Multicast Session Research Articles

Multicast Scaling of Capacity and Energy Efficiency in Heterogeneous Wireless Sensor Networks

Motivated by the requirement of heterogeneity in the Internet of Things, we initiate the joint study of capacity and energy efficiency scaling laws in heterogeneous wireless sensor networks, and so on. The whole network is composed of n nodes scattered in a square region with side length L = n α , and there are m = n ν home points { c j } j=1 m , where a generic home point c j generates q j nodes independently according to a stationary and rotationally invariant kernel k ( c j , ⋅). Among the n nodes, we schedule n s independent multicast sessions each consisting of k − 1 destination nodes and one source node. According to the heterogeneity of nodes’ distribution, we classify the network into two regimes: a cluster-dense regime and a cluster-sparse regime. For the cluster-dense regime, we construct single layer highway system using percolation theory and then build the multicast spanning tree for each multicast session. This scheme yields the Ω( n ½+(α − ½)γ / n s √ k ) per-session multicast capacity. For the cluster-sparse regime, we partition the whole network plane into several layers and construct nested highway systems. The similar multicast spanning tree yields the Ω( n ½−(1− ν)γ/2 / n s √ k ) per-session multicast capacity, where γ is the power attenuation factor. Interestingly, we find that the bottleneck of multicast capacity attributes to the network region with largest node density, which provides a guideline for the deployment of sensor nodes in large-scale sensor networks. We further analyze the upper bound of multicast capacity and the per-session multicast energy efficiency. Using both synthetic networks and real-world networks (i.e., Greenorbs), we evaluate the asymptotic capacity and energy efficiency and find that the theoretical scaling laws are gracefully supported by the simulation results. To our best knowledge, this is the first work verifying the scaling laws using real-world large-scale sensor network data.

An offline cost-efficient strategy for multicast traffic protection in WDM optical mesh networks to aid rapid recovery

The most effective way of providing popular user services such as high-definition television, video conferencing and distributed gaming over the Internet is multicasting. Protecting multicast sessions against single link failure or a fiber cut in the WDM optical backbone is thus vital. Protection schemes involve reserving resources for backup paths that remain idle during normal fault-free operation. It is thus important to design protection or survivability schemes that consume as few extra resources as possible. A number of protection schemes for multicast sessions exist in the literature but only few can provide rapid recovery. In this paper we propose a new offline strategy for ensuring survivability of multicast traffic that can aid rapid recovery from a link failure. Our strategy is designed to achieve significant resource saving while providing recovery speed comparable to 1:1 dedicated path protection. We first propose an Integer Linear Program formulation to solve the problem optimally for small networks and then a heuristic for large networks. Performance comparisons show that our heuristic performs better than two well-known heuristics and also produces near optimal results. Time complexity analysis further shows that our heuristic runs in polynomial time.

Multicast routing from a set of data centers in elastic optical networks

This paper introduces the Multi-Server Multicast (MSM) approach for Content Delivery Networks (CDNs) delivering services offered by a set of Data Centers (DCs). All DCs offer the same services. The network is an Elastic Optical Network (EON) and for a good performance, routing is performed directly at the optical layer. Optical switches have heterogeneous capacities, that is, light splitting is not available in all switches. Moreover, frequency slot conversion is not possible in any of them. We account for the degradation that optical signals suffer both in the splitting nodes, as well as across fiber links to compute their transmission reach. The optimal solution of the MSM is a set of light-hierarchies. This multicast route contains a light trail from one of the DCs to each of the destinations with respect to the optical constraints while optimizing an objective (e.g., minimizing a function). Finding such a structure is often an NP-hard problem. The light-hierarchies initiated from different DCs permit delivering the multicast session to all end-users with a better utilization of the optical resources, while also reducing multicast session latencies, as contents can be delivered from such DCs closer to end-users. We propose an Integer Linear Programming (ILP) formulation to optimally decide on which light-hierarchies should be setup. Simulation results illustrate the benefits of MSM in two reference backbone networks.

