Delay Bound Violation Probability Research Articles

Two-Stage Task Offloading Optimization With Large Deviation Delay Analysis in IoT Networks

In the edge computing Internet of Things network, we minimize the offloading overhead (caused by the bandwidth cost for data transmission and computation resource consumption for task remote processing) while providing the end-to-end (E2E) delay provisioning. Under the scenario, a tandem queue consisting of a transmission queue and a computing process queue is formed by the tasks offloaded to the edge server via wireless link and then processed through the computing resource. Due to the tandem queue, the offloading decision and computing resource allocation are coupled over the tandem queue. To make the problem tractable, we decouple the above two operations and propose a two-stage offloading filtering and computing resource allocation policy. After decouple, we then investigate the delay bound violation probability of the tandem queue by leveraging large deviation analysis. Further, we reveal that under the same E2E delay provisioning, the offloading overhead under the proposed decoupled policy can approach to the non-decoupled optimum by selecting an appropriate value of control parameter. Simulation results verify the theoretical analysis and show the efficiency of the proposed policy.

SLA-Aware Protocol Design for Energy-Efficient OLT Transmitter in TWDM-EPON

Environmental and economic concerns promote research on designing energy-efficient Time and Wavelength Division Multiplexed Ethernet Passive Optical Network (TWDM-EPON). TWDM-EPON allows achieving energy efficiency at the Optical Line Terminal (OLT) along with Optical Network Units (ONUs). All existing protocols for energy efficient TWDM-EPON have primarily been designed for saving energy at the OLT receivers. In this paper, we propose a method for saving energy at the OLT transmitter in TWDM-EPON while satisfying the service level agreements (SLAs) of corresponding downstream traffic. This includes a proposal for a heuristic algorithm that exploits some specific features of downstream scheduling in TWDM-EPON. Through extensive simulations, we demonstrate that the proposed method provides a significant improvement in energy efficiency in comparison with existing DBA protocols (up to ~ 45%). Moreover, we analyse a theoretical lower bound of the probability of delay bound violation (SLA parameter) and through simulations, we have demonstrated that delay bound violation probability of our proposed protocol is close to this lower bound.

Delay Guaranteed Joint User Association and Channel Allocation for Fog Radio Access Networks

In the Fog Radio Access Networks (F-RANs), the local storage and computing capability of Fog Access Points (FAPs) provide new communication resources to address the latency and computing constraints for delay-sensitive applications. To achieve the ultra-low latency, a novel joint user association and channel allocation scheme is proposed in this paper, where the FAPs are clustered from a user-centric perspective. The delay performance is improved regarding both the control signaling procedure and the data transmission procedure. Specifically, the multiple access interference (MAI) between users is analyzed, where the closed-form expression for the effective rate of a typical user with multiple FAP connections and arbitrary interfering users is obtained. With the consideration of MAI, the proposed distributed joint user association and channel allocation algorithm provides a guaranteed delay violation probability. Moreover, the distributed algorithm can be conducted on individual FAPs, whose calculation is simplified by look-up tables. Simulation results show that the proposed algorithm is capable of providing statistical delay performance guarantee including both average delay and delay bound violation probability, which demonstrates its superiority in supporting delay-sensitive applications in F-RANs.

Delay Characterization of Mobile-Edge Computing for 6G Time-Sensitive Services

Time-sensitive services (TSSs) have been widely envisioned for future sixth generation (6G) wireless communication networks. Due to its inherent low-latency advantage, mobile edge computing (MEC) will be an indispensable enabler for TSSs. The random characteristics of the delay experienced by users are key metrics reflecting the quality of service (QoS) of TSSs. Most existing studies on MEC have focused on the average delay. Only a few research efforts have been devoted to other random delay characteristics, such as the delay bound violation probability and the probability distribution of the delay, by decoupling the transmission and computation processes of MEC. However, if these two processes could not be decoupled, the coupling will bring new challenges to analyzing the random delay characteristics. In this paper, an MEC system with a limited computation buffer at the edge server is considered. In this system, the transmission process and computation process form a feedback loop and could not be decoupled. We formulate a discrete-time two-stage tandem queueing system. Then, by using the matrix-geometric method, we obtain the estimation methods for the random delay characteristics, including the probability distribution of the delay, the delay bound violation probability, the average delay and the delay standard deviation. The estimation methods are verified by simulations. The random delay characteristics are analyzed by numerical experiments, which unveil the coupling relationship between the transmission process and computation process for MEC. These results will largely facilitate elaborate allocation of communication and computation resources to improve the QoS of TSSs.

