Packet Transmission Process Research Articles

Study of the probabilistic and temporal characteristics of wireless networks using the CSMA/CA access method

Objectives. The aim of this study is to develop analytical methods to evaluate the probabilistic and temporal characteristics and performance of wireless networks using the CSMA/CA access method. These methods enable the process of selecting rational operating modes to be automated and the impact of collisions in networks implementing the 802.11 protocols to be reduced.Methods. The methods employed herein include reliability theory, theory of random processes, queuing theory, and the Laplace–Stieltjes transform.Results. A problem statement is presented and developed, along with an analytical method for evaluating the probabilistic and temporal characteristics and performance of wireless networks using the CSMA/CA access method. This method considers time constraints on information transmission, thus expanding the applicability of previously proposed analytical approaches for studying Ethernet local area networks. The analysis of networks that use the CSMA/CA access method was carried out. An original mathematical model was developed that allows evaluating various characteristics of packet transmission processes in wireless networks under time constraints on the transmission. These characteristics include latency, packet transfer time, node load, and network performance. A software package was developed to simplify the analysis and evaluation of various operation modes of wireless networks using the CSMA/CA access method.Conclusions. We demonstrate the need for developing nested analytical models describing packet transmission processes in wireless networks under time constraints on link-layer transmission. This implies the development of more complex models for more exact description of packet transmission processes in such networks. The software package developed herein enables the various options for the functioning of the network to be studied and analytical calculations to be performed. Calculations were carried out, in order to assess the probabilistic and temporal characteristics of packet transmission processes and the wireless network performance. The research involved varying the number of workstations and the intensity of packet flows entering the network nodes under the time constraint on packet transmission. The application of the developed mathematical models will be useful in creating and optimizing wireless networks such as Wi-Fi networks, networks based on the IEEE 802.11 standard, and other data transmission systems using the CSMA/CA access method. Such models and the analysis based on them will be useful in optimizing network performance, adjusting parameters, as well as selecting the capacity and configuration of wireless networks.

Hierarchical Q-learning-enabled neutrosophic AHP scheme in candidate relay set size adaption in vehicular networks

Cooperative candidate relay sets (CRS) in opportunistic broadcast paradigms can significantly improve the performance efficiency of traditional broadcast schemes by simultaneously scheduling multiple vehicles in the data packet transmission process. Nonetheless, multiple relay synchronization may cause enormous data redundancy and high delays in data delivery, resulting in a high cooperative transmission cost. High vehicle velocities and vehicular topology restrictions, including intersections, exacerbate the cooperative transmission cost. Motivated by a trade-off between delay and delivery ratio via reducing duplicate data packets and redundant relays, we address this gap in this paper. To this end, we propose an adaptive candidate relay set (ACRS) size scheme based on the Neutrosophic Set Analytic Hierarchy Process (NS-AHP) technique assisted by a Q-learning algorithm. The NS-AHP pair-wise comparison matrix includes; redundancy, cooperative-based efficiency, and relay set stability as the decision-making attributes. Meanwhile, we use a hierarchical Q-learning approach based on the time-varying vehicular environment to adjust the relative preference of the attributes and alternatives (i.e., various CRS sizes) over each other. To optimally learn the relative preference values of the attributes and alternatives over each other, reward functions are set dynamically at both levels. Comprehensive simulations via NS-2 and SUMO are carried out to assess the efficacy of our ACRS scheme compared to three commonly used baseline techniques of fixed size, threshold-based, and probability-based techniques. Overall, the average yields obtained from the experimental outcomes in the urban and highway scenarios show that the ACRS scheme, on average, improves the packet delivery ratio by 3.77%, 5.36%, and 1.35%; reduces the single-hop delay by 34.78%, 42.085%, and 19.39%; reduces the end-to-end delay by 34.76%, 42.72%, and 21.35%; improves the transmission throughput by 34.24%, 41.54%, and 19.305%; and reduces the redundancy ratio by 43.69%, 50.66%, and 24.32% compared to the fixed size, threshold-based, and probability-based techniques, respectively.

