reduced training time, yielding up to 1.8 times throughput gains over exhaustive-search training and grouping.

In recent years there has been an exponential increase in the growth in multimedia applications, and in particular in video applications. Understanding the behavior of the video traffic and the requirements for the network helps network administrators to improve the traffic. In this work, a quantitative analysis is performed by experimentation, in order to evaluate the behavior and impact of video traffic on WAN networks. We propose a WAN test bed with fourth subescenarios that allows to inject unicast or multicast video traffic, compressed with several codecs. The generic topology used includes a computer running as a streaming server and up to 20 desktop computers (PCs) as clients connected at the ends of a network as if outside a WAN. This network WAN is formed by routers and switchs with different types of links interconnecting the same. For the operation between routers was configured the OSPF routing protocol v2. For the same routers are configured the routing multicast protocol PIM in dense mode. From capturing video traffic, we identified several interesting performance and Qo metrics, such as unicast and multicast throughput, delay, jitter, and Pareto distribution. We include detailed contributions on the impact produced by several factors, such as the codec used for the compression, and the use of unicast and multicast traffic when there are restrictions on the bandwidth, as in a corporate real WAN link of some few Mbps. The work oriented on the configurations to be taken into account for an adequate management of similar networks and an efficient use of the resources available, without compromising the performance and the expected QoS. Besides facilitates the comparison of the results with those obtained from analytical studies and modelling for different contexts.

Multicast and prefix caching are two promising approaches to provide scalable video-on-demand (VoD) services. We contribute to solve the adaptive multicast delivery and the cache allocation problem for VoD services with client caching under asynchronous client requests. We first propose a client caching enabled adaptive multicast delivery scheme, which combines the stream merginglike method with prefix caching and adaptive modulation and coding, to fully exploit the multicast opportunity among asynchronous requests from heterogeneous clients. Next, we derive the bandwidth consumption of the proposed delivery scheme under a given prefix cache allocation and Poisson arrival request. We then optimize the cache allocation to minimize the average bandwidth consumption, and the problem is proved to be convex and solved effectively. Finally, three extreme cases are studied to provide closed-form solutions and more insight on the cache allocation and the delivery scheme for VoD systems.

Smart Grids (SGs) are emerging cyber-physical systems, equipped with sophisticated communication and information technologies, for efficient and large-scale power supply and management. SGs demand advanced communication technologies between energy providers and consumers, for enabling a control-feedback loop, by using time-dependent pricing. In this paper, we propose an efficient planning of 5G small cells, with evolved multimedia broadcast and multicast communication, between aggregators (small cells) and SG consumers, for efficient demand-response (DR) programs. After pointing out that optimal multicast scheduling and radio resource management problem is NP-complete, we propose two different solutions, based on dynamic programming (DP) and greedy heuristics, for minimizing the energy cost for DR customers. We also analyze the performance of SG user capacity for 5G single cell multicast and multicast broadcast single frequency network. Extensive OPNET simulation results, over actual energy data and real wireless trace, demonstrate that our proposed 5G small cell planning and multicast solutions are capable of reducing energy production cost by $30\%$ , with up to $35\%$ shift in peak energy load, low latency and packet drop.

Secondary users (SUs) can flexibly access licensed channels to improve the spectrum utilization in cognitive radio networks (CRNs). In mobile cognitive radio ad hoc networks (MCRAHNs) where nodes can move, SUs are intermittently connected because of node mobility, as well as the uncertain channel availability. Providing multicast services in MCRAHNs is urgently needed with the compelling demand on service qualities and varieties, and the proliferation of cognitive technology. The benefits of network coding over multicast in traditional wireless networks or CRNs have been well demonstrated in existing works. However, the existing studies merely address the two crucial issues (i.e., uncertain channel availability and node mobility) together and, thereby, cannot be applied to network coding-based multicast in MCRAHNs. In this paper, we study the problem of network coding-based multicast in MCRAHNs considering both channel uncertainty and node mobility. We utilize discrete-time Markov chains to model the channel availability and node mobility in MCRAHNs, and we then formulate a spectrum-aware network coded multicast problem as an optimization problem, which minimizes the total transmission cost, subject to the timely successful delivery constraint and link transmission constraint. Since the formulated problem is hard to tackle according to mixed integer programing, we further design a distributed spectrum-aware cost-based (SACB) scheme based on the metric of forwarding benefit. With extensive simulations based on both synthetic and realistic traces, we show that, compared with existing schemes, SACB can achieve almost the minimum transmission cost while maintaining high multicast success probability.

