Queueing Delay Performance Research Articles

Connection-Based Aloha: Modeling, Optimization, and Effects of Connection Establishment

According to whether a connection to the receiver is established before data transmission, random access schemes can be divided into two categories: connection-based and connection-free. For cellular networks, its connection-based access mechanism has been heavily criticized for being ill-suited to Machine-to-Machine (M2M) communications. With the existing studies overwhelmingly focusing on the physical-layer transmission and detection design of various connection-free access schemes, less attention has been paid to the fundamental understanding of when connection establishment could be beneficial. The challenge originates from the lack of proper modeling of connection-based random access. In this paper, a scalable model that incorporates each node’s queueing behavior is proposed for connection-based slotted Aloha, based on which both the data throughput and the mean queueing delay of data packets are characterized, optimized, and compared with those for connection-free slotted Aloha. Conditions for beneficial connection establishment in terms of the optimal throughput and queueing delay performance are discussed and applied to cellular networks with the newly introduced Random Access-based Small Data Transmission (RA-SDT) schemes. The analysis offers important insights for the optimal access design of M2M communications.

AI-Based Cloud-Edge-Device Collaboration in 6G Space-Air-Ground Integrated Power IoT

Space-air-ground integrated communication networks and artificial intelligence (AI) play critical roles in future 6G wireless communication. The Power Internet of Things (PIoT) assisted by the space-air-ground integrated communication network, that is, space-air-ground integrated PIoT (SAG-PIoT), has emerged as a promising solution to provide seamless communication and computing services for PIoT devices with stringent QoS requirements. Cloud-edge-device collaboration is leveraged to enable intelligent resource management in SAG-PIoT. This article proposes an AI-based cloud-edge-device collaboration framework for SAG-PIoT to cope with multi-dimensional resource heterogeneity and network dynamics. Specifically, the SAG-PIoT application scenarios and research challenges are first introduced. Then we develop a hybrid and hierarchical cloud-edge-device collaboration architecture to adapt with different scenarios and domains, followed by the detailed implementation procedures. Next, a queue-aware deep actor-critic (Q-DAC)-based task offloading algorithm is proposed to facilitate decision making optimization under incomplete information. A case study is provided to validate the energy consumption and end-to-end queuing delay performance of Q-DAC.

Queueing Delay Performance of Schedulers in Centralized Sensing Cognitive Radio Networks

Wireless communication has become cost-effective and it can be established very rapidly in order to bring broadband access to under-served rural as well as urban area users. The underutilized spectrum has enormous, untapped, public capacity to provide high-speed and pervasive broadband connectivity. The wireless Radio Frequency (RF) spectrum is highly congested due to the continuous increase in the demand for high data rate services. Cognitive Radio (CR) allows secondary/unlicensed users to use a part/slice of a licensed spectrum, referred to as a channel, whenever the primary/licensed user is not transmitting in that channel during a period. In order to find the primary–free channels in the RF spectrum, CR performs spectrum sensing before transmitting its signal. When there are multiple secondary users trying to sense, find and access the available free channels it becomes very challenging. Scheduling resolves the problem by the use of queues. The behaviour of queues in terms of Queuing delay performance of Schedulers in Multiuser Cognitive Radio Networks when there is a Centralized Coordinator performs sensing and scheduling, has been studied. Three different scheduling policies are considered, namely Maximum Gain, Maximum Weight and Proportionally Fair scheduling. When the network is heavily loaded, each policy presents varied Queuing Delay Performance. The cases when average Signal-to-Noise Ratio of users is considered to be unequal have been analysed with varying normalized sensing duration. Queuing delay for various arrival rates of users is plotted and the performances have been compared and discussed. From the results, it can be concluded that the Maximum Weight Scheduler performs better than others do.