An Enhanced Energy-Efficient Data Collection Optimization Algorithm for UAV Swarm in the Intelligent Internet of Things

In the case of limited endurance of unmanned aerial vehicles (UAVs), in order to further improve UAV data collection efficiency, this paper puts forward EDC-UAVIIoT: an enhanced energy-efficient data collection optimization algorithm for UAV swarm in the intelligent Internet of Things. First of all, the algorithm optimizes the UAV cruise path through the intelligent Internet of Things routing mechanism, avoids the occurrence of data errors in the packet transmission process, and uses the end-to-end transmission error probability model. The error probability of data packets in the transmission process is calculated to improve the efficiency of data collection tasks and data throughput. Secondly, considering the relationship between energy harvesting and energy consumption balance, this paper uses semi-definite programming and a convex approximation algorithm to transform the non-convex optimization problem into a convex optimization problem and realize the mapping relationship between the UAV cluster node and the target node coordinates, which reduces the computational complexity. Finally, the simulation results show that the EDC-UAVIIoT algorithm is compared with other algorithms in network energy consumption, running time, network delay, and network throughput. The numerical values are increased by 7.03%, 10.16%, 12.39%, and 8.82%, respectively, thus verifying the effectiveness and stability of the proposed EDC-UAVIIoT algorithm.

Energy Auditing and Broken Path Identification for Routing in Large-Scale Mobile Networks Using Machine Learning

In mobile computing, all nodes are movable nodes, which causes many problems for transmitting data packets in a sequence manner; since the mobile nodes are connected with each other, during movement, nodes make the connection fail or damaged. This kind of link damage is caused by nodes that travel out of range from the network limit and also affect the packet success rate. This reduces the network lifetime and detection efficiency and increases the communication overhead. Every mobile node in mobile computing is an unstable node, causing numerous problems for broadcasting data packets in a series method. When the mobile nodes are connected to each other, relay nodes cause the link to break or else sustain damage. This type of connection failure is brought on by nodes that leave the network’s permitted range, which also lowers the packet success rate. The link failure cannot be recovered by the multipath routing algorithm. As a result, the communication overhead is increased while the network lifetime and detection effectiveness are reduced. Then, the novel energy routing (NER) method that has been proposed is employed to support the energetic routing path across the middle nodes. It is challenging to locate the failed channels and carry on with the successful packet transfer. The master node selection algorithm is intended to identify the best relaying node, fault-free packet transmission process among the network structure’s relaying nodes. The master node is efficiently chosen in this manner. The master node, also known as the energy-based important node, is employed in the mobile network to carry out error-free packet transmission procedures. The other nodes are lower energy nodes that do not participate in packet forwarding, and this algorithm only detects the higher energy successful nodes. This lengthens the network’s lifespan, improves detection effectiveness, and lowers communication overhead. The energy-based heavy node is also known as the master node, which is used to perform a problem-free communication process in the mobile network. This algorithm only accepts the higher energy successful node; the remaining nodes are lower energy nodes which do not perform the communication process. This increases the network lifetime and detection efficiency and reduces the communication overhead. The performance metrics for the proposed system is evaluated by end to end delay, communication overhead, throughput, detection efficiency, network lifetime, and packet drop rate.

Intrusion detection in healthcare domain using machine learning

Intrusion detection system is considered as one of the main sources for protection of important information and communication technologies especially in healthcare networks. Intrusion detection system must be updated frequently because of intrusions that improves periodically. Due to particular limitations such as resource-constrained devices, limited memory and battery capacity of nodes, and unique protocol stacks, traditional intrusion detection algorithms must be updated and improved for application to the Internet of Things. To address this issue, a lightweight attack detection approach based on supervised machine learning–based FIDS (Frothy Disturbance Intrusion Detection System) was developed to detect an adversary attempting to inject unneeded data into the network. FIDS can play an important role in intrusion detection. The proposed model was trained with KDD (Knowledge Discovery in Database) dataset using SVM (Support Vector Machine) algorithm. AODV (Ad-hoc- on-demand Distance Vector) routing protocol was used for routing to make it more energy efficient since the energy usable was limited. The process of packet transmission was done with the help of clustering algorithm to separate the sensors into groups with each group containing a cluster head. 