Martingales-Based ALOHA-Type Grant-Free Access Algorithms for Multi-Channel Networks With mMTC/URLLC Terminals Co-Existence

As a simple single-phase transmission strategy, grant-free access is believed to be an effective way to guarantee the stringent quality of service (QoS) requirements for ultra-reliable low-latency communications (URLLCs). However, unless a theory-based fine evaluation on dynamic delay, we cannot hope to overcome the natural defects of random access and so effectively utilize the time-frequency resources. In this paper, we propose a novel multi-channel ALOHA-type (M-ALOHA) grant-free access algorithm for heterogeneous machine type communication (MTC) networks with URLLC-type terminals and delay-tolerant massive MTC (mMTC)-type terminals co-existence. Firstly, we construct a statistical service model characterizing the transmission rate of each terminal with joint consideration of the features of M-ALOHA access scheme, short packet transmissions and frequency-selective fading channel. Then, taking the great advantages of service-martingales theory in random queuing analysis, we present an ingenious delay analysis and obtain the martingales-based formulation of delay-bound violation probability, where the sporadic feature of MTC traffic arrival is carefully addressed. Finally, the M-ALOHA algorithm is formulated as a system throughput maximization problem subject to martingales-based statistical delay-QoS and the total bandwidth of system. The problem is solved by the proposed bi-objective multi-variable-grey wolf optimizer (BOMV-GWO) algorithm. As a result, we obtain the access probability for each terminal and the optimal parameters for the system design, including the number of sub-channels, the bandwidth for each sub-channel and the packets transmission rate. Simulation results demonstrate that the performance of our M-ALOHA algorithm is favorable.

On Effective Capacity and Effective Energy Efficiency in Relay-Assisted Wireless Networks

The tremendous proliferation of smart phones and other smart devices has spurred the explosive growth of delay-sensitive high-rate multimedia services, which significantly increases energy consumption in wireless cellular networks. Therefore, it is an important yet challenging issue to carry out resource allocation for cellular networks to meet the quality of service requirement in terms of high data rate and, at the same time, achieve high energy efficiency. In this paper, two resource allocation approaches are proposed, where user selection and power allocation are jointly considered, to maximize effective capacity (EC) and effective energy efficiency (EEE), respectively, for a relay-assisted downlink of cellular networks. Channel estimation errors are taken into account to make the proposed approaches more practical. Moreover, to solve the EC maximization problem efficiently, we develop an optimal algorithm based on Lagrange method and Karush–Kuhn–Tucker conditions, and derive closed-form optimal solutions for user selection and power allocation at both the base station and relays. For the EEE maximization problem, an iterative algorithm based on the Dinkelbach method is developed to find the optimal solutions. Theoretical analysis and simulation results are presented to demonstrate the performance of the proposed approaches in terms of EC, EEE, and delay bound violation probability.

