Mean Packet Delay Research Articles

Modeling and Performance Analysis of LBT-Based RF-Powered NR-U Network for IoT.

Energy harvesting combined with spectrum sharing offers a promising solution to the growing demand for spectrum while keeping energy costs low. New Radio Unlicensed (NR-U) technology enables telecom operators to utilize unlicensed spectrum in addition to the licensed spectrum already in use. Along with this, the energy demands for the Internet of Things (IoT) can be met through energy harvesting. In this regard, the ubiquity and ease of implementation make the RF-powered NR-U network a sustainable solution for cellular IoT. Using a Markov chain, we model the NR-U network with nodes powered by the base station (BS). We derive closed-form expressions for the normalized saturated throughput of nodes and the BS, along with the mean packet delay at the node. Additionally, we compute the transmit outage probability of the node. These quality of service (QoS) parameters are analyzed for different values of congestion window size, TXOP parameter, maximum energy level, and energy threshold of the node. Additionally, the effect of network density on collision, transmission, and energy harvesting probabilities is observed. We validate our model through simulations.

An Optimal Resource Allocation Scheme with Carrier Aggregation in 5G Network under Unlicensed Band

Carrier aggregation (CA) technology in the Fifth-Generation (5G) network can be considered as a major feature for high-rate data services, which can be combined with the concept of 5G in unlicensed band (5G-U) for data offloading to further enhance the efficiency of the scarce licensed spectral resource. However, the introduction of cellular services in an unlicensed spectrum can force unlicensed band users to silent mode. Meanwhile, the coexistence among different radio access technologies operating on the same frequency band is a complex issue, especially considering the requirement diversity of quality of service (QoS) in networking. In this paper, we propose an optimal resource allocation mechanism to maximize system performance satisfaction for multiple types of services with different QoS requirements in the 5G-U network with a CA feature to address the challenge. Additionally, the performance of services in Wi-Fi system is protected by reserving the minimum spectrum resource when offloading for the 5G-U network. Analytical results on the mean ergodic achievable rate of Wi-Fi services and the mean packet delay of 5G services are provided to maximize the system performance satisfaction. Numerical results demonstrate the effectiveness of the proposed algorithm, wherein optimal spectrum and power allocation can contribute to the maximum system satisfaction in a 5G-U network with a CA feature.

An Analysis of the Mixed IEEE 802.11ax Wireless Networks in the 5 GHz Band.

This paper presents an analysis of the IEEE 802.11ax networks' coexistence with legacy stations, namely IEEE 802.11ac, IEEE 802.11n, and IEEE 802.11a. The IEEE 802.11ax standard introduces several new features that can enhance network performance and capacity. The legacy devices that do not support these features will continue to coexist with newer devices, creating a mixed network environment. This usually leads to a deterioration in the overall performance of such networks; therefore, in the paper, we want to show how we can reduce the negative impact of legacy devices. In this study, we investigate the performance of mixed networks by applying various parameters to both the MAC and PHY layers. We focus on evaluating the impact of the BSS coloring mechanism introduced to the IEEE 802.11ax standard on network performance. We also examine the impact of A-MPDU and A-MSDU aggregations on network efficiency. Through simulations, we analyze the typical performance metrics such as throughput, mean packet delay, and packet loss of mixed networks with different topologies and configurations. Our findings indicate that implementing the BSS coloring mechanism in dense networks can increase throughput by up to 43%. We also show that the presence of legacy devices in the network disrupts the functioning of this mechanism. To address this, we recommend using an aggregation technique, which can improve throughput by up to 79%. The presented research revealed that it is possible to optimize the performance of mixed IEEE 802.11ax networks.

