Channel Idle Time Research Articles

Marine Mammal Conflict Avoidance Method Design and Spectrum Allocation Strategy

Underwater wireless sensor networks play an important role in underwater communication systems. Communication through collaborative communication is an effective way to solve critical problems in underwater communication systems. Underwater sensors are often deployed in spaces that overlap with those of marine mammals, which can adversely affect them. For this reason, in this paper, a marine mammal conflict avoidance method that can be dynamically adjusted according to the channel idle time duration and sensor node demand is designed, and the derivation of the maximum occupancy time duration is performed. Meanwhile, in addition, combining the potential of reinforcement learning in adaptive management, efficient resource optimization, and solving complex problems, this study also proposes a reinforcement learning-based relay-assisted spectrum switching method (R2S), which aims to achieve a reasonable allocation of spectrum resources in relay collaborative communication systems. The experimental results show that the method proposed in this study can effectively reduce the disturbance to marine mammals while performing well in terms of conflict probability, interruption probability, and quality of service.

MR-SFAMA-Q: A MAC Protocol based on Q-Learning for Underwater Acoustic Sensor Networks

<p>In recent years, with the rapid development of science and technology, many new technologies have made people’s exploration of the ocean deeper and deeper, and due to the requirements of national defense and marine development, the underwater acoustic sensor network (UASN) has been paid more and more attention. Nevertheless, the underwater acoustic channel has the properties of considerable propagation delay, limited bandwidth, and unstable network topology. In order to improve the performance of the medium access control (MAC) protocol in UASN, we propose a new MAC protocol based on the Slotted-FAMA of Multiple Reception (MR-SFAMA) protocol. The protocol uses the Q-Learning algorithm to optimize the multi-receiver handshake mechanism. The current state is judged according to the received node request, and the Q-table is established. Through the multi-round interaction between the node and the environment, the Q-table is continuously updated to obtain the optimal strategy and determine the optimal data transmission scheduling scheme. The reward function is set according to the total back-off time and frame error rate, which can reduce the packet loss rate during network data transmission while reducing the delay. In addition, the matching asynchronous operation and uniform random back-off algorithm are used to solve the problem of long channel idle time and low channel utilization. This new protocol can be well applied to unstable network topology. The simulation results show that the protocol performs better than Slotted-FAMA and MR-SFAMA regarding delay and normalized throughput.</p> <p> </p>

QoT-aware adaptive modulation format-based resource provisioning for clustered LR-PON

• This study presents a QoT-aware adaptive modulation format based on resource provisioning (QAMF-RP) algorithm for software-defined long-reach passive optical networks architecture. • The LR-PON architecture incorporates orthogonal frequency division multiplexing-based time-wavelength division multiplex PON (OFDM-based-TWDM-PON), thus high bandwidth utilisation and small bandwidth allocation granularity with limited network resources is possible to deal with this rapid traffic growth. • What’s more, the proposed QAMF-RP algorithm addresses the challenges associated with the higher upstream channel idle time owing to long round trip time and data-reliable transmission for all types of services. • We believe that our study makes a significant contribution to the literature because our results show a promising performance of the proposed system that significantly reduce average latency, improve throughput and network QoS, ensure optimal resource provisioning, and satisfy various service requirements. The range of conventional passive optical networks (PONs) is 20 km, which are difficult to satisfy the requirements of accommodating increasing number of users and coverage areas. Thus, a software-defined long-reach PON (LR-PON) architecture which extends the access network to hundreds of kilometres is proposed in this paper. Using the proposed LR-PON architecture, which incorporates orthogonal frequency division multiplexing-based time-wavelength division multiplex PON (OFDM-based-TWDM-PON), high bandwidth utilisation and small bandwidth allocation granularity with limited network resources is possible to deal with this rapid traffic growth. Further, to address major challenges such as higher upstream channel idle time owing to long round trip time and data-reliable transmission for all types of services, while considering energy consumption, we also propose a quality-of-transmission (QoT)-aware adaptive modulation format-based resource provisioning algorithm that considers the PHY and MAC layers. The results of simulations conducted to verify the performance of the proposed architecture and algorithm demonstrate that they can reduce average latency, significantly improve throughput and network QoS, ensure optimal resource provisioning, and satisfy various service requirements.