Delay-aware spectrum sharing solutions for mixed cellular and D2D links

In this paper, we dynamically determine the spectrum share of cellular and overlay device to device communication (D2D) links to improve queuing delay performance. Along changing the portion of resource blocks (RBs) dedicated to each cellular and D2D network, we assign the required power and RBs to each link. We consider a cross-layer optimization problem taking channel state information (CSI) and queue state information (QSI) into account. Two spectrum access mechanisms of overlay D2D mode, known as orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) are investigated. First, the dynamic spectrum sharing and power assignment problem is formulated as a general stochastic problem, then it is transformed into a deterministic one using Lyapunov optimization. As the cellular and D2D links should be scheduled prior to each frame transmission, low-complexity approaches are necessary to deal with the dynamic nature of the optimization problem. Thereby, we obtain closed-form-iterated solutions for OMA and NOMA with low design complexity because they do not need to know the probability functions of the channel state and traffic arrival process. Furthermore, for computational complexity reduction, a linear-complexity heuristic approach is proposed. Numerical results demonstrate that the proposed dynamic spectrum sharing approaches outperform static approaches in terms of average delay and average power. In addition, the performance of dynamic NOMA is superior to the dynamic OMA approach at the expense of higher computational complexity which can be compensated by the heuristic approach with a small power computation increase.

Queue-Aware Cell Activation and User Association for Traffic Offloading via Dual-Connectivity

With the objective of reducing energy cost, we study the stochastic optimization of traffic off-loading via dual-connectivity by joint cell activation and user association. Particularly, explicitly considering the dynamic effects of time-varying and random traffic arrivals, we formulate a stochastic problem that quantifies the tradeoff between energy cost and queuing delay. Employing two-time-scale Lyapunov optimization, the formulated problem is transformed as a user association problem at each time slot and a small-cell activation problem at each frame. However, the user association problem turns out to be a mixed-integer nonlinear programming problem and is difficult to be transformed into a convex problem, and traditional game-theoretic solutions, such as Nash equilibrium, cannot be used to solve it. Then, we introduce a two-sided many-to-one matching game and propose a distributed user association algorithm that converges to a local optimum. On the other hand, the cell activation problem belongs to the class of maximum facility location problems that are generally NP-hard. Additionally, its objective function is not a submodular one. Thus, we present an iterative and heuristic algorithm that finds the best set of active small-cell BSs by repeatedly solving the user association problem with different sets of active small cells in each iteration. Furthermore, an online two-time-scale joint cell activation and user association algorithm are developed. Finally, numerical results show the effectiveness of the matching-based user association algorithm on traffic off-loading improvement, the heuristic cell activation algorithm on trading off between energy cost reduction and network throughput enhancement, and the online joint algorithm on balancing between energy cost reduction and queuing delay performance.

Delay Guaranteed Network Association for Mobile Machines in Heterogeneous Cloud Radio Access Network

In the heterogeneous cloud radio access network (H-CRAN), which consists of multiple access points (APs) providing smaller coverage and a high power node (HPN) providing ubiquitous coverage, the mobile machines can connect to multiple APs and HPN by coordinated multi-point transmission (CoMP) concurrently to achieve ultra-reliable and low-latency communication. However, the current network association (or priorly known as handovers), which only focuses on switching between two base stations, may not be an efficient scheme in H-CRAN. In this paper, we innovate a proactive network association mechanism by taking CoMP into consideration under the H-CRAN architecture. We consider two scenarios under the H-CRAN architecture: with and without the assistance of HPN in the network. By regarding APs/HPN in H-CRAN as resources that allocated to mobile machines, a novel proactive network association concept is proposed, and then generalized from one-to-one to multiple-to-multiple case. With the assistance of Lyapunov optimization theory , effective bandwidth, and capacity theory , we can prove that this proactive network association scheme can guarantee that the queueing delay performance and the delay violation probability can be both smaller than a corresponding upper bound. That is, both low-latency and ultra-reliable communication can be guaranteed. We also conduct experiments by using real trace from taxis movement data to verify the analytical results. Our results suggest the guidelines to design the proactive network association scheme in H-CRAN.