Wireless links are inherently lossy due to channel fading or interference. Previously, duplicate packets were transmitted on multiple routes of lossy mobile ad hoc networks (MANETs) to enhance reliability. In this paper, a multicast routing protocol that constructs multiple multicast trees and employs network coding is proposed for lossy MANETs, where each multicast tree can satisfy a predefined percentage of the bandwidth requirement. The proposed protocol can reduce the total bandwidth consumption while providing bandwidth guarantees to a requested flow and ongoing flows. As a consequence of employing network coding, no redundant packet is generated, and no scheduling algorithm for distributing packets among the multicast trees is needed. Simulation results show that the proposed protocol outperforms prior multicast routing protocols in terms of the receiving ratio, the admission ratio, and the total bandwidth consumption.

We propose and investigate a subtree scheme for all-optical multicast routing, modulation level and spectrum allocation (AOM-RMSA) in elastic optical networks. A multicast request is accommodated by several light-trees and each light-tree covers only a part of the destination set. We assume that all nodes are multicast capable and investigate the subtree scheme over the single light-tree scheme for the AOM-RMSA problem under both static and dynamic traffic scenarios. In the static scenario, we formulate an integer linear programming model to obtain the optimal solution. Then, we propose two time-efficient heuristic algorithms that construct subtrees according to the link-sharing ratio between the paths from source to two distinct destinations. The proposed algorithms improve the spectrum utilization by building subtrees that have smaller tree-spanning size and adopt higher level modulation formats. They have also effectively reduced the blocking probability compared to single light-tree schemes.

In this paper, we formulate an integer linear programming (ILP) to perform multicast routing and spectrum assignment (MRSA) in elastic optical networks, which serves jointly a set of multicast requests. In this formulation, all physical layer restrictions including modulation level assignment, maximum number of multicast capable nodes (MCNs), and maximum splitting degree (MSD) of MCNs, are considered. In addition, we modify the proposed joint ILP to serve multicast requests one-by-one, which is referred to as a separate ILP. Furthermore, we present three heuristic algorithms for MRSA, namely distance-based MRSA (DMRSA), congestion-based MRSA (CMRSA), and mixed CMRSA/DMRSA, which are applicable in both static and dynamic operation scenarios. In CMRSA and DMRSA, the link length and the amount of occupied spectrum are considered as the cost function of multicast routing, respectively; and in mixed CMRSA/DMRSA, a combination of normalized link length and normalized occupied spectrum is considered as the cost function. The comparison of ILPs and heuristic algorithms in static operation reveals that the joint ILP, as the benchmark, gives the optimum solution while has the most computational complexity. Furthermore, the separate ILP has lower complexity at the cost of consuming slightly more spectrum. Unless the DMRSA method, which has the worst performance, the gap between the other two heuristic algorithms and the ILPs is negligible. Furthermore, simulation results of dynamic operation scenarios reveal that mixed CMRSA/DMRSA outperforms other two heuristics algorithms in terms of blocking probability.

With the growing trend of deploying Software defined networks (SDN) in Internet and data centers, it is necessary to investigate the operation of multicast services in this paradigm shift. We propose an OpenFlowbased virtualized platform to support multiple multicast services simultaneously, each with their own customized multicast algorithms and performance-enhancing strategies for its service requirements. The contributions include: 1) systematic discussions of the technical challenges re-garding to implementing multicast services in SDN, with the proposed architectural components addressing these issues; 2) a virtualized platform enabling user-defined multicast services, independent of current Internet-based protocols; 3) experiments validating the necessity and efficiency of the platform in supporting its design goals and functionalities, with two additional real multicast applications further confirming the feasibility and operability of the proposed prototype.