5G Infrastructure Network Slicing: E2E Mean Delay Model and Effectiveness Assessment to Reduce Downtimes in Industry 4.0

Fifth Generation (5G) is expected to meet stringent performance network requisites of the Industry 4.0. Moreover, its built-in network slicing capabilities allow for the support of the traffic heterogeneity in Industry 4.0 over the same physical network infrastructure. However, 5G network slicing capabilities might not be enough in terms of degree of isolation for many private 5G networks use cases, such as multi-tenancy in Industry 4.0. In this vein, infrastructure network slicing, which refers to the use of dedicated and well isolated resources for each network slice at every network domain, fits the necessities of those use cases. In this article, we evaluate the effectiveness of infrastructure slicing to provide isolation among production lines (PLs) in an industrial private 5G network. To that end, we develop a queuing theory-based model to estimate the end-to-end (E2E) mean packet delay of the infrastructure slices. Then, we use this model to compare the E2E mean delay for two configurations, i.e., dedicated infrastructure slices with segregated resources for each PL against the use of a single shared infrastructure slice to serve the performance-sensitive traffic from PLs. Also we evaluate the use of Time-Sensitive Networking (TSN) against bare Ethernet to provide layer 2 connectivity among the 5G system components. We use a complete and realistic setup based on experimental and simulation data of the scenario considered. Our results support the effectiveness of infrastructure slicing to provide isolation in performance among the different slices. Then, using dedicated slices with segregated resources for each PL might reduce the number of the production downtimes and associated costs as the malfunctioning of a PL will not affect the network performance perceived by the performance-sensitive traffic from other PLs. Last, our results show that, besides the improvement in performance, TSN technology truly provides full isolation in the transport network compared to standard Ethernet thanks to traffic prioritization, traffic regulation, and bandwidth reservation capabilities.

Buffer-loss estimation to address congestion in 6LoWPAN based resource-restricted ‘Internet of Healthcare Things’ network

The Internet of Healthcare Things (IoHT) consists of a wide variety of resource-restricted, heterogeneous, IoT-enabled, wearable/non-wearable medical equipment (things) that connect over the internet to transform traditional healthcare into a smart, connected, proactive, patient-centric healthcare system. The pivotal functions of the 6LoWPAN protocol stack enable comprehensive integration of such networks from wearable wireless sensor networks (W-WSN) to IoHT, as TCP/IP does not suffice the requirements of IoHT networks. As a result, the congestion in the IoHT network increases with a growing number of devices, resulting in loss of critical medical information due to buffer loss and channel loss, which is unacceptable. In this paper, we explored different applications of patient-centric IoHT architectures to draw a realistic resource-limited topological layout of IoHT for congestion estimation. After critically reviewing existing congestion schemes for 6LoWPANs, we proposed an effective buffer-loss estimation model based on the Queuing Theory to determine the number of packets lost at the node’s buffer. The buffer is modeled as an M/M/1/K Markov Chain Queue. The M/M/1/K Queue equilibrium equation is used to establish a relationship between the probabilities of the buffer being empty or completely filled. We derived the expressions for total buffer-loss probability and expected mean packet delay for the resource-constraint IoHT network. Furthermore, to validate the buffer-loss estimation, an analytical model is used to compare buffer-loss probabilities, the number of packets dropped at leaf/intermediate nodes and the number of packets successfully received at the local sink node. The results show a close correlation between both the models on varying values of the number of leaf nodes, buffer size, offered packet load and available channel capacity. Thus, in resource-restrictive IoHT, the proposed model performs better than two related works.