Cross-Layer Performance of Downlink Dynamic Cell Selection With Random Packet Scheduling and Partial CQI Feedback in Wireless Networks With Cell Sleeping

In this paper, we consider a coordinated multipoint dynamic cell selection (DCS) transmission scheme for serving sleeping cell user equipments (UEs). According to this DCS scheme, packets of UEs in a sleeping cell are randomly forwarded to the potential active base stations (BSs) by the packet serving gateway and UEs in the sleeping cell dynamically select their serving BS from these active BSs. We model the system as a fork/join (F/J) queuing system and develop a cross-layer analytical model that considers the time varying nature of the channels, channel scheduling mechanism, partial channel quality information feedback, cell selection mechanism, bursty packet arrivals, and packet scheduling mechanism. The developed analytical model can be used to measure various packet-level performance parameters, such as packet loss probability (PLP) and queuing delay while accounting for out-of-sequence packet delivery. We validate the accuracy of the developed analytical model via simulations, and we compare the performance of the DCS scheme under consideration with the conventional fixed cell selection scheme and with the state-of-the-art DCS scheme. Presented numerical results show that the DCS scheme under consideration significantly improves the PLP performance. Queuing delay performance, on the other hand, depends on the system and operating parameters.

A High-Order Markov-Chain-Based Scheduling Algorithm for Low Delay in CSMA Networks

Recently, several CSMA algorithms based on the Glauber dynamics model have been proposed for wireless link scheduling, as viable solutions to achieve the throughput optimality, yet simple to implement. However, their delay performance still remains unsatisfactory, mainly due to the nature of the underlying Markov chains that imposes a fundamental constraint on how the link state can evolve over time. In this paper, we propose a new approach toward better queueing delay performance, based on our observation that the algorithm needs not be Markovian, as long as it can be implemented in a distributed manner. Our approach hinges upon utilizing past state information observed by local link and then constructing a high-order Markov chain for the evolution of the feasible link schedules. We show that our proposed algorithm, named delayed CSMA, achieves the throughput optimality, and also provides much better delay performance by effectively “decorrelating” the link state process (and thus resolves link starvation). Our simulation results demonstrate that the delay under our algorithm can be reduced by a factor of 20 in some cases, compared to the standard Glauber-dynamics-based CSMA algorithm.

Delay Analysis of Max-Weight Queue Algorithm for Time-Varying Wireless Ad hoc Networks—Control Theoretical Approach

Max weighted queue (MWQ) control policy is a widely used cross-layer control policy that achieves queue stability and a reasonable delay performance. In most of the existing literature, it is assumed that optimal MWQ policy can be obtained instantaneously at every time slot. However, this assumption may be unrealistic in time varying wireless systems, especially when there is no closed-form MWQ solution and iterative algorithms have to be applied to obtain the optimal solution. This paper investigates the convergence behavior and the queue delay performance of the conventional MWQ iterations in which the channel state information (CSI) and queue state information (QSI) are changing in a similar timescale as the algorithm iterations. Our results are established by studying the stochastic stability of an equivalent virtual stochastic dynamic system (VSDS), and an extended Foster-Lyapunov criteria is applied for the stability analysis. We derive a closed form delay bound of the wireless network in terms of the CSI fading rate and the sensitivity of MWQ policy over CSI and QSI. Based on the equivalent VSDS, we propose a novel MWQ iterative algorithm with compensation to improve the tracking performance. We demonstrate that under some mild conditions, the proposed modified MWQ algorithm converges to the optimal MWQ control despite the time-varying CSI and QSI.