Construction of an Innovative Development Model of Intelligent Media under the Coverage of a Wireless Sensor Network

A distributed network composed of sensor nodes with limited computing and communication capabilities is a wireless sensor network, which is a system that can autonomously and intelligently complete target tasks according to the surrounding environment. With its wide application in the fields of smart medical care, smart home, networks of vehicles, and smart media, its communication performance requirements are also increasing. According to the needs of different application scenarios, the first key problem to be solved in wireless sensor networks is what optimization coverage strategy to adopt, which will have a direct impact on the optimal allocation of very limited resources such as node energy, communication bandwidth, computing power, and other network services’ quality. Nodes adopt a probability-based joint perception model, and its algorithm is a node scheduling mechanism based on the connected dominating set to construct a tree. Each node sets the waiting time and becomes a candidate node priority according to the remaining energy and the distance from the parent node. In this paper, the issue of energy fairness is considered in heterogeneous wireless sensor networks. In order to prevent the occurrence of “energy holes,” this paper proposes a node deployment model similar to cellular networks. By deploying heterogeneous sensor nodes in this way, energy saving can be achieved. Based on this model, game theory is used to simulate the data packet transmission process between sensor nodes, an energy consumption mechanism suitable for each stage of data transmission is proposed, and Nash equilibrium is finally obtained by rationally designing the measurement function. The node deployment scheme proposed in this paper not only balances the energy consumption of the network but also prolongs the life cycle of the network. Aiming at the three-dimensional (3D) space environment, this paper studies a node deployment mechanism that guarantees connectivity and has a perceptual coverage degree of k with the help of the Reuleaux tetrahedron model. In this paper, a node deployment strategy is proposed and compared with the node deployment algorithm for 3D sensor network based on truncated octahedron. The simulation experiment results show that the wireless sensor network with artificial intelligence can not only optimize the production process of intelligent media but also improve each link of the media industry chain and further catalyze the development of new formats in the media industry. The experimental results also show that the algorithm can effectively meet the requirements of sensing coverage and connectivity coverage, the number of working nodes is small, the network life cycle is significantly prolonged, and the overall energy consumption of the network is reduced. The study results of this paper provide a reference for follow-up research on the construction of innovative development model of intelligent media under the coverage of wireless sensor network.

Design and Analysis of MEC- and Proactive Caching-Based $360^{\circ }$ Mobile VR Video Streaming

Recently, 360-degree mobile virtual reality video (MVRV) has become increasingly popular because it can provide users with an immersive experience. However, MVRV is usually recorded in a high resolution and is sensitive to latency, which indicates that broadband, ultra-reliable, and low-latency communication is necessary to guarantee the users’ quality of experience. In this paper, we propose a mobile edge computing (MEC)-based 360-degree MVRV streaming scheme with field-of-view (FoV) prediction, which jointly considers video coding, proactive caching, computation offloading, and data transmission. To meet the requirement of stringent end-to-end (E2E) latency, the user’s viewpoint prediction is utilized to cache video data proactively, and computing tasks are partially offloaded to the MEC server. In addition, we propose an analytical model based on diffusion process to study the packet transmission process of 360-degree MVRV in multihop wired/wireless networks and analyze the performance of the MEC-enabled scheme. The simulation results verify the accuracy of the analysis and the effectiveness of the proposed MVRV streaming scheme in reducing the E2E delay. Furthermore, the analytical framework sheds some light on the impacts of system parameters, e.g., FoV prediction accuracy and transmission rate, on the balance between computation delay and communication delay.

Data traffic capability of double-layer network based on coupling strength

The two-layer network model offers us a new viewpoint to observe the traffic dynamics of multilayer network systems. An efficient coupling mechanism is of great importance for alleviating the traffic congestion on two-layer networks. In order to reduce the network congestion and improve network transmission performance, the coupling mechanism between two layers of network and three coupling methods, which are random coupling, disassortative coupling and assortative coupling, are studied based on degree correlation. The packet transmission process is analyzed with both the shortest path routing strategy and degree-based weight routing strategy. The influences of the coupling mode and its corresponding routing strategy on the traffic capacity of the two-layer network are studied. In this paper, two scale-free networks are used to construct the two-layer network for simulation experiments. The network scale is in a range from 200 to 2400 with the value of average degree being 8. We focus on the traffic dynamics of two-layer network, and analyze the relationship between the traffic capacity and the three coupling modes, which are random coupling, disassortative coupling and assortative coupling, under the constraints of the shortest path routing strategy and the weight-based routing strategy. According to the characteristics of the coupling connection between the two layers of network, the best coupling method which is suitable for a certain routing strategy should be investigated. The suitable coupling connection between the two layers can effectively increase the traffic capacity. Both numerical result and analytical result show that the packet generation rate, average transmission time, and average throughput can be obviously improved under the shortest path routing strategy with the disassortative coupling method. When the degree-based static weight routing strategy is used, the traffic performance parameters such as packet generation rate, average transmission time, and average throughput can reach the optimal values with the assortative coupling method. It makes the traffic flow uniform that the routing strategy is chosen with the most suitable coupling method on the two-layer network, and the network traffic capacity may be effectively enhanced. More generally, the results indicate that the coupling modes can give rise to traffic behavior that relies subtly on the routing strategy on the two-layer network. Our work may shed some light on the design and optimization of some real traffic or communication networks.