In emerging fifth generation (5G) systems, mobile social networks are expected to play an important role to enable proximity-based content distribution among devices. In this paper, we address social-awareness aspects and device-to-device (D2D) communications for information diffusion solutions in emergency scenarios. Context-aware information is collected from a set of devices deployed in the environment and received data are integrated and elaborated at the cellular base station before being delivered. In such a framework, we model the expected information diffusion time by taking into account both networking- and sociality-related metrics. In particular, we introduce the so-called social intercontact time which is able to model the interaction frequency between the user and a generic social platform. The proposed approach is compared with alternative solutions where the dissemination process is either managed through direct links from the central base station, as a conventional multicast scheme, or with the support from proximity communications, as a D2D-enhanced multicast scheme. The results of a performance assessment study show that the proposed framework achieves considerable gains, up to 50%, in terms of overall information diffusion time and data rate per user equipment.

Today’s multiprocessor platforms employ the network-on-chip (NoC) architecture as the preferable communication backbone. Conventional NoCs are designed predominantly for unicast data exchanges. In such NoCs, the multicast traffic is generally handled by converting each multicast message to multiple unicast transmissions. Hence, applications dominated by multicast traffic experience high queuing latencies and significant performance penalties when running on systems designed with unicast-based NoC architectures. Various multicast mechanisms such as XY-tree multicast and path multicast have already been proposed to enhance the performance of the traditional wireline mesh NoC incorporating multicast traffic. However, even with such added features, the multihop nature of the wireline mesh NoC leads to high network latencies and thus limits the achievable system performance. In this paper, to sustain the high-bandwidth and high-throughput requirements of emerging applications, we propose the design of a wireless NoC (WiNoC) architecture incorporating necessary multicast support. By integrating congestion-aware multicast routing with network coding, the WiNoC is able to efficiently handle heavy multicast injections. For applications running with a broadcast-heavy Hammer cache coherence protocol, the proposed multicast-aware WiNoC achieves an average of 47% reduction in message latency compared with the XY-tree-based multicast-aware mesh NoC. This network level improvement translates into a 26% saving in full-system energy delay product.

Multicast routing that meets multiple quality of service constraints is important for supporting multimedia communications in the Internet of Things (IoT). Existing multicast routing technologies for IoT mainly focus on ad hoc sensor networking scenarios; thus, are not responsive and robust enough for supporting multimedia applications in an IoT environment. In order to tackle the challenging problem of multicast routing for multimedia communications in IoT, in this paper, we propose two algorithms for the establishing multicast routing tree for multimedia data transmissions. The proposed algorithms leverage an entropy-based process to aggregate all weights into a comprehensive metric, and then uses it to search a multicast tree on the basis of the spanning tree and shortest path tree algorithms. We conduct theoretical analysis and extensive simulations for evaluating the proposed algorithms. Both analytical and experimental results demonstrate that one of the proposed algorithms is more efficient than a representative multiconstrained multicast routing algorithm in terms of both speed and accuracy; thus, is able to support multimedia communications in an IoT environment. We believe that our results are able to provide in-depth insight into the multicast routing algorithm design for multimedia communications in IoT.

With the ever-increasing demands for popular content sharing among humans, device-to-device (D2D) multicast communication, as a promising technology to support wireless services within a local area, is introduced in a 5G cellular network. However, the existing resource allocation approaches for D2D multicast communication usually consider only physical domain constraints but neglect social domain factors, which would result in ineffective D2D links between users unwilling to share interests. Different from existing works, the D2D multicast scheme proposed in this paper will produce effective D2D multicast links by sufficiently utilizing both the physical and social properties of mobile users, with the goal to maximize the throughput of the overall social-aware network and guarantee fairly allocation of the channel between different D2D multicast clusters. The scheme mainly consists of two parts, the formation of D2D multicast clusters and joint optimization of power and channel allocation. In the formation of D2D multicast clusters, members and head in each cluster are selected by taking into account both social attributes and physical factors, such as community, ties, and geographical closeness. In the joint optimization, a two-step scheme is designed to first calculate the optimal power allocation by geometric proximity and then select suitable cellular channels for each D2D multicast cluster utilizing an extended one-to-many bipartite graphs matching algorithm. Simulation results demonstrate that, compared with heuristic algorithm and stochastic algorithm, the proposed scheme can increase the throughput of the overall social-aware network by about 5% and 50%, respectively.