A Characterization of Delay Performance of Cognitive Medium Access

We consider a cognitive radio network where multiple secondary users (SUs) contend for spectrum usage, using random access, over available primary user (PU) channels. Our focus is on SUs' queueing delay performance, for which a systematic understanding is lacking. We take a fluid queue approximation approach to study the steady-state delay performance of SUs, for cases with a single PU channel and multiple PU channels. Using stochastic fluid models, we represent the queue dynamics as Poisson driven stochastic differential equations, and characterize the moments of the SUs' queue lengths accordingly. Since in practical systems, an SU would have no knowledge of other users' activities, its contention probability has to be set based on local information. With this observation, we develop adaptive algorithms to find the optimal contention probability that minimizes the mean queue lengths. Moreover, we study the impact of multiple channels and multiple interfaces on SUs' delay performance. As expected, the use of multiple channels and/or multiple interfaces leads to significant delay reduction. Finally, we consider packet generation control to meet the delay requirements for SUs, and develop randomized and queue-length-based control mechanisms accordingly.

Queueing Delay Analysis for Multicast With Random Linear Coding

We analyze the queueing delay performance when random linear coding is performed over packets randomly arriving at a source node for multicast transmission over packet erasure channels. We model random coding of packets as a bulk-service queueing system, where packets are served and depart the queue in groups. In this framework, we analyze two different block-based random linear coding schemes. The first scheme involves coding over a fixed blocksize, which leads to simpler analysis but also to a delay penalty for lightly-loaded systems. The second scheme adapts to the traffic load by allowing for a variable blocksize, thereby removing the delay penalty at low loads. We provide results on the maximum stable arrival rate of packets at the source and on the queueing delay as a function of the arrival rate.

Performance of a Two-Level Call Admission Control Scheme for DS-CDMA Wireless Networks

We propose a two-level call admission control (CAC) scheme for direct sequence code division multiple access (DS-CDMA) wireless networks supporting multimedia traffic and evaluate its performance. The first-level admission control assigns higher priority to real-time calls (also referred to as class 0 calls) in gaining access to the system resources. The second level admits nonreal-time calls (or class 1 calls) based on the resources remaining after meeting the resource needs for real-time calls. However, to ensure some minimum level of performance for nonreal-time calls, the scheme reserves some resources for such calls. The proposed two-level CAC scheme utilizes the delay-tolerant characteristic of non-real-time calls by incorporating a queue to temporarily store those that cannot be assigned resources at the time of initial access. We analyze and evaluate the call blocking, outage probability, throughput, and average queuing delay performance of the proposed two-level CAC scheme using Markov chain theory. The analytic results are validated by simulation results. The numerical results show that the proposed two-level CAC scheme provides better performance than the single-level CAC scheme. Based on these results, it is concluded that the proposed two-level CAC scheme serves as a good solution for supporting multimedia applications in DS-CDMA wireless communication systems.

Delay analysis of all-optical packet-switching ring and bus communications networks

We study the delay performance of all-optical packet communication networks configured as ring and bus topologies employing crossconnect switches (or wavelength routers). Under a cross-connect network implementation, a packet experiences no (or minimal) internal queueing delays. Thus, the network can be implemented by high speed all-optical components. We further assume a packet-switched network operation, such as that using a slotted ring or bus access methods. We also derive the delay performance for networks under a store-and-forward network operation. We show these implementations to yield very close average end-to-end packet queueing delay performance. We note that a cross-connect network operation can yield a somewhat higher queueing delay variance levels. However, the mean end-to-end queueing delay for all traffic flows are the same for a cross-connect network operation (under equal nodal traffic loading), while that in a store-and-forward network increases as the path length increases. Similar delay performance results are obtained for bus networks.

Multiaccess Model for Packet Switching with a Satellite Having Processing Capability: Delay Analysis

The multiaccess model for satellite packet switching proposed by the authors [1] employs a frame format, with scheduling assignments broadcast from the satellite. The total delay recurred by a data packet in traversing the satellite channel consists of queueing delay, scheduling delay, transmission delay and propagation delay. In this paper we analyze the queueing and scheduling delays and compare the analytical and simulation results. For the queuemg delay analysis we model the multiaccess scheme using an M/D/N queue, where N is the number of slots per frame. For the scheduling delay analysis we emply a round-robin scheduling assignment algorithm. We treat the cases with and without random transmission; our results indicate that random transmission improves the queueing delay performance.