Comprehensive Polling and Scheduling Mechanism for Long Reach Gigabit Passive Optical Network

Abstract Dynamic bandwidth assignment (DBA) schemes for long reach PONs face a suffer from higher upstream channel idle time due to long round trip time (RTT). In ITU PONs, the DBA schemes; Immediate allocation with colorless grant (IACG), Efficient bandwidth utilization (EBU) and GPON redundancy eraser algorithm (GREAL) minimize idle time by sending bandwidth grants to the optical network units (ONUs) every downstream frame (DF). EBU further improves IACG by utilizing unused bandwidth (UBW) of other traffic classes. Sending the grant results every DF requires optical line terminal (OLT) to remember all previous grants sent to ONU during RTT and subtract them from the received queue reports. Since, both IACG and EBU assign the excess bandwidth equally to ONUs. Therefore, the OLT is actually not aware of the complete grant to each traffic class and thus do not subtract these completely from receiving reports. This leads to wastage of bandwidth and higher US delays due to over granting. GREAL resolves this problem by not utilizing the excess bandwidth which also leads to increased US delays. The proposed scheme in this study eliminates this shortcoming by allocating excess bandwidth to each traffic class completely at the OLT. Moreover, the UBW assignment mechanism of EBU is also improved. Simulation results show a 50–85 % reduction in delays of type-2 (T2) and type-3 (T3) traffic classes versus GREAL and IACG and up to 40 % reduction in delays for type-4 (T4) versus EBU.

N-DCF: MAC overhead reduction using narrow channel contention in wireless networks

This paper presents a medium access control protocol for wireless networks that improves system spectral efficiency using multiple channels. Use of multiple narrow channels has already been proposed as a solution to reduce MAC overhead, but merely dividing a wide channel into narrow channels cannot mitigate the negative effect of packet collisions especially when the network is densely populated. The proposed protocol, called N-DCF, adds protocol support to reduce packet collisions and improve channel utilization. The main idea is to let each node contend on one of the multiple channels and give the node privilege to access other channels when it successfully finishes transmission on its contention channel. When a node gains privilege to a channel, it can access the channel without contention. Privilege is gained probabilistically so that other nodes can have chance to win the channel and obtain privilege for other channels as well. N-DCF reduces channel idle time by conducting random backoff only on one of the narrow channels and reduces packet collisions by assigning contention channel randomly. Idle channels are not wasted because nodes can access other channels once the node wins its contention channel. Performance evaluation shows that the proposed scheme achieves higher throughput than 802.11 DCF without harming the fairness, regardless of node density, packet size, and number of radios.

FDoF: Enhancing Channel Utilization for 802.11ac

Multi-user multiple input multiple output (MU-MIMO) enables a multi-antenna access point to serve multiple users simultaneously, and has been adopted as the IEEE 802.11ac standard. While several PHY-MAC designs have recently been proposed to improve the throughput performance of a MU-MIMO WLAN, they, however, usually assume that all the concurrent streams are of roughly equal length. In reality, users usually have frames with heterogeneous lengths even after aggregation, leading to different lengths of a transmission time. Hence, the concurrent transmission opportunities might not always be fully utilized when some streams finish earlier than the others in a transmission opportunity. To resolve this inefficiency, this paper presents full degree-of-freedom (FDoF), a PHY-MAC design that exploits a novel power allocation scheme to reduce the idle channel time and further leverages frame padding to better utilize the spatial multiplexing gain. Unlike traditional MIMO power allocation, which aims at maximizing the theoretical sum-rate, FDoF’s power allocation explicitly considers heterogeneous frame lengths and minimizes the channel time required to finish concurrent frames, as a result improving the effective throughput. FDoF’s padding protocol then identifies proper users to reuse the remaining idle channel time, while preventing this padding from harming all the ongoing streams. Our evaluation via large-scale trace-driven simulations demonstrates that FDoF’s improves the throughput by up to $2.83\times $ , or by $1.36\times $ on average, as compared to the conventional 802.11ac. By combining FDoF’s power allocation with frame padding, the average throughput gain can be further increased to $1.75\times $ .

Optimal number of frames transmitted in a sensing based opportunistic spectrum access

The opportunistic spectrum access (OSA) has emerged as promising approach to increase the efficiency in spectrum sharing. The important feature of the OSA is to enable the unlicensed users or secondary users (SUs) to search for unused spectrum vacated by idle licensed user or primary user (PU). In this paper, we consider the maximization of the number of frames sent by the SUs during the idle period (white space) of the PU, while avoiding the infringement into the privileges of the PU. We set up this problem in terms of an optimal stopping problem. Explicit expression for the optimal number of frames that can be sent by the SUs in a white space is derived. Performance analysis for channel utilization and channel idle time is presented. Finally, the analytical results for optimal number of frames sent by SU in white space are numerically illustrated.