A multi Ability CP-ABE access control scheme for public cloud storage

The main personality of the cryptography structure based on communication with writings of stable figures and private keys [1-4]. Our development is a key encapsulation mechanism (KEM), so long messages can be coded under a short symmetric key. In our response, the writings of the figures and the private keys have stable dimensions and the people in general are directly in the maximum estimate of s. Furthermore, in our plan, the private key generator (PKG) can potentially include new people without modifying the already widespread data (as in the EIB’s plans). We also note that there is no chain of importance between the characters, despite HIBE. The income of the general population is directed at the maximum size of S, and not in the amount of decoding keys that can be transmitted, which is the amount of conceivable characters. In this case, use a simple situation to find out about the group classification and main administration test problems. Think about a source that sends information to a provision of beneficiaries in a multicast session. Session security is supervised by two principles of useful substances: a Group Controller (GC) responsible for confirmation, approval and control and a Key Server (KS). To ensure classification in the middle of the multicast session, the sender (source) shares a mysterious symmetric key with all the individuals in the legitimate collection, called the Traffic Encryption Key (TEK). To multicast a mysterious message, the source encodes the message with the TEK using a symmetric encryption calculation. From previous documents, we look at how to share protected information in the cloud without losing keys. In this article, we present a new digital brand, an SSH key, hash functionality, and major escrow calculations.

CMU-VP: Cooperative Multicast and Unicast With Viewport Prediction for VR Video Streaming in 5G H-CRAN

Virtual reality (VR) is commonly regarded as one of 5G killer-applications. Transmission efficiency and quality of experience (QoE) are the most concerning issues for VR video streaming in 5G networks. Several multicast approaches were proposed to address these issues regardless of variance of personal viewports. In this paper, we explore a novel scheme combining multicast and unicast sessions in heterogeneous cloud-radio access networks (H-CRAN), in which a basic version of the video is transmitted to all users through the g-NB in a multicast session, and tiles of enhanced-version are transmitted to each viewer in a unicast session through its stationed remote radio head (RHH). To ensure the real-time content delivery, a user's viewport is predicted using a method based on historical trajectories and similarity of motion behavior, and then the tiles of predicted viewport in a version dependent on the channel quality are sent to the user in the unicast session. The scheme is formulated into a mixed-integer nonlinear problem (MINLP), and two near-optimal solutions are proposed to solve it by applying greedy approach and approximate approach, respectively. The simulation results show that our proposed scheme ensures better QoE under constrained bandwidth, and the proposed near-optimal solutions can efficiently solve the problem with low complexity and comparable performance.

Weight-based Energy-efficient Multicasting (WEEM) In Mobile Ad Hoc Networks

Multicasting in ad hoc network is an extremely important operation where there is only one sender and multiple receivers per session. During route discovery, generally multiple paths are discovered to each of the multicast destinations. Among them only one is elected depending upon its lifetime or weight. Priority is assigned to the paths that will survive upto completion of the present session of packet transfer from given source to destination node. If more than one path is expected to remain alive till the multicast session is over or none of the available path options have chance to live (at least mathematically) till end of the multicast session, weight is assigned to the paths by the destination. The path with highest weight is elected as optimal. Weight is computed based on residual energy and multicast packet transmission capability of nodes in a path along with number of multicast destinations residing in that path. If more than one path has same weight then the one suffering less delay is given priority. Simulation section in this article demonstrates that WEEM produces more packet delivery ratio and alive node ratio, at much less control message cost, than other competing multicast protocols.

Output Forms of Packets in a Multicast Session Using Network Coding With R Flow

A one-session multicast network, on which a coding scheme with Network Coding is defined, was implemented with a maximum common flow of r-packets arriving simultaneously at |T| sink nodes. Determining how to order the r-packets that emerge from the source node s through their output n-links, constitutes a combinatorial problem. In this work, the set of all the possible output configurations is constructed, where each configuration is a vector of packets tags of length equal to n. Each tag has a length equal to r. Through a combinatorial algorithm on the set of possible output configurations, a path is carried out on the graph representing the one-session multicast network. The path is based on a topological ordering of the multicast graph that allowed us finding all possible ways to order the output of the r-packets from s to the sink nodes in T. An ordering configuration based on Network Coding is valid, if the coding of packets is achieved through a linear combination in the coding nodes and the decoding of packets in the sink nodes. This validation verifies, then, a one-session multicast solution. The proposal of this work is independent of the network topology, the maximum flow value, and the size of the packets.