A number of today’s over-the-top (OTT) services could greatly benefit from a flexible, efficient, and scalable network-layer multicast support on the Internet. IP multicast showed not to meet these requirements, hindering its adoption in more than individual network islands. As a consequence, content delivery networks (CDNs) emerged as alternative and implemented one-to-many multicasting at the application layer. Yet, due to practical reasons and conflicting stakeholder interests, CDN deployments usually end at the border of Internet service provider networks, making one-to-many deliveries at an Internet-scale challenging up to date. In a previous work, the authors presented software-defined multicast (Sdm) to mitigate this problem by unlocking network-layer multicast support for OTT services inside ISP networks. In this paper, DynSdm is proposed to complement Sdm in key aspects, allowing for a more holistic support of relevant scenarios aspects, and enabling a fine-granular traffic engineering of multicast traffic inside ISP networks. For this, DynSdm presents a detailed design of the ISP-internal traffic and service management process and introduces a set of novel SDN-based network-layer mechanisms for traffic load balancing as well as handling of group and network dynamics. DynSdm was implemented as prototype and extensively evaluated, showing its flexibility, high traffic efficiency, good scalability, and superior ability to balance traffic load inside ISP networks.

WiFi networks have been globally deployed and most mobile devices are currently WiFi-enabled. While WiFi has been proposed for multimedia content distribution, its lack of adequate support for multicast services hinders its ability to provide multimedia content distribution to a large number of devices. In this paper, we present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast services. AMuSe is based on accurate receiver feedback and incurs a small control overhead. In particular, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes, which periodically send information about the channel quality to the multicast sender. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. AMuSe does not require any changes to the standards or any modifications to the WiFi devices. We implemented AMuSe on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi devices , both with and without interference sources. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions.

We investigate the multicast of layered multimedia content in single hop cognitive radio (CR) networks and ways of improving the subscriber utility. The proposed unified opportunistic scheduling (UOS) aggressively utilizes diversity potential present in CR by exploiting two types of multiuser diversity (MUD), one between multicast groups and another between data stream subscribers in a group. As a result, the resource usage efficiency is significantly increased, and better utility can be achieved. According to derived effective average subscriber throughput under unified MUD, a scheduling algorithm is designed to approach the theoretical throughput improvement. We specifically introduce controlled competition between multicast groups to balance the increasing resource efficiency and the risk of overstretching the limited available spectrum. The algorithm combines prioritization, rateless coding, and data fragmentation to inherently cope with dynamic spectrum availability in CR. The presented simulation results show improved performance in various situations in comparison to other schemes not taking full advantage of the present MUD potential.

We present a novel control scheme that dynamically optimizes multirate multicast. By computing the differential backlog at every node, our scheme adaptively allocates transmission rates per session/user pair in order to maximize throughput. An important feature of the proposed scheme is that it does not require source cooperation or centralized calculations. This methodology leads to efficient and distributed algorithms that scale gracefully and can be embraced by low-cost wireless devices. Additionally, it is shown that maximization of sum utility is possible by the addition of a virtual queue at each destination node of the multicast groups. The virtual queue captures the desire of the individual user and helps in making the correct resource allocation to optimize total utility. Under the operation of the proposed schemes backlog sizes are deterministically bounded, which provides delay guarantees on delivered packets. To illustrate its practicality, we present a prototype implementation in the NITOS wireless testbed. The experimental results verify that the proposed schemes achieve maximum performance while maintaining low complexity., National Science Foundation (U.S.) (grant CNS-0915988), National Science Foundation (U.S.) (grant CNS-1116209), United States. Office of Naval Research (grant N00014-12-1-0064)

Random network coding (RNC) is a promising solution for multicast services over wireless networks. In this paper, we consider the problem of deadline-constrained multimedia multicast from a single transmitter to multiple users over wireless erasure channels. A novel transmission scheduling strategy based on adaptive RNC is developed to maximize the throughput of multicast sessions under a deterministic delay constraint. Particularly, we optimize the number of multimedia data layers under different assumptions on users' feedback. Simulation results show the effectiveness of the proposed methods.