Toward enhanced wireless coexistence in ISM band via temporal characterization and modelling of 802.11b/g/n networks

AbstractThis paper presents extensive experimental characterization and empirical modelling of 802.11 temporal behavior. A detailed characterization of 802.11b/g/n homogeneous and heterogeneous network traffic patterns is featured, including idle time distribution and channel utilization. A complete modelling of 802.11 networks in the 2.4 GHz Industrial, Scientific, and Medical band is also presented. Such information can assist the development of other wireless technologies aiming to utilize the crowded Industrial, Scientific, and Medical band more efficiently and to achieve enhanced wireless coexistence. In this work, models are derived for both homogeneous and heterogeneous 802.11 network idle time distributions. Also presented is a case study utilizing 802.15.4 ZigBee transmitter packet size that was adaptively modified based on channel idle time distribution. Results demonstrate superior ZigBee performance and significant enhancement in throughput. Copyright © 2016 John Wiley & Sons, Ltd.

Pliable Cognitive MAC for Heterogeneous Adaptive Cognitive Radio Sensor Networks.

The rapid expansion of wireless monitoring and surveillance applications in several domains reinforces the trend of exploiting emerging technologies such as the cognitive radio. However, these technologies have to adjust their working concepts to consider the common characteristics of conventional wireless sensor networks (WSNs). The cognitive radio sensor network (CRSN), still an immature technology, has to deal with new networks that might have different types of data, traffic patterns, or quality of service (QoS) requirements. In this paper, we design and model a new cognitive radio-based medium access control (MAC) algorithm dealing with the heterogeneous nature of the developed networks in terms of either the traffic pattern or the required QoS for the node applications. The proposed algorithm decreases the consumed power on several fronts, provides satisfactory levels of latency and spectrum utilization with efficient scheduling, and manages the radio resources for various traffic conditions. An intensive performance evaluation is conducted to study the impact of key parameters such as the channel idle time length, node density, and the number of available channels. The performance evaluation of the proposed algorithm shows a better performance than the comparable protocols. Moreover, the results manifest that the proposed algorithm is suitable for real time monitoring applications.

Dynamic bandwidth allocation in heterogeneous WDM EPONs

Several dynamic bandwidth allocation algorithms have been introduced to schedule upstream wavelength channels in wavelength division multiplexing Ethernet passive optical networks (WDM EPONs), but mostly for homogenous WDM EPON networks with the same distance between each optical network unit (ONU) and the optical line terminal. For WDM EPON with heterogeneous round trip times (RTTs), we propose two algorithms for ONU scheduling, called nearest first and early allocation (EA); and a wavelength assignment algorithm, called best fit (BF). Both ONU scheduling algorithms take RTT dissimilarities into account, thus minimizing packet delay and packet drop ratio at ONUs. Additionally, EA can relive the common drawback of offline scheduling, i.e., channel idle time. On the other hand, the BF wavelength assignment is proposed that assigns the best wavelength to each ONU in order to improve network performances in terms of packet queuing delay and packet drop ratio at ONU sides.

Modeling of variable Clear Channel Assessment MAC protocol for Wireless Sensor Networks

Toward devising a new efficient Medium Access Control (MAC) protocol that overcomes the shortcomings of the IEEE 802.15.4 standard MAC, we work on exploiting the Clear Channel Assessment (CCA) feature in a more efficient fashion. This paper proposes the Variable CCA MAC protocol; a new MAC protocol that increases the number of CCAs performed by a node beyond the standard value of two. We develop a Markov-based mathematical model that describes the functionality of this new protocol. We also validate our mathematical model through conducting extensive simulations that focus on a rich set of performance parameters, including the probability of collision, throughput, channel idle time, channel collision time, energy consumption, delay, and reliability.

Design and Analytical Analysis of a Novel DBA Algorithm with Dual-Polling Tables in EPON

Ethernet passive optical network is a point-to-multipoint structure, and an effective media access protocol should be designed for collision avoidance and bandwidth allocation. Most previous researches have aimed to solve the problem using dynamic bandwidth allocation (DBA) algorithms with polling-based schemes. Unfortunately, idle channel time among the polling cycles cannot be overcome efficiently. In this paper, a dual-polling DBA (DP-DBA) algorithm which consists of an interpolling mechanism and an intrapolling mechanism is proposed. The interpolling mechanism helps eliminate the idle time problem while the intrapolling part aggregates the unused bandwidth of the light-loaded users and those due to nondefragmentation of the Ethernet frames of the general users. We also evaluate the performance of the DP-DBA algorithm by a comparison with the interleaved polling with adaptive cycle time (IPACT), the dynamic bandwidth allocation with a modified grant table generation algorithm (DBA2), the Double-Phase Polling (DPP), and the adaptive DBA algorithm with sorting report messages (Sort-DBA) schemes with simulation results. For greater realism with regard to general applications, we also simulate the asymmetric traffic loads at the optical network units (ONUs).The results show that DP-DBA outperforms the other DBA schemes under asymmetric load conditions.