Martingales-Based Energy-Efficient D-ALOHA Algorithms for MTC Networks With Delay-Insensitive/URLLC Terminals Co-Existence

One of the key features in machine type communications (MTCs), especially for MTCs embracing ultrareliable and low latency communications (URLLCs), is the short packet transmission with finite block-length. Both feature of short packet transmissions and requirement on supporting low latency communications or URLLCs pose challenges to radio access design for MTC networks in fifth generation. In this paper, for the MTC networks with delay-insensitive/URLLC terminals co-existence scenarios, we propose the energy-efficient differentiated ALOHA (D-ALOHA) random access algorithms, which simultaneously achieve energy efficient and satisfy the requirements of URLLC in a distributed mode. First, we abstract a service model of an MTC terminal with joint consideration of the achievable rate for short packet transmissions, the truncated channel inverse scheme, and the D-ALOHA scheme. Based on the formulated service model, then we derive the martingale parameters of service process for each terminal, and analyze the delay-bound violation probability of a terminal via the optimum stopping theory for martingales. The martingales-based delay analysis is verified via simulations. Finally, we formulate our energy-efficient D-ALOHA algorithm as an energy efficiency maximization problem with martingales-based statistical delayquality of service constraints, and the resultant optimization problem is solved by the invasive weed optimization-differential evolution (IWO-DE) algorithm. Furthermore, we propose a suboptimal but low-complexity energy-efficient D-ALOHA scheme, which neglects the distance difference of delay-insensitive terminals, such that the same access probability is imposed on these terminals for reducing the computational complexity of IWO-DE. Simulation results demonstrate that the energy efficiency performance of our D-ALOHA algorithms is favorite, and our D-ALOHA can achieve URLLCs in case of short duration of a slot.

Delay-QoS-Aware Adaptive Modulation and Power Allocation for Dual-Channel Coherent OWC

Statistical-delay quality of service (QoS) provides bounded link-layer delay over wireless fading channels with a certain delay-bound violation probability. We propose statistical-delay-QoS-aware adaptive modulation (AM) and power allocation for a dual-channel coherent optical wireless communication system over the atmospheric turbulence fading channels. For given statisticaldelay constraints and target bit-error-rate requirements, our proposed AM and power allocation maximize the effective spectral efficiency subject to the transmit-power constraints. We develop delay-QoS-aware adaptive transmission schemes by employing independent and joint channel optimizations subject to average transmit-power constraints. We also consider independent, joint, and successive channel optimizations for developing delay- QoS-aware adaptive transmission schemes subject to peak transmit-power constraints. Numerical results demonstrate that our proposed AM and power allocation significantly outperform the conventional adaptive transmission schemes in the strict statistical-delay constraints. Numerical results also depict superiority of the joint channel optimization in the strong turbulence fading and strict statistical-delay constraints.

MAC Protocol for Quality-Aware Real-Time Voice Delivery in Cognitive Radio-Enabled WSNs

We propose a quality-aware media access control (MAC) protocol for real-time voice delivery in cognitive radio- (CR-) enabled wireless sensor networks (WSNs). The temporal structure of the system model is addressed by using periodic timeslots in order to make more efficient use of the spectrum. In our proposed temporal structure, a bandwidth broker in such centralized CR networks (CCRNs) is selected as a central counterpart to synchronize with secondary users (SUs) and assign spectral resources to them. We develop an analytical model for SUs for the Call Admission Control (CAC) of voice traffic using the quality of service (QoS) requirements of delay bound and delay bound violation probability. Ours is an approach that provides reliable data transmission and reduces packet delay and packet delay jitter. In addition to the aforementioned packet-level performance metrics, we calculated a call-level performance metric, that is, the number of acceptable SUs, satisfying QoS requirements.

Delay-Bounded Priority-Driven Resource Allocation for Video Transmission Over Multihop Networks

In this paper we consider the problem of resource allocation for video transmission over mesh networks with delay bound constraints and priority-based packet scheduling. We observe that priority-driven packet scheduling at the intermediate network routers has a direct and significant impact on the queuing behaviors and delay bound violation probabilities of video packets, as well as the overall end-to-end video distortion. Using learning methods, we develop a packet delay bound violation probability model for video transmission over multihop networks with priority-based packet scheduling. With this model, we can successfully predict the probability of packets being dropped due to violation of specified delay bounds. We also observe that the transmission distortion caused by packet drops exhibits a unique exponential behavior with priority-based packet scheduling. With these analysis results, we formulate the resource allocation for multisession video transmission over networks with priority-driven packet scheduling under delay bound constraints as a multiobjective optimization problem. Evolutionary optimization methods based on single- and multiobjective genetic algorithms are proposed to solve the problem and obtain the optimal resource allocation. Extensive experiment results demonstrate the effectiveness of the proposed resource-distortion models and optimization algorithms.