We consider the multicast scheduling problem for the block transmission of packets in a heterogeneous network using a half-duplex relay station (RS). The RS uses random linear coding to efficiently transmit packets over time-varying multicast channels. Our goal is to minimize the average decoding delay. Because of the half-duplex operation, at each time slot, the RS must decide to either: 1) fetch a new packet for encoding from the base station or 2) multicast a coded packet to wireless users. Thus, optimal scheduling hinges on exploiting multicast opportunities while persistently supplying the encoder (at the RS) with new packets. We formulate an associated fluid control problem and show that the optimal policy incorporates opportunism across multicast channels, i.e., the RS performs a multicast transmission only if the collection of channel conditions is favorable; otherwise, it performs a fetch. Based on the fluid policy, we propose an online algorithm. We prove that our algorithm asymptotically incurs no more than 4/3 and 2 times the optimal delay, for two-user and arbitrary number of user system, respectively. Simulation results show that, in fact, our algorithm’s performance is very close to theoretical bounds.

In cellular network, users with same demand and in proximity to each other form the mobile cloud, in which the short-range D2D technology is employed by users to improve the data dissemination efficiency. In view of the fact that the D2D links with the poor channel conditions are likely to be the bottleneck of resource utilization improvement, aiming at the differentiation of link quality, this paper proposes a intra-cloud D2D multicast retransmission algorithm based on SINR constraint to meet the minimum requirement of D2D retransmission for QoS. In the proposed algorithm, the model of system link cost is built, the number of multicast retransmission times is restricted and each link quality matrix is traversed to reasonably select the multicast transmitter as well as its routing, which further reduces the link cost consumption, and in turn improves the bandwidth efficiency. Simulation results show that the proposed algorithm is more efficient to improve the bandwidth utilization when the ratio between normal user and non-normal user is small in mobile cloud.

Scalable video coding, together with adaptive modulation and coding, is a promising technique for providing real-time video multicast services on mobile stations (MSs) in heterogeneous channel conditions. On the other hand, since MSs are often powered by batteries, reducing the energy consumption of mobile devices is an important concern. In this paper, we study the problem of scalable video multicast scheduling in a mobile worldwide interoperability for microwave access (WiMAX) network with the objective of maximizing the multicast energy throughput. This problem has never been seriously studied when the assumption that different multicast groups may partially overlap is made. We prove that this problem is NP-complete. Our proposed solution, which is called energy-efficient multicast scheduling with adaptive modulation and coding (EEMS-AMC), consists of three modules, namely, online admission control, base-layer data scheduling, and enhancement-layer data scheduling. The admission control rules not only help the base station to admit the maximum number of video streams but ensure that the video data can be delivered to mobile users within the timeliness requirement as well. Moreover, EEMS-AMC adopts the greedy strategy to schedule base-layer data such that even in the worst-case scenario, the average duty cycle of admitted MSs can be within a bounded factor from the theoretical minimum. Finally, EEMS-AMC employs the metric “expected multicast throughput” to derive the proper modulation and coding scheme for each enhancement-layer data and employs the metric “marginal multicast energy throughput” to efficiently derive near-optimal enhancement-layer data scheduling. Simulation results exhibit that EEMS-AMC achieves relatively good performances in terms of multicast energy throughput and normalized total utility.

Cooperative wireless multicast is investigated, in which a source sends multicast messages to a number of users. For a multicast message from the source, some users do not successfully receive the message (called unsuccessful users). For a successful user (who successfully receives the message from the source), we define its worst relaying channel gain as the smallest channel gain among its channel gains to all unsuccessful users. It is proposed that the successful user whose worst relaying channel gain is the highest among the worst relaying channel gains of all successful users is selected to serve as a relay. Considering that the channels in the system are independent but nonidentically distributed Rayleigh fading, we derive a closed-form outage probability expression for the proposed scheme. It is shown that the proposed scheme can achieve full diversity, and thus, having a larger number of users can improve the outage performance. Furthermore, we study the time allocation strategy that determines the durations used by the source and the selected relay for their transmissions, respectively. An approximate optimal time allocation is derived. In addition, we also investigate the case with relay selection error and the case with mixed Rayleigh/Rician fading. Simulation results verify the performance of the proposed cooperative multicast scheme and time allocation strategy.