Sensing-Transmission Edifice Using Bayesian Nonparametric Traffic Clustering in Cognitive Radio Networks

In cognitive radio networks, the main objective of spectrum sensing is to exploit spectrum holes left by the primary users (PUs). Different PUs' traffic patterns might provide different opportunities for second user (SU) spectrum access. In this paper, we identify the PUs' traffic patterns and then maximize SU transmission accordingly. First a theoretical framework is developed to cluster PU traffic patterns based on a Bayesian nonparametric inference model, in which the number of traffic types is unknown. Second, in order to exploit the spectrum holes, we study a sensing-transmission structure to optimize the SU transmission strategy. Specifically, we exploit the short and long transmission opportunities based on the PU traffic pattern and channel idle time distribution. Finally, we propose a threshold-based sensing-transmission method that optimizes the SU utility, while protecting PU transmissions. Both sensing and transmission errors are considered for perfect sensing with/without acknowledgement-based transmission and imperfect sensing, respectively. From the simulation results, we show that the proposed technique outperforms the nonparametric mean shift clustering algorithm. Furthermore, we utilize these clustering results to optimize the SU's transmission strategy with perfect and imperfect sensing. We compare our proposed technique with the probabilistic sensing-transmission structure and show the performance gain in terms of throughput.

Primary Traffic Characterization and Secondary Transmissions

Channel idle time distribution based secondary transmission strategies have been studied intensively in the literature. Under various performance metrics, the ultimate performance of secondary devices are eventually dictated by the presumed channel idle time distribution. Such distributions can take any arbitrary form in practice. In this work, we study idle time distributions in wireless local area networks (WLAN) using large amount of the channel idle time data collected in real-world WLAN networks. We demonstrate with experimental data that the channel idle time distribution can be closely modeled by hyper-exponential distribution. Furthermore, one can treat the primary packet arrival process as a semi-Markov modulated Poisson process. Several secondary transmission strategies are discussed under this model. It is shown that using only one hyper-exponential distribution, the secondary user can achieve a desirable performance when the primary packet arrival process is stationary. However, experimental data suggests that in practice, this process is not stationary and the secondary user can experience a large performance loss with stationary transmission strategy. We propose a novel transmission strategy that achieves suboptimal secondary user performance when the idle time distribution is not stationary. The performances of secondary transmission strategies are demonstrated using experimental data.

Closing the gap between traffic workload and channel occupancy models for 802.11 networks

The modeling of wireless network traffic is necessary to evaluate the possible gains of spectrum sharing and to support the design of new cognitive protocols that can use spectrum efficiently in network environments where diverse technologies coexist. In this paper we focus on IEEE 802.11 wireless local area networks and close the gap between two popular levels of modeling, macroscopic traffic workload modeling and microscopic channel occupancy modeling. We consider traffic streams generated by established traffic workload models and characterize the networking scenarios where a simple, semi-Markovian channel occupancy model accurately predicts the wireless channel usage. Our results demonstrate that the proposed channel occupancy model can capture the channel idle time distribution in most of the scenarios, while the Markovian assumption cannot be validated in all cases.

Impact of report message scheduling (RMS) in 1G/10G EPON and GPON

A wide array of dynamic bandwidth allocation (DBA) mechanisms have recently been proposed for improving bandwidth utilization and reducing idle times and packet delays in passive optical networks (PONs). The DBA evaluation studies commonly assumed that the report message for communicating the bandwidth demands of the distributed optical network units (ONUs) to the central optical line terminal (OLT) is scheduled for the end of an ONU's upstream transmission, after the ONU's payload data transmissions. In this paper, we conduct a detailed investigation of the impact of the report message scheduling (RMS), either at the beginning (i.e., before the pay load data) or the end of an ONU upstream transmission on PON performance. We analytically characterize the reduction in channel idle time with reporting at the beginning of an upstream transmission compared to reporting at the end. Our extensive simulation experiments consider both the Ethernet Passive Optical Networking (EPON) standard and the Gigabit PON (GPON) standard. We find that for DBAs with offline sizing and scheduling of ONU upstream transmission grants at the end of a polling cycle, which processes requests from all ONUs, reporting at the beginning gives substantial reductions of mean packet delay at high loads. For high-performing DBAs with online grant sizing and scheduling, which immediately processes individual ONU requests, or interleaving of ONUs groups, both reporting at the beginning or end give essentially the same average packet delays.