Low complexity user scheduling for multi‐antenna Gaussian broadcast systems with quality of service requirements

In this study, the authors propose a low complexity user scheduling for multi-antenna broadcast systems with a large number of users with diverse delay-quality of service (QoS) assurances. Owing to the exclusive user scheduling constraints, the optimisation is combinatorial. Furthermore, by adopting effective capacity and effective bandwidth to illustrate the behaviours of different traffic characteristics such as different source statistics and queue dynamics, the delay-bound violation probability constraints can be converted into equivalent minimum data rate constraints. To reduce the computational complexity, they use genetic algorithm (GA) to perform scheduling, instead of a brute-force exhaustive search (ES) over all possible user subsets. By comparing the complexity of GA and ES, they show that GA is a rapid, although suboptimal, option of performing user scheduling optimisation. Simulation results show that the proposed algorithm can not only maximise the achievable user sum data rate, but also keep the delay-bound violation probability of each user below a given threshold.

QoS provisioning performance of IntServ, DiffServ and DQS with multiclass self‐similar traffic

ABSTRACTQuality of service (QoS) provisioning, especially delay guarantee, is particularly important to the explosive growth of Internet applications. Traditional QoS schemes include the per‐flow integrated services (IntServ) and per‐class differentiated services (DiffServ) as well as their variants. To address the scalability problem of IntServ and the coarse QoS granularity of DiffServ, we proposed the per‐packet differentiated queueing service. Although the three schemes all aim to provide delay guarantee, the network resource in terms of bandwidth and buffer required by them will vary because of their distinct service disciplines. Indeed, network resources are so precious especially in wireless networks, whereas QoS provisioning is so important that it is necessary to investigate the resource consumption of these schemes to find better QoS solutions for different kinds of networks. Therefore, QoS provisioning performance of the previous schemes should be modelled analytically. To this end, this paper derives the delay bound violation probability for these QoS schemes with the self‐similar and long‐range dependent traffic model because this traffic model can well approximate the Internet traffic, especially delay‐sensitive traffic. The minimum bandwidth and the buffer size suitable for delay guarantee are further derived. Numerical results show that differentiated queueing service consumes the least bandwidth resources and DiffServ can minimise the buffer size whereas IntServ can provide exactly QoS in per‐flow granularity. In this sense, there is a trade‐off between QoS granularity and bandwidth as well as buffer requirements for QoS provisioning. The analytical results are also studied through simulations. Copyright © 2013 John Wiley & Sons, Ltd.

Statistical quality‐of‐service analysis in multiuser diversity system enhanced with queue information

In recent years, the scheduling scheme of exploiting multiuser diversity gain has attracted much attention for the purpose of efficient spectrum utilisation. The authors consider the problem of analysing the quality of service in the scheduler extracting multiuser diversity gain. The authors use not only the channel state information but also the queue information in determining the optimal user to be scheduled. Through queuing analysis, the guaranteed rate, the average delay and the delay-bound violation probability can be calculated.

Effective capacity of multiple antenna channels: correlation and keyhole

In this study, the authors derive the effective capacity limits for multiple antenna channels which quantify the maximum achievable rate with consideration of link-layer delay-bound violation probability. Both correlated multiple-input single-output and multiple-input multiple-output keyhole channels are studied. Based on the closed-form exact expressions for the effective capacity of both channels, the authors look into the asymptotic high and low signal-to-noise ratio regimes, and derive simple expressions to gain more insights. The impact of spatial correlation on effective capacity is also characterised with the aid of a majorisation theory result. It is revealed that antenna correlation reduces the effective capacity of the channels and a stringent quality-of-service requirement causes a severe reduction in the effective capacity but can be alleviated by increasing the number of antennas.