Secure Global Positioning System For Vehicle To Vehicle (V2V) Communication

In this paper, we first focused on the developing a secure global positioning system for vehicle-to-vehicle (V2V) communication which adopts the secure transmission with respect to vehicle location. In literature, different existing positioning and wireless communication technologies have been presented with their detailed comparison with the global positioning system. In methodology we proposed a GPS-based model of Contention Intensity Control with Rate Control (CICRC) for efficient and secure V2V communication. We deduced the PDR and mean packet delay between heavy and low vehicle load scenarios under fully-connected vehicle network case and a hidden terminal participation case. We also presented the PDR and mean packet delay of safety messages generated with deterministic inter-arrival time and exponential inter-arrival time, respectively. Our GPS-based CICRC model provides a good match with simulation results on well-known MATLAB tool with wireless and networking toolbox. We also verified the model by showing our simulation provides good match with analytical results. Finally, comparing PDR, mean delay and PCR with proposed CICRC by some metrics, we can verify that CICRC improves V2V communication performance compared to existing communication methods. The simulation results we obtained show the packet delivery ratio under CICRC increases nearly 10% compared with that under CSMA [8] in heavy vehicle load scenarios for secure communication undermining the vehicle location. We have also found that if packet collisions occur in some vehicles at the during V2V communication, the collision probability between those vehicles in deterministic inter-arrival time will be always higher than that in exponential inter-arrival time. Average successful packet reception time under CICRC is around 20ms lower than CSMA in heavy vehicle loads, which verifies that CICRC improves on CSMA for the GPS performance especially in heavy vehicle load scenarios for secure communication

Applying a Dwell Time-Based 5G V2X Cell Selection Strategy in the City of Los Angeles, California

The fifth generation of wireless networks is expected to provide high capacity, low latency, high reliability, and massive connectivity services. Ultra-dense network (UDN) is a clear trend for enhancing capacity, coverage, and load balancing. In UDNs, the cell selection issue for moving vehicles should be addressed. In this paper, a cell selection strategy known as a dwell time estimation (DTE) scheme is proposed, which is based on Vehicle-to-Everything (V2X) communications. It selects small cells that have the longest dwell time in a vehicle’s direction to decrease handover (HO) rate. The proposed DTE scheme is evaluated using two datasets, which are 5G small cells and vehicles datasets, that were collected in the city of Los Angeles in California. The simulation result shows that our DTE algorithm outperforms other recent related schemes in terms of the mean number of HOs by up to 36.26% because it prolongs the dwell time of the vehicle within the serving small cell. Consequently, it reduces the average number of HO failures and unnecessary HOs. In addition, it gives improvements in terms of the average achievable downlink throughput and network energy efficiency. Furthermore, it has superiority over the other schemes in terms of the mean packet delay by up to 16.49%.

Toward lower-diameter large-scale HPC and data center networks with co-packaged optics

We investigate the advantages of using co-packaged optics for building low-diameter, large-scale high-performance computing (HPC) and data center networks. The increased escape bandwidth offered by co-packaged optics can enable high-radix switch implementations of more than 150 switch ports, which can be combined with data rates of up to 400 Gb/s per port. From the network architecture perspective, the key benefits of using co-packaged optics in future fat-tree networks include (a) the ability to implement large-scale topologies of > --> 11 , 000 end points by eliminating the need for a third switching layer and (b) the ability to provide up to 4 × higher bisection bandwidth compared to existing solutions, reducing at the same time the number of required switch application-specific integrated circuits by > --> 80 % . From the network operation perspective, both reduced energy consumption and lower packet delays can be achieved since fewer hops are required; i.e., packets need to traverse fewer serializer/deserializer lanes and fewer switch buffers, which reduces the probability of contending with other packets and improves the tolerance of network congestion. The performance of the proposed architecture is evaluated via discrete-event simulations for a wide range of representative HPC synthetic-traffic cases that include both hotspot and non-hotspot scenarios. The simulation results suggest that co-packaged optics form a promising solution to keep up with bandwidth scaling in future networks, while the reduced number of switching layers can lead to significant mean packet delay improvements that start from 30% and reach up to 74% for high-load conditions.

Modeling and delay performance analysis of wireless regional area networks under incumbent coexistence and self‐coexistence with multichannel operations