Scheduling algorithms are crucial for most existing switches to improve the throughput. However, the delay of the switching fabric cannot be guaranteed with such scheduling algorithms. This paper aims to design a novel load-balanced wire-speed multicast switching fabric along with the attractive merits of network coding. We adopt a two-phase self-routing switching fabric constructed by Boolean-multicast concentrators (SRBMCs), where the first SRBMC distributes the incoming cells to its outputs uniformly and the second allows the distributed cells to be self-routed and multicast to their destinations concurrently. To further improve the switching performance, linear network coding is smoothly combined with SRBMC to reduce the packet loss rate. Theoretical analysis and numerical simulation demonstrate that the proposed switching fabric cannot only achieve wire-speed multicast switching but also be recursively constructed into an indefinite large-scale one with such merits as no internal buffers, low complexity, and guarantee in switching delay. Finally, we implement the proposed fabric on Field-Programmable Gate Array and verify its performance in multicast switching.

In wireless local area networks (WLANs), link-layer multicast is a promising technology for many multimedia applications, e.g., video streaming, as multicast frames can reach multiple clients simultaneously. However, the efficiency of multicast in WLANs is usually low since multicast frames are transmitted at a basic data rate to reach clients with poor channel quality. Moreover, the reliability of multicast cannot be guaranteed either, as multicast transmissions are not acknowledged. Some recent works have utilized smart antennas to improve multicast performance. However, most of them require customized hardware and are not designed for the latest IEEE 802.11 standard, 802.11n WLANs. More importantly, these works did not consider the impact of AP association strategies on the performance of link-layer multicast. In this paper, we study the problem of link-layer multicast in large-scale 802.11n WLANs where each AP is equipped with a smart antenna that supports multiple antenna patterns. Based on channel gains of various antenna patterns from different APs, we choose the associated AP for multicast clients, partition associated clients of each AP into multiple groups, select an antenna pattern and data rate for each group of client, and transmit multicast frames to each group once. We first examine the limitation of multicast in 802.11n WLANs and the benefits of smart antennas to multicast via experiments. We then introduce the system model and formulate the problem into an optimization problem, and prove its NP-hardness. The objective is to minimize the time to transmit a multicast frame to all clients while guaranteeing high packet reception ratio (PRR) for each client. For generic WLANs where APs are sparsely deployed, we propose an optimal algorithm under the condition that the PRR of antenna patterns and data rates are known for every client. For generic large-scale WLANs, we further propose an on-line algorithm in which the AP association strategy, the partition of clients, the antenna pattern and data rate of each group are adapted dynamically, based on PRR reports from clients. We have implemented the on-line algorithm on off-the-shelf WLAN products, and conducted extensive experiments and simulations to evaluate the performance. The results show that the proposed algorithm can significantly improve multicast performance compared to other schemes, and at the same time guarantee high PRR for all clients.

Comparing with the unicast technology, multiple flows from the same source in multicast scenario can be aggregated even if their destinations are different. This paper evaluates such distinction by the multicast gain on per-node capacity and delay, which are defined as the per-node capacity and delay ratios between multi-unicast and multicast ( $m$ destinations for each multicast session). Particularly, the restricted mobility model is proposed, which is a representative mobility model characterizing a class of mobility models with different average moving speeds. The theoretical analysis of this model indicates that the mobility significantly decreases the multicast gain on per-node capacity and delay, though the per-node capacity of both unicast and multicast can be enhanced by mobility. This finding suggests that mobility weakens the distinction between multicast and unicast. Finally, a general framework of multicast study is constituted by analyzing the upper-bound ( $\Theta (m)$ ), the lower-bound ( $\Theta (1)$ ) and the main determinants of the multicast gain on both per-node capacity and delay regardless of mobility model.