A Dynamic Multipath Scheme for Protecting Source-Location Privacy Using Multiple Sinks in WSNs Intended for IIoT

Among several new technologies, such as social and cognitive mobile computing, wireless sensor networks (WSNs) constitute the founding pillar of the industrial Internet of Things. These networks are expected to play an increasingly important role in our daily lives. Social and cognitive mobile computing requires the sharing of data recorded by sensor nodes. However, the data can be vulnerable to attacks. It is of utmost importance to protect the users privacy while ensuring the security of the WSNs. This investigation is focused on the source-location privacy (SLP) of WSNs. This article proposes a dynamic multipath privacy-preserving routing (DMPPR) scheme based on multiple sinks for protecting the privacy. Different from single sink schemes, the technique of using multiple sink nodes to protect SLP is discussed in this article. Furthermore, a packet-slicing transmission scheme that generates a large number of dynamic routings based on multiple sink nodes is adopted for transmitting the packets. Local adversaries are considered, and to cope with these adversaries, a transmission loop, constructed using real and fake packets, is proposed to confuse the adversaries during the source detection process. The aim is to break the sociality between the sensor nodes. Simulations performed in MATLAB show that the proposed method outperforms similar existing schemes in terms of the secure time, adversary's capture probability, and node utilization ratio. Moreover, the DMPPR scheme also reduces energy consumption by allowing more nodes in the nonhotspot areas to participate in the packet transmission process.

Integrating power assignment into energy‐efficient routing in E2E retransmission systems

Routing design is an effective mechanism to improve the energy-efficiency in packet transmissions for wireless multihop networks. Meanwhile, the total energy consumption for packet transmissions over a path comprising of several unreliable links depends on the power assignment on each link. In this study, the authors address the energy-efficient routing, which integrates with the optimal power assignment, in end-to-end (E2E) retransmission systems. The process of packet transmission across a path in E2E systems is modelled as a random walk. The expected energy consumed for the packet transmission is then calculated. As the expected energy consumption closely relies on the transmit power assigned on the path, it is necessary to integrate the power assignment into the energy-efficient routing. The optimal power assignment on the candidate path is analytically derived for minimising the expected energy consumption. Specially, the energy-efficient routing integrated with power sssignment (EERPA) algorithm is developed to find the optimal path among all candidate paths with all possible power assignments. Simulations demonstrate the efficiency of the authors' EERPA algorithm.

RETRACTED ARTICLE: Cognitive learning performance assessment and analysis with CSCL applied on the NetGuru platform and CSPL applied on the TAoD platform for the network experiment class

How to find the best learning performance in the network experimental course is an important research topic. Therefore, collaborative learning and personalized learning have been applied in traditional classes for a similar significance regardless of how times change and advancements develop. We used the computer-supported collaborative learning (CSCL) pedagogy with NetGuru network experimental platform and the computer-supported personalized learning (CSPL) pedagogy with the teaching assistant on demand (TAoD) network experimental platform, respectively, in the “Network Engineering Lab (1)” course to assess the distinctions in impacts for the two methods. The objective students were four junior classes of ordinary students in the department of Computer Information and Network Engineering. As a rule, one should think about that CSCL pedagogy is better than CSPL pedagogy because of discussion and collaborative learning between students for learning performances. Nonetheless, the fact that the missing and late rates of students in technical and vocational college are a lot higher that makes adopting CSCL pedagogy difficult. Therefore, we designed and made some assistant materials of “graphical-based teaching powerpoint slides,” “animations of packet transmission process for network protocol theories,” and “Customized IP-oriented template-based assignments (simplified as CIPOTA or template-based assignment)” to be applied to compare and analyze the network practices of CSCL-based on NetGuru platform and CSPL-based on TAoD platform. We also design “satisfaction scale of learning performance” to analyze the students’ satisfaction degrees of learning performance with the pedagogy (CSCL or CSPL), the assignment form (normal assignment or template-based assignment), and the learning satisfaction (CSCL or CSPL combines the normal assignment or template-based assignment). They were for the most part being utilized to demonstrate that TAoD platform-based CSPL pedagogy is truly appropriate for network experiment courses. And the CSPL pedagogy is not more terrible than the CSCL pedagogy and may even bring about optimizing learning results for the learning of network experiment course.