Characterization of SINR Region for Multiple Interfering Multicast in Power-Controlled Systems

This paper considers a wireless communication network consisting of multiple interfering multicast sessions. Different from a unicast system where each transmitter has only one receiver, in a multicast system, each transmitter has multiple receivers and broadcasts a common message to all of them. It is a well-known result for wireless unicast systems that the feasibility of a signal-to-interference-plus-noise power ratio (SINR) without power constraint is decided by the spectral radius of a nonnegative matrix. We generalize this result and obtain necessary and sufficient conditions for the feasibility of an SINR in a wireless multicast system with and without power constraint. The feasible SINR region and its geometric properties are studied. Besides, an iterative algorithm is proposed, which can efficiently check the feasibility condition and compute the boundary points of the feasible SINR region.

Energy-efficient multicast routing protocol based on SDN and fog computing for vehicular networks

Vehicular networks have been expanding significantly to perform several applications and strategies related to vehicles, ambulances, traffic jam, drivers, and even passengers. The most important challenge in this network is routing data among vehicles. Therefore, there is a need to design efficient routing protocols for unicast, Geocast, multicast and broadcast transmission modes. The multicasting can be used in many application fields such as emergency, police, and firefighting. There is a large body of studies on multicast routing in vehicular networks. However, safety applications in vehicular networks require a special multicast routing protocol that takes into account the deadline and existing bandwidth constraints. On the other hand, there has been a growing tendency towards electric cars in recent years. Therefore, energy consumption is one of major parameters that should be considered in the design of this routing protocol. The goal of this paper is to present a new Energy Efficient Multicast routing protocol based on Software Defined Networks and Fog computing for Vehicular networks called EEMSFV including deadline and bandwidth constraints. Multicast routing with multiple constraints of QoS has been proved to be a NP complete problem. The proposed architecture consists of four layers: vehicles, fog computing, OpenFlow switches and SDN controller. Moreover, a priority based scheduling algorithm and a classification algorithm to schedule the multicast requests based on their application type and deadline constraint after classifying them are proposed. The partitioning concept is used to decrease time complexity and overhead in the SDN controller. From the simulation results, we concluded that EEMSFV is better than MABC and CVLMS in terms of successfully transmitted ratio, average end to end delay, normalized overhead load, multicast energy consumption, packet loss ratio and percentage of critical multicast sessions that meet the deadline.

Adaptive multicast streaming for videoconferences on software-defined networks

Real-time applications, such as video conferences, have strong Quality of Service requirements for ensuring a decent Quality of Experience. Nowadays, most of these conferences are performed over wireless devices. Thus, an appropriate management of both heterogeneous mobile devices and network dynamics is necessary. Software Defined Networking enables the use of multicasting and stream layering inside the network nodes, two techniques able to enhance the quality of live video streams. In this paper, we propose two algorithms for building and maintaining multicast sessions in a software-defined network. The first algorithm sets up the initial multicast trees for a given call. It optimally places the stream layer adaptation function inside the core network in order to minimize the bandwidth consumption. This algorithm has two versions: the first one, based on shortest path trees is minimizing the latency, while the second one, based on spanning trees is minimizing the bandwidth consumption. The second algorithm adapts the multicast trees according to the network changes occurring during a call. It does not recompute the trees, but only relocates the stream layer adaptation functions. It requires very low computation at the controller, thus making our proposal fast and highly reactive. Extensive simulation results confirm the efficiency of our solution in terms of processing time and bandwidth savings compared to existing solutions such as multiple unicast connections, Multipoint Control Unit solutions and application layer multicast.