In this paper, we propose virtual direction multicast (VDM) for video multicast applications on peer-to-peer overlay networks. It locates the end hosts relative to each other based on a virtualized orientation scheme using real-time measurements. It builds multicast tree by connecting the nodes, which are estimated to be in the same virtual direction. By using the concept of directionality, we target to use minimal resources in the underlying network while satisfying users' quality expectations. We compare VDMagainst host multicast tree protocol.We simulated the protocol in a network simulator and implemented in PlanetLab. Results both fromsimulation and PlanetLab implementation show that our proposed technique exhibits good performance in terms of defined metrics.

The growing demand for mobile multicast services, such as Internet Protocol television (IPTV) and video streaming, requires effective radio resource management (RRM) to handle traffic with strict quality-of-service constraints over Long-Term Evolution (LTE) and beyond systems. Special care is needed to limit system performance degradation when multiple multicast streams are simultaneously transmitted. To this aim, this paper proposes an RRM policy based on a subgrouping technique for the delivery of scalable multicast video flows in a cell. Our proposal enhances the legacy multicast transmission over LTE systems by exploiting multiuser diversity and the users' channel quality feedbacks. Moreover, it is designed to take advantage of the frequency selectivity in the subgroup formation. Simulation results demonstrate the effectiveness of the proposed scheme, which outperforms existing approaches from the literature. It succeeds in achieving higher spectral efficiency and guaranteeing adequate video quality to all multicast receivers and improved quality to those with good channel conditions.

In this paper, we propose a probability-based relay selection and power control method in two-phase cooperative multicast communications to minimize the user power consumption for any given multicast data rate. Our method gives each user the ability to autonomously decide whether to participate in the relay transmission based on an active probability. In particular, we develop an optimal algorithm to calculate the optimal active probability and relay power by balancing the outage reduction efficiency. We also develop a sub-optimal algorithm by balancing the outage probability of the cell-center and the cell-edge users. Simulation results demonstrate that the proposed optimal and sub-optimal algorithms can reduce the user power consumption up to about 54% and 40%, respectively, compared with the conventional algorithm that requires all users to participate in the relay transmission.

With the explosive growth of cloud-based services, large-scale data centers are widely built for housing critical computing resources to gain significant economic benefits. In data centers, the cloud services are generally accomplished by multicast-based group communications. Recently, many well-known industries, such as Microsoft, Google, and IBM, adopt high-speed wireless technologies to augment network capacity in data centers. However, those well-known multicast delivery schemes for traditional wired data centers do not consider the unique characteristics of wireless communications, which may result in unnecessary data transmissions and network congestions. Under the coexisting scenario of wired and wireless links, this paper studies multicast tree construction and maintenance problems. The objective is to minimize the total multicast traffic. We prove the problems are $\mathcal {NP}$ -hard and propose efficient heuristic algorithms for the two problems. Based on real traces and practical settings obtained from commercial data centers, a series of experiments are conducted, and the experimental results show that our proposed algorithms are effective for reducing multicast data traffic. The results also provide useful insights into the design of multicast tree construction and maintenance for wireless data center networks.

In this letter, a predictive unicast and multicast scheduling (PUMS) scheme is proposed for onboard buffered crossbar switches to cope with time-variant traffic composition. The multicast service ratios required with respect to traffic composition ratio are deduced in theory to guarantee stability and fairness. In the proposed scheme, the multicast service ratios are obtained by a real-time traffic prediction in advance. Accordingly, the bandwidth and crosspoint buffers are adaptively assigned. Simulation results indicate that the proposed PUMS exhibits a promising performance under various traffic scenarios with both fixed and time-variant traffic composition ratios.