SummaryIncumbent coexistence and self‐coexistence are common among wireless regional area networks (WRANs) using TV white space (TVWS) due to their large coverages and opportunistic spectrum access. Among incumbents of WRANs are wireless microphones (WMs) whose frequent ON–OFF activities result in intermittent availability of transmission channels. In this work, WRANs under self‐coexistence in addition to incumbent coexistence are modeled for queueing analysis using two‐dimensional (2D) Markov chains taking into account intermittent channel availability for multichannel operations. The proposed models are created based on the widely used ON–OFF Markov chain model for an individual transmission channel. The Markov chain structures depend on the number of WRANs under self‐coexistence as well as the number of transmission channels. In order to reduce the computational complexity associated with a large number of channels, truncated Markov chain models are proposed so that the scenarios with more channels than WRANs can be analyzed with the same complexity as the scenarios with the same number of channels and WRANs. The matrix geometric method is used to numerically compute steady‐state probabilities of the Markov chain, which are then used to evaluate the mean packet delay performance. These results are then used to quantify the mean packet delay obtained from channel sharing among WRANs under self‐coexistence with multichannel operations. Finally, the impact of varying the number of channels as well as varying the ON‐OFF durations of each channel on the delay performance is observed.

Impact of Offloading on the Efficiency of Wireless Access Networks

Wireless access networks need to deliver a satisfactory level of Quality of Service (QoS) to their subscribers. The service quality can be measured through various metrics, for example the mean packet delay, average throughput, the jitter and bandwidth. Based on the type of network application, one or the other can be more important. Mobile data offloading has a crucial effect on the efficiency of wireless access networks. Offloading decreases the load on mobile networks (LTE) which frees the band to other users and consequently improves the QoS level. Also data offloading reduces the cost of the downloaded information. In this paper we assess the impact of data offloading on the efficiency of wireless access networks. We employ two popular scheduler algorithms to measure the effect of resource allocation among users. In particular, an analytical model for mixed LTE and WiFi access networks is developed. The model takes into account the role and the effect of various application demands. The model evaluates the wireless access networks behavior when some portions of network service zones are tenanted by different application types. Using the real network simulation NS3, the network performance metrics (the average throughput, delay and packet loss) are investigated to evaluate the network performance under diverse traffic loads.

Downlink Analysis of NOMA-Enabled Cellular Networks With 3GPP-Inspired User Ranking

This paper provides a comprehensive downlink analysis of non-orthogonal multiple access (NOMA) enabled cellular networks using tools from stochastic geometry. As a part of this analysis, we develop a novel 3GPP-inspired user ranking technique to construct a user cluster for the non-orthogonal transmission by grouping users from the cell center (CC) and cell edge (CE) regions. This technique allows the pairing of users with distinct link qualities, which is imperative for harnessing NOMA performance gains. The analysis is performed from the perspective of the typical cell , which is significantly different from the standard stochastic geometry-based approach of analyzing the performance of the typical user . For this setting, we first derive the moments of the meta distributions for the CC and CE users under NOMA and orthogonal multiple access (OMA). Using this, we then derive the distributions of the transmission rates and mean packet delays under non-real time (NRT) and real-time (RT) service models, respectively, for both CC and CE users. Finally, we study two resource allocation (RA) techniques to maximize the cell sum-rate ( $\mathtt {CSR}$ ) under NRT service, and the sum effective capacity ( $\mathtt {SEC}$ ) under RT service. In addition to providing several useful design insights, our results demonstrate that NOMA provides improved rate region and higher $\mathtt {CSR}$ as compared to OMA. In addition, we also show that NOMA provides better $\mathtt {SEC}$ as compared to OMA for the higher user density.

Software-Defined Time-Shifted IPTV architecture for locality-awareness TWDM-PON

IPTV brought great potential to give network providers the capacity to expand their market value and revenue generated by increasing the number of users. Time-shifted IPTV (TS-IPTV) is one way of accomplishment through IP multicasting. Amongst the access network solutions, Ethernet passive optical network (EPON) is regarded as one of the best solutions due to its high bandwidth provision, low operation and maintenance cost. Software-Defined Networking (SDN) separates the network control plane from the data-forwarding plane with the promise to dramatically improve the network resource utilization. Time and wavelength division multiplexed access passive optical network (TWDM-PON) is the ultimate solution for the next generation PON (NG-PON2), in which each wavelength is shared between multiple optical network units (ONUs) by employing the time division and multiplexing access mechanism. Local-awareness based TWDM-PON allows for the higher bandwidth and optimal flexibility, fiber management, service convergence and resources sharing. In this paper, the SDN is integrated into the TWDM-PON architecture to facilitate an orchestrated multicasting time shifted IPTV through the SDN controller to control and manage the traffic. The simulation results show that the proposed architecture and mechanism improves the quality of service (QoS) requirements in terms of the mean packet delay, jitter, throughput and packet loss.