A Novel Approach to Efficient Resource Allocation in NOMA Heterogeneous Networks: Multi-Criteria Green Resource Management

ABSTRACTNowadays, Green Communications has been introduced as an appealing approach to achieve the maximum degree of energy efficiency in new generation heterogeneous networks. To achieve the effective resource management, this paper suggests a novel approach to joint optimal power allocation and user association techniques in which cells are powered via a common grid network and alternative energy resources. This research focuses on resource assignment in energy-cooperated heterogeneous systems with non-orthogonal multiple access so that the quality of experience indexes are assumed to be bounded during multicell multicast sessions. The solution to the introduced problem has been developed to a mixed-integer programming framework in which the goal function is solved based on a Lagrangian convex optimization method by considering user association constraints. The effectiveness of the suggested approach has been confirmed by the numerical results and we compared the complexity of the proposed model to those of the conventional schemes. Also, the results reveal that non-orthogonal multiple access can provide greater energy efficiency than orthogonal multiple access in heterogeneous wireless networks.

Secure Data Delivery with Linear Network Coding for Multiple Multicasts with Multiple Streams in Internet of Things

With the rapid developments of Internet of Things (IoT), tremendous number of sensors are deployed in the environment to monitor and collect different types of information. When a group of sensors located with the same location (or area) should deliver their data to a set of users and they have connected with the same network device, e.g., base station or access point, the data delivery between them and their users can be treated as a single source multicast in the core network from the network device connected with them to the network devices connected with their users. Generally, in such a case, multiple multicast sessions exist in the network simultaneously. In this paper, we study two major considerations, i.e., transmission throughput and information security, for multiple multicasts with multiple streams in IoT by using linear network coding (LNC). Specifically, we jointly consider the transmission rate allocation, transmission topology selection, and secure LNC design for multiple multicasts to maximize the total secure weighted throughput (SWT), which is referred to as the secure delivery for multiple multicasts with multiple streams (SMMS) problem. To this end, we firstly consider the SMMS problem in the case that each sensor is connected with a fixed network device. We then study the SMMS problem when the source of each multicast can be selected from a set of nodes. For the first case, we formulate it to be a linear programming (LP), based on which we give the MORT algorithm to optimally solve it. On the other hand, for the second case, we first formulate it to be an integer linear programming (ILP) and then propose an efficient MBLP algorithm based on linear programming relaxation to obtain a suboptimal solution. Finally, we conduct extensive simulations to show the effectiveness and efficiency of the proposed algorithms.

SDN and NFV enabled service function multicast mechanisms over hybrid infrastructure

Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are two new paradigms which can accelerate service provisioning. Specifically, NFV decouples proprietary network functions from the hardware and implements them in the form of software which is referred to as Virtual Network Function (VNF). In this way, NFV offers great flexibility for service composition and provision. SDN decouples network control from data forwarding and provides a centralized orchestrator for managing and guiding the provision process of services. However, in the context of SDN and NFV, most researches focus on provisioning the unicast service, while the multicast service provision problem lacks sufficient research. The NFV-enabled multicast is important, which involves not only constructing the multicast topology, deploying and chaining VNFs, but also steering traffic through required VNFs before reaching destinations. In this paper, we propose three efficient heuristics to solve the static, dynamic and scalable multicast problems in the context of SDN and NFV. In particular, the static multicast means that end users do not join or leave the multicast session until it ends, while the dynamic multicast means that end users can join or leave dynamically. The scalable multicast means that network functions can be added to or removed from the multicast service dynamically. The novel strategy of the three heuristics is decoupling traffic forwarding and function deployment. With the decoupling, NFV-enabled multicast can be implemented in multiple stages, during which we can achieve a certain extent of reliability by selectively deploying multiple function instances of the same type. In addition, such decoupling also enables adding or removing functions for multicast services easily, which means that we can also achieve a certain extent of function scalability. The experiment results are achieved under the hybrid environment and show that the proposed heuristics can effectively address the multicast problem in the context of SDN and NFV.