Toward efficient estimation of available bandwidth for IEEE 802.11-based wireless networks

Accurately measuring the available bandwidth information is critical for providing QoS (Quality of Service) assurance, especially for the bandwidth-limited 802.11-based wireless networks. However, the shared nature of wireless medium and IEEE 802.11 MAC pose great challenges for estimating the bandwidth accurately. This paper tends to tackle this issue. In particular, based on our formal definition of available bandwidth in IEEE 802.11-based wireless networks, a novel Passive Available Bandwidth Estimation (PABE) approach is proposed. In PABE, the effective link capacity is analyzed by considering the random factors in transmission like backoff and the retransmission of frame. To estimate the available channel idle time ratio (CITR), a new, lower threshold (named No Collision Sensing Range threshold, NCSR-threshold) is introduced, and the underestimation problem raised by the new threshold is compensated by the non-affect case analysis. Our approach incurs very low cost to the network without any explicit message overhead. Through extensive simulation, our data validate that our approach consistently achieves much better performance than other existing algorithms in terms of estimation accuracy.

CSIT: channel state and idle time predictor using a neural network for cognitive LTE-Advanced network

Abstract Cognitive radio (CR) is a novel methodology that facilitates unlicensed users to share a licensed spectrum without interfering with licensed users. This intriguing approach is exploited in the Long Term Evolution-Advanced (LTE-A) network for performance improvement. Although LTE-A is the foremost mobile communication standard, future underutilization of the spectrum needs to be addressed. Therefore, dynamic spectrum access is explored in this study. The performance of CR in LTE-A can significantly be enhanced by employing predictive modeling. The neural network-based channel state and idle time (CSIT) predictor is proposed in this article as a learning scheme for CR in LTE-A. This predictive-based learning is helpful in two ways: sensing only those channels that are predicted to be idle and selecting the channels for CR transmission that have the largest predicted idle time. The performance gains by exploiting CSIT prediction in CR LTE-A network are evaluated in terms of spectrum utilization, sensing energy, channel switching rate, packet loss ratio, and average instantaneous throughput. The results illustrate that significant performance is achieved by employing CSIT prediction in LTE-A network.

Learning-based p-persistent CSMA for secondary users of cognitive radio networks

In this paper, we consider learning-based p-persistent carrier sense multiple access (CSMA) for cognitive radio secondary users (SUs) when the primary user (PU) operates with the conventional CSMA/CA scheme. The learning algorithms are applied to tune the value of p to balance the channel idle time and collision costs due to both the PU and the SUs sharing the same wireless channel. Our proposal comprises two steps: first, the Q-learning scheme is used to adjust the transmission probability p when the PU has imperfect sensing. Then, for the multiple SUs’ case, a mixed strategy access policy is executed to solve the fairness problem in media access control (MAC). Our proposed scheme can maximise the SUs’ throughput and ensure protection of the performance of the PU, as well.

A Markovian approach for best-fit channel selection in cognitive radio networks

An efficient channel selection scheme in multi-user cognitive radio networks (CRN) is supposed to address two often conflicting objectives: enhancing the network-wide performance while satisfying the individual quality of service demands of cognitive radios (CRs). In this sense, best-fit channel selection (BFC) inspired from well-known classical bin-packing algorithms achieves better performance compared to the longest-idle time channel selection (LITC). BFC facilitates each CR, with the capability of primary channel idle time estimation, select the channel that is expected to be idle for sufficiently long duration for its traffic request. Unlike BFC, LITC favors the selection of the channel with the longest idle time although the channel is not needed and will not be used for such long duration by this CR. As a generalization of these two approaches, we introduce the p – selfish scheme in which a CR selects the longest channel with probability p. Hence, we also refer to p as degree of selfishness. In [1], we evaluate the performance of BFC and show that it improves performance of the CRN in terms of spectrum opportunity utilization and CR throughput, compared to the LITC. In this work, we present an analytic model for BFC using continuous-time Markov chains (CTMC). The performance improvement achieved by BFC is due the reduced spectrum fragmentation that is achieved by best-fit allocation. BFC can be considered as an implicit solution to spectrum fragmentation in time dimension. We study the CR performance in terms of spectrum opportunity utilization and probability of success under various degree of selfishness through the presented model and compare our results with the simulation results.