A secured and reliable communication scheme in cognitive hybrid ARQ-aided smart city

Due to advancements in communication technologies, specifically, the Internet of Things (IoT)-based smart cities, the allocation of spectral bands is a major challenge. To overcome this challenge, the cognitive radio network (CRN) has widely been accepted for efficient utilization of the available spectrum. Hence, efficient spectrum utilization and secured communication have attracted significant attention in recent years. However, due to the involvement of smart wireless devices in CRN, the cognitive radio (CR) systems are vulnerable to security threats that mainly target the weaknesses of CR communication and networking. Considering the efficient utilization of spectrum and secured smart city applications, this paper proposes a Secured and Reliable Cognitive Hybrid Automatic Repeat reQuest (SRC-HARQ) scheme. The SRC-HARQ models the primary user (PU) channel by Hidden Markov Model (HMM) to identify the unoccupied spaces. Based on the HMM results, the cluster head (CH) in a smart city determines the activity pattern of PUs and detects idle channels. After the detection of an idle channel, the CH broadcasts a beacon. Upon the reception of a beacon, each member node responds with a ready-to-send (RTS) message along with an encrypted message. The CH replies with a clear-to-send (CTS) signal after the successful decryption of the received message. Furthermore, a 4-state Markov Chain is used for reliability in terms of false alarm and misdetection. The closed-form expressions for mean packet delay, end-to-end delay, and throughput are derived and validated using Monte Carlo simulations.

Internet Provisioning in VANETs: Performance Modeling of Drive-Thru Scenarios

Drive-thru-Internet is a scenario in cooperative intelligent transportation systems (C-ITSs), where a road-side unit (RSU) provides multimedia services to vehicles that pass by. Performance of the drive-thru-Internet depends on various factors, including data traffic intensity, vehicle traffic density, and radio-link quality within the coverage area of the RSU, and must be evaluated at the stage of system design in order to fulfill the quality-of-service requirements of the customers in C-ITS. In this paper, we present an analytical framework that models downlink traffic in a drive-thru-Internet scenario by means of a multidimensional Markov process: the packet arrivals in the RSU buffer constitute Poisson processes and the transmission times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we use iterative perturbation techniques to calculate the stationary distribution of the Markov chain. Our numerical results reveal that the proposed approach yields accurate estimates of various performance metrics, such as the mean queue content and the mean packet delay for a wide range of workloads.

Energy and delay aware massive access management in machine‐to‐machine communications

AbstractMachine‐to‐machine (M2M) communication is a challenging topic in the Internet‐of‐Things era. The increasing growth of machines and high rate of packet production have result in massive access to the network. Therefore, one of the media access control (MAC) challenges in 5G cellular networks is the management of massive access to the wireless media regarding quality‐of‐service (QoS) requirements and battery restrictions of the machines. Delay is one of the QoS requirements that should be guaranteed in most applications. To the best of our knowledge, previous studies on scheduled MAC mechanisms have not addressed energy efficiency and delay requirements appropriately. In this paper, the problem of scheduled massive access management has been considered with the aim of simultaneously meeting delay requirements of machines and increasing energy efficiency. The proposed solution exploits gateways to reuse the spectrum dedicated to M2M communications and introduces a clustering algorithm to allocate radio resources to the machines appropriately. Moreover, an optimization problem is defined and solved using genetic algorithms (GA) to adjust the optimal transmission power of machines, aiming at maximizing the energy efficiency. To preserve delay constraints, the proposed method exploits an existing scheduling algorithm. Simulation results demonstrate more than 50% reduction in probability of packet delay violation for various classes of service and in mean packet delay compared to the baseline method. The results have also shown more than 20% improvement in energy efficiency of proposed method compared to the baseline.