Optimized buffer allocation for video multicasting applications with virtual memory implementation

Memory requirement is a key issue when servicing more number of nodes in a heterogeneous environment. We have to ensure an optimum buffer size in order to reduce the initial latency. In this paper, we propose a novel approach, which involves, augmenting a virtual memory (VM) with the existing physical memory of the video buffer. In addition to the benefits of improved queuing size, it also paves the way for better quantization, ordering of frames, and higher error resiliency. Instead of allocating the virtual memory as a single file, it is fragmented according to the number of nodes in a specific multicast group. This avoids the flushing of an entire buffer to begin a new streaming. Furthermore, this avoids the requirement of proxy servers for each multicast group. Hence, this reduces the burden of the server, when a new user joins the multicast session later, requesting same content. VM also facilitates a platform to support old and advanced graphical interface irrespective of device capability. A bit rate reduction technique is also applied to video streams which enables seamless streaming even in degraded network. Unlike existing buffer adaptation techniques, this method does not require a feedback loop, as most of the rate adaptation is processed by the VM. Extensive simulation results show that this research work helps in significant improvement in throughput, PSNR (peak signal-to-noise ratio) when compared to existing buffer management algorithms such as RBA (rate-based adaptation), BBA (buffer-based adaptation), Elastic, and FESTIVE (Fair, Efficient, and Stable adapTIVE algorithm).

Relay Selection for Multi-Channel Cooperative Multicast: Lexicographic Max–Min Optimization

Cooperative multicast has been demonstrated to achieve significant performance gain over the classic source–destination transmission paradigm by exploiting spatial diversity through the participation of multiple relay nodes. As a major technical challenge, the selection of relays for a multicast session has significant impact on the multicast performance. The challenge is even more pronounced when the number of channels is limited as the relay selection is in this context coupled with channel allocation. The goal of this paper is to design a fair multicast relay selection scheme with limited channel resources. Specifically, we establish an analytical framework for this joint relay selection and channel allocation problem and develop a lexicographic max–min multicast relay selection scheme. Our design consists of two technical steps. First, we consider the maximization of the minimal data rate. By decoupling relay selection and channel allocation, the problem is transformed to a max–min–max problem, which is difficult to solve. To make this problem tractable, we reformulate it as a convex optimization problem via relaxation and smoothing, and prove the asymptotic equivalence from a geometrical perspective. Second, we propose an adjustment algorithm based on the initial max–min solution, and prove that the proposed scheme achieves lexicographic optimality. Finally, our proposed algorithm is evaluated by simulation to show its superiority over the conventional schemes.

Joint Optimization for Multicast Provisioning in Mixed-Line-Rate Optical Networks With a Column Generation Approach

Mixed-line-rate (MLR) optical networks (e.g., 10/40/100 Gb/s) offer a new paradigm in backbone networks to meet the increasing traffic demands. They are considered as a transitional solution for future flexible and dynamic optical networks. In order to provision multicast in MLR optical networks, we need to address multicast routing, line rate selection, and wavelength assignment subproblems, while still respecting the maximum transmission reach. In this paper, we investigate the multicast provisioning problem, which aims at minimizing the total cost on transponder, wavelength channel, and wavelength usage. First, a lightpath-based joint integer linear programming (ILP) model is formulated to minimize the total cost. To overcome the scalability of this joint ILP model, a decomposition approach based on column generation is proposed, which achieves comparable results within an extremely short period of time. Extensive simulations are performed to study the impact on the total cost of multicast provisioning with the MLR regarding the number of multicast sessions, destinations, traffic amount, and network topologies. It is observed that the multicast provisioning with the MLR has significant total cost savings over the single line rate, especially in the scenarios of a large number of multicast sessions and in optical networks with small average nodal degree.