MoHoP: A protocol providing for both mobility management and host privacy

The types and numbers of moving objects connected to the Internet are rapidly increasing. Thus, a number of methods have been proposed to provide mobility to moving objects and to ensure host privacy. However, when both methods are applied at the same time without considering their interoperation, either host privacy cannot be provided or packets are delivered to an incorrect location. In this paper, we propose a protocol termed MoHoP which provides both mobility management and host privacy simultaneously. MoHoP obtains the identifier of a mobile node by decoding an anonymized identifier included in a packet. Using the obtained identifier in a distributed hash table, it finds an edge router to which a mobile node is connected, and delivers the packet. We implemented MoHoP in a testbed and proved that it supports mobility. Moreover, the identifier of a mobile node is not exposed in a packet header during the packet transmission process. Our experiment also demonstrated that MoHoP offers low protocol overhead and low handover delay.

A full-featured efficient clustering mechanism for improving QoS in MANETs

Due to the dynamicity of MANET's topology and its infrastructureless nature, various problems arise from those inherent properties which degrade the QoS. Those negative issues are the energy constraints, problems related to broadcasting, high node mobility, unpartitioned network, and various challenges faced during the path discovery, route selection, packet scheduling and packet transmission processes, and security issues. To find an efficient solution to all those problems, in this paper, we propose a robust algorithm; Full-featured secure routing clustering algorithm with energy-aware and scheduling capabilities for highly increasing QoS in MANET (FSR-CAES), an efficient clustering technique which is a combination of numerous algorithms, each one containing one of the previously mentioned problems. The simulation results are provided with the NS-2 simulator varying the number of nodes and the evaluating parameters namely the routing overhead, packet delivery ratio, normalised routing load, and the average end-to-end delay while comparing the performance of our proposed scheme with neighbour coverage-based probabilistic rebroadcast (NCPR), a routing protocol specialised in providing high QoS in MANETs as it is efficient in reducing the routing overhead in the network. The outcomes prove that our proposed scheme outperforms NCPR for all the studied scenarios for small, medium, and large MANETs.

A full-featured efficient clustering mechanism for improving QoS in MANETs

Due to the dynamicity of MANET's topology and its infrastructureless nature, various problems arise from those inherent properties which degrade the QoS. Those negative issues are the energy constraints, problems related to broadcasting, high node mobility, unpartitioned network, and various challenges faced during the path discovery, route selection, packet scheduling and packet transmission processes, and security issues. To find an efficient solution to all those problems, in this paper, we propose a robust algorithm; Full-featured secure routing clustering algorithm with energy-aware and scheduling capabilities for highly increasing QoS in MANET (FSR-CAES), an efficient clustering technique which is a combination of numerous algorithms, each one containing one of the previously mentioned problems. The simulation results are provided with the NS-2 simulator varying the number of nodes and the evaluating parameters namely the routing overhead, packet delivery ratio, normalised routing load, and the average end-to-end delay while comparing the performance of our proposed scheme with neighbour coverage-based probabilistic rebroadcast (NCPR), a routing protocol specialised in providing high QoS in MANETs as it is efficient in reducing the routing overhead in the network. The outcomes prove that our proposed scheme outperforms NCPR for all the studied scenarios for small, medium, and large MANETs.

Joint Design of Routing and Power Control Over Unreliable Links in Multi-Hop Wireless Networks With Energy-Delay Tradeoff