Link state opportunistic routing for multihop wireless networks

Enhancing the quality of service is the crucial issue of future wireless networks. In this paper, we propose a new multihop wireless routing protocol inspired by opportunistic resource allocation strategies that take into account the variability of the radio conditions due to path loss, shadowing and multipath fading. Thanks to this knowledge, our proposition dynamically adapts the selected path accross time. The adaptation is function of each link state and the amount of channel information available. This allows to improve system performance in terms of delay and throughput. This solution can be used in all multihop wireless contexts but can have a special interest in wireless coverage zone extension context. Simulation results will show that the proposed routing protocol greatly outperforms the other existing protocols such as ad-hoc on-demand distance vector, optimized link state routing and extremely opportunistic routing protocols reducing mean packet delays by more than 50% in several scenarii.

Performance Analysis and Optimization of a $N$ -Class Bipolar Network

A wireless network with unsaturated traffic and N classes of users sharing a channel under random access is analyzed here. Necessary and sufficient conditions for the network stability are derived, along with simple closed formulas for the stationary packet transmission success probabilities and mean packet delays for all classes under stability conditions. We also show, through simple and elegant expressions, that the channel sharing mechanism in the investigated scenario can be seen as a process of partitioning a well-defined quantity into portions, each portion assigned to each user class, the size of which determined by system parameters and performance metrics of that user class. Using the derived expressions, optimization problems are then formulated and solved to minimize the mean packet delay and to maximize the channel throughput per unit of area. These results indicate that the proposed analysis is capable of assessing the trade-off involved in radio-resource management when different classes of users are considered.

Investigating Random Linear Coding from a Pricing Perspective.

In this paper, we study the implications of using a form of network coding known as Random Linear Coding (RLC) for unicast communications from an economic perspective by investigating a simple scenario, in which several network nodes, the users, download files from the Internet via another network node, the sender, and the receivers as users pay a certain price to the sender for this service. The mean packet delay for a transmission scheme with RLC is analyzed and applied into an optimal pricing model to characterize the optimal admission rate, price and revenue. The simulation results show that RLC achieves better performance in terms of both mean packet delay and revenue compared to the basic retransmission scheme.

P2P Live-Streaming Application-Aware Architecture for QoS Enhancement in the EPON

Managing a single state-of-the-art ethernet passive optical network optical line terminal (EPON OLT) that can support many customers with different multimedia services and quality of service (QoS) is a challenge. Peer-to-peer (P2P) live streaming is one of the most popular multimedia applications in access networks, especially in the Asia-Pacific region, which requires higher QoS, but such streaming is difficult to manage. Therefore, a new approach is required that can provide flexible control to Internet service providers (ISPs) over their networks. In this paper, we propose a P2P application-aware architecture at the OLT and optical network unit (ONU) that aims to improve overall QoS and, at the same time, preserve user-perceived quality and provide ISPs with flexible control over P2P live-streaming traffic. Finally, a new application-aware dynamic bandwidth allocation (ADBA) is presented. Simulation results show that the proposed architecture can improve the overall QoS in terms of mean packet delay, system throughputs, and jitter, and it can also alleviate inter-ISP traffic bandwidth.

Exact Mean Packet Delay for Delayed Report Messages Multipoint Control Protocol in EPON

The infrastructure to develop the next generation optical access network is the Ethernet passive optical network (EPON). Interleaved polling with adaptive cycle time (IPACT) is a common polling method of an EPON. However, the mean waiting time of packets (= the mean packet delay) with IPACT is large depending on the arriving time of the packets. In this paper, a novel media access method for IPACT is proposed in order to minimize the mean packet delay. The mean packet delay with the proposed method is also derived as the exact solution. This solution is based on the non-trivial simplification of the previous work on the analytical solution for general IPACT. We confirm a close match between simulation and our theoretical results and show the effectiveness of our method.