Big Data based Self-Optimization Networking: A Novel Approach Beyond Cognition

AbstractIt is essential to satisfy class-specific QoS constraints to provide broadband services for new generation wireless networks. A self-optimization technique is introduced as the only viable solution for controlling and managing this type of huge data networks. This technique allows control of resources and key performance indicators without human intervention, based solely on the network intelligence. The present study proposes a big data based self optimization networking (BD-SON) model for wireless networks in which the KPI parameters affecting the QoS are assumed to be controlled through a multi-dimensional decision-making process. Also, Resource Management Center (RMC) was used to allocate the required resources to each part of the network based on made decision in SON engine, which can satisfy QoS constraints of a multicast session in which satisfying interference constraints is the main challenge. A load-balanced gradient power allocation (L-GPA) scheme was also applied for the QoS-aware mult...

Directional core selection approach and dynamic tree reorganization for delay and delay variation multicast routing

SummaryMulticast communication constrained by end‐to‐end and interdestination delay variation is known as delay and delay variation–bounded multicast. These constraints are salient for real‐time multicast communications. In this paper, we propose a directional core selection algorithm for core selection and delay variation–bounded multicast tree generation. Another algorithm, based on k‐shortest paths, is proposed to further decrease the interdestination delay variation of the trees generated by directional core selection. We also propose the dynamic version of both algorithms that respond to dynamic join and leave requests to the ongoing multicast session by reorganizing the tree and avoiding session disruption. Simulations show that the proposed algorithms surpass existing algorithms in end‐to‐end delay, interdestination delay variation, execution time, and failure probability.

Multicast-Based Optimized Peer Control for Efficient P2P Video Streaming in TDM-PONs

An important issue in network traffic management for Internet service providers (ISPs) is how to efficiently handle a large amount of data traffic generated by peer-to-peer (P2P) applications. This paper discusses the efficiency of P2P video streaming in time-division-multiplexed (TDM)-passive optical networks (PONs). We summarize the technical requirements that are required to efficiently serve P2P video streaming in the broadcast-and-select architecture of the TDM-PON. The proposed localized multicast-based P2P (LM-P2P) mechanism controls generation of P2P sessions adaptively based on information about the peer location and multicast efficiency in the optical line termination (OLT) domain. The centralized control node of LM-P2P selects a multicast seeder and recommends it to later clients as a seeder so that the amount of P2P streaming traffic can be minimized both in the inter-OLT domain and in the intra-OLT domain. The efficiency of LM-P2P in allocation of network resources is achieved by optimal migration of the property of P2P streaming on the unique architectural feature of TDM-PON. The efficiencies of typical P2P localization and P2P caching are compared with LM-P2P, and the systematic issues in localization of P2P sessions and management of multicast sessions are also discussed. The efficiencies of the proposed mechanism are validated by numerical analysis and practical test results.

Elastic Versus WDM Networks With Dedicated Multicast Protection

We consider the routing and spectrum allocation (RSA) problem of protecting all-optical multicast sessions against a single link failure in elastic optical networks (EONs). A tree is derived to support a multicast session and can be considered as a set of paths originating from a common source. We use a scheme to protect each of the paths by an arc-disjoint backup path in the case of any link failure. For this problem, we provide a node-arc integer linear programming (ILP) formulation and propose a heuristic algorithm for this protection scheme. We evaluate the improvement achieved by the flexible grids adopted in EONs over the fixed-grid wavelength-division multiplexing (WDM) networks. The evaluation is done by considering static modeling based on ILP and heuristics as well as dynamic simulations. We consider two approaches for heuristic algorithms: one is a two-step (TS) approach that computes the routing trees then allocates spectrum. The other uses the spectrum window plane (SWP) and constructs auxiliary graphs for the relevant range of spectrum to jointly solve the RSA problem. We evaluate the performances of the proposed algorithms under static and dynamic traffic models. Based on the studied scenarios, we observe consistent improvement in efficiency of flexible grid EONs over fixed-grid WDM networks. Moreover, we demonstrate that the network size (likely because of the availability of more alternative routes) can significantly affect the benefit in efficiency achieved by the SWP-based approaches over the TS approaches.