Energy consumption and delay in end-to-end transmission, two significant cost metrics for guiding the design of routing protocols, are often relevant and even conflicting with each other. Therefore, it naturally becomes important to identify the tradeoff between them. In this paper, we investigate the joint design of routing and power control over unreliable communication links in multi-hop wireless networks with energy-delay tradeoff. Two popular retransmission schemes, hop-by-hop (HBH) scheme and end-to-end (E2E) scheme, are adopted to achieve the reliable transmissions over unreliable links. We model the process of packet transmission in HBH or E2E scheme as a random walk and then calculate the expected energy consumption and the expected delay needed to forward a packet. An expected cost function is defined to capture the tradeoff between energy consumption and delay. Due to the correlation between cost function and transmit power assigned on each link, power control technique is necessary to be integrated into the minimum expected cost routing (MECR) for each retransmission scheme. We prove that the optimal power assignment for each link in a candidate path, which minimizes the expected cost for packet transmission, uniquely exists. Then, the MECR algorithms are proposed for both HBH scheme and E2E scheme to find the optimal routing paths. Simulations illustrate that our proposed protocols not only attain the tradeoff between energy consumption and delay, but also outperform the existing protocols in terms of energy-efficiency and delay.

A MARKOV-MODULATED DIFFUSION MODEL FOR ENERGY HARVESTING SENSOR NODES

This paper presents a probability model of an energy-harvesting wireless sensor node, with the objective of linking quality of sensed data to energy consumption and self-sustainability. The model departs from the common energy discretization framework used in the literature, and instead uses a diffusion process modulated by discrete packet arrival and transmission processes for the detailed representation of renewable energy supply, consumption and storage. An analytical–numerical method is developed to compute the average time until the node experiences an outage, due to lack of energy, for a given workload and ambient energy characteristics, battery capacity and initial charge. The results are illustrated with numerical examples.

Zoning and Relaying-Based MAC Protocol With RF Recharging

Radio-frequency (RF) recharging can extend maintenance-free operation of wireless sensor networks. However, the period between recharging is limited by the distance between the most distant sensor node and the master, which sends out recharging pulses. To increase this period, we propose a zoning scheme in which nodes are logically grouped into circular zones centered at the master so that nodes in a given zone send their data to their neighbors in the next closer zone, which act as relays. We describe and analyze a polling Medium Access Control (MAC) protocol that supports zoning and relaying through a probabilistic model of the energy depletion process and a queueing model of the packet transmission process. Our results indicate that zoning extends the time interval between recharge pulses and leads to equalization of node lifetimes, but limits the available data transmission bandwidth as well.

Hash searching and network coding based constant retransmission for wireless multicast

This study is concerned with the network coding (NC) problem in error-prone wireless multicast networks. A hash searching and NC-based constant retransmission scheme (HSNCR) is proposed to make combination selection, where the retransmission of the packet losses can be carried out during the whole process of original packet transmission, and thus the HSNCR can increase the possibility of NC. Furthermore, this new scheme maximises the efficiency of every retransmission by only retransferring an optimum combination or maximum combination of original lost packets. To support HSNCR, an efficient hash searching approach is also designed for the combination selection of original lost packets. Simulation results show that the authors’ proposed scheme indeed outperforms previous works in reducing the number of retransmission.

Performance evaluation of multiple relays cooperative GBn-ARQ with limited retransmission

We investigate the performance of multiple relays cooperative go back n automatic repeat request(MRC-GBn-ARQ) protocol with limited retransmission. An N +2-state Markov transition model is constructed for analyzing arbitrary packet transmission process with limited retransmission. Then the system’s steadystate distribution is derived by using the Kolmogorov equations.Further, the mean packet transmission delay and startup delay are obtained respectively; the channel utilization is derived based on discrete-time Geom/G/1 queue model with startup. Also, we get the energy efficiency of the MRC-GBn-ARQ based on energy analytical model. Especially, the presented models are contrary to the classical ARQ protocols of always allowing infinite retransmission, and our analysis of the MRC-GBn-ARQ protocol with limited retransmission provides theoretical results for reducing the system’s delay and energy consumption. Finally, analysis is validated through some numerical simulations.

Delay and energy efficiency analysis of multicast cooperative ARQ over wireless networks

This paper investigates the performance of multicast cooperative ARQ (MCARQ) in wireless networks for reducing the system's waiting time and the sum energy, where the delay and energy analytical model are proposed under equivalent service time and ideal Nyquist pulse. The packet transmission process is modulated by a three-state Markov chain, then the steady-state distribution of the MCARQ is obtained by solving the Markov chain. Further, the queue waiting time and energy efficiency of the multicast ARQ (MARQ) and MCARQ are obtained respectively. Theoretical analysis and simulation results demonstrate that the MCARQ protocol has a better performance than the MARQ in delay and energy efficiency. The presented model has potentially applications in practical systems, e.g. Multi-user MIMO communications.