The high-availability seamless redundancy (HSR) protocol is one of the most important redundancy IEC standards that has garnered a great deal of attention because it offers a redundancy with zero recovery time, which is a feature that is required by most of the modern substation, smart grid, and industrial field applications. However, the HSR protocol consumes a lot of network bandwidth compared to the Ethernet standard. This is due to the duplication process for every sent frame in the HSR networks. In this paper, a novel algorithm known as the reducing multicast traffic (RMT) is presented to reduce the unnecessary redundant multicast traffic in HSR networks by limiting the spreading of the multicast traffic to only the rings that have members associated with that traffic instead of spreading the traffic into all the network parts, as occurs in the standard HSR protocol. The mathematical and the simulation analyses show that the RMT algorithm offers a traffic reduction percentage with a range of about 60–87% compared to the standard HSR protocol. Consequently, the RMT algorithm will increase the network performance by freeing more bandwidth so as to reduce HSR network congestion and also to minimize any intervention from the network administrator that would be required when using traditional traffic filtering techniques.

Most practical networks are cyclic and demand Convolutional network coding (CNC). Researches on application of CNC in practical networks are still insufficient. Conventional graph theories cannot model the multicast channel properly. This paper introduces a multicast graph with multicast edges to model the multicast networks, and proposes a Multicast edge generation and max-flow detection (MEGAMAD) algorithm to approach the lower bound of necessary multicast edge number for a multicast network. Based on the algorithm we designed a new Media access control (MAC) protocol, the CNC oriented four-stage contention protocol (NC-FSCP) for the all-to-all broadcasting networks. The protocol runs a four stage reservation procedure to reserve time slots for encoded data transmission. Simulation proves that the reserved slot number approaches the lower bound for data dispersion in an all-to-all broadcasting network.

Current cellular networks support video streaming over unicast or multicast. However, there exists a tradeoff between utilizing the two: i) unicast leads to higher network load, but lower energy consumption of mobile devices, and ii) multicast results in lower network load, but higher energy consumption. To make the best out of both, we propose to concurrently utilize unicast and multicast for minimizing the energy consumption of mobile devices and minimizing the load on cellular networks. Cellular networks support two multicast schemes: i) independent cell networks and ii) multi-cell single frequency networks, where multiple adjacent base stations operate on the same frequency. We first consider the less-complicated independent cell networks, and then extend our solution to single frequency networks for better performance. We formulate the resource allocation in hybrid multicast -unicast streaming systems as a binary integer programming problem. We describe optimal algorithms for the two multicast schemes. We then propose two efficient, heuristic, algorithms that run faster and provide close to optimal results. While our solution is general, for concreteness, we conduct detailed LTE packet-level simulations using OPNET. Our simulation results show the proposed algorithms i) scale to many more mobile devices than the state-of-the-art unicast-only approaches and ii) result in lower energy consumption than the latest multicast-only approaches. In addition, the algorithms designed for multi-cell single frequency networks outperform the algorithms designed for independent cell networks in all aspects, such as service ratio, spectral efficiency, energy saving, video quality, frame loss rate, initial buffering time, and number of re-buffering events.

Many multicast services such as live multimedia distribution and real-time event monitoring require multicast mechanisms that involve network functions (e.g., firewall and video transcoding). Network function virtualization (NFV) is a concept that proposes using virtualization to implement network functions on infrastructure building block (such as high volume servers and virtual machines), where software provides the functionality of existing purpose-built network equipment. We present an approach for building the multicast mechanism whereby multicast flows are processed by NFV before reaching their end users. We propose a routing algorithm and a method for building an appropriate multicast topology.

In computer networks, multicast routing is that in which a single message is transmitted to multiple recipients from a subset of devices, called multicast group. To address the multicast routing problem, it is usual to model the computer network as a graph. In line with this, some strategies aim at building a routing tree that minimizes the total costs of transmission between the vertices of the routing tree that contains the multicast group, the Steiner tree. However, in large scale applications, local-based strategies may be a better alternative, since they can also be easily adapted to tackle distributed systems. In the literature, to the extent of our knowledge, to construct approximate Steiner tree using this type of approach remains a challenge. In this paper, we present a neighborhood-based metaheuristic to find an approximate solution for the Steiner tree in graphs. In the computational experiments, we used benchmark instances of small, medium and large scales and compared the results achieved by the proposed strategy with the best found so far. In addition, we analyze a real word instance for which the proposed algorithm has obtained good performance.