Hierarchical queue‐length‐aware power control for real‐time applications over wireless networks

AbstractWe consider the problem of optimal power control for quality‐of‐service‐assured wireless communication. The quality of service (QoS) measures of our consideration are a triplet of data rate, delay, and delay bound violation probability (DBVP). Our target is to develop power control laws that can provide delay guarantees for real‐time applications over wireless networks. The power control laws that aim at optimizing certain physical‐layer performance measures, usually adapt the transmission power based on the channel gain; we call these “channel‐gain‐based” (CGB) power control (PC). In this paper, we show that CGB‐PC laws achieve poor link‐layer delay performance. To improve the performance, we propose a novel scheme called hierarchical queue‐length‐aware (HQLA) power control. The key idea is to combine the best features of the two PC laws, i.e., a given CGB‐PC law and the clear‐queue (CQ) PC law; here, the CQ‐PC is defined as a PC law that uses a transmission power just enough to empty the queue at the link layer. We analyze our proposed HQLA‐PC scheme by the matrix‐geometric method. The analysis agrees well with the simulation results. More importantly, our results show that the proposed HQLA power control scheme is superior to the corresponding CGB‐PC in both average power consumption and effective capacity. Copyright © 2010 John Wiley & Sons, Ltd.

Power control for delay constrained multi‐channel communications using outdated CSI

AbstractIn this paper, we study the power allocation scheme for a single user, multi‐channel system, e.g., orthogonal frequency‐division multiplexing (OFDM) systems, under time‐variant wireless fading channels. We assume the receiver feeds back perfectly estimated channel state information (CSI) to the transmitter after a processing delay. The objective of the power allocation is to maximize throughput subject to quality‐of‐service (QoS) constraint. The QoS measure of our consideration is a triplet of data rate, delay, and delay bound violation probability. A two‐step sub‐optimal power allocation scheme is proposed to address the impact of outdated CSI. In the first step, the total transmission power that can be used within one block is determined according to the summation of the channel gains of all the channels. In the second step, the total transmission power is allocated among all the channels. The proposed power control scheme is less sensitive to the feedback delay. Compared to the optimal power allocation scheme designed for the perfect CSI scenario, it has lower computational complexity while achieving comparable capacity. Copyright © 2010 John Wiley & Sons, Ltd.

QoS-Aware Base-Station Selections for Distributed MIMO Links in Broadband Wireless Networks

The distributed multiple-input-multiple-output (MIMO) techniques across multiple cooperative base stations (BS) can significantly enhance the capability of the broadband wireless networks in terms of quality-of-service (QoS) provisioning for wireless data transmissions. However, the computational complexity and the interfering range of the distributed MIMO systems also increase rapidly as the number of cooperative BS's increases. In this paper, we propose the QoS-aware BS-selection schemes for the distributed wireless MIMO links, which aim at minimizing the BS usages and reducing the interfering range, while satisfying diverse statistical delay-QoS constraints characterized by the delay-bound violation probability and the effective capacity technique. In particular, based on the channel state information (CSI) and QoS requirements, a subset of BS with variable cardinality for the distributed MIMO transmission is dynamically selected, where the selections are controlled by a central server. For the single-user scenario, we develop two optimization frameworks, respectively, to derive the efficient BS-selection schemes and the corresponding resource allocation algorithms. One framework uses the incremental BS-selection and time-sharing (IBS-TS) strategies, and the other employs the ordered-gain based BS-selection and probabilistic transmissions (OGBS-PT). The IBS-TS framework can yield better performance, while the scheme developed under the OGBS-PT framework is easier to implement. For the multi-user scenario, we propose the optimization framework applying the priority BS-selection, block-diagonalization precoding, and probabilistic transmission (PBS-BD-PT) techniques. We also propose the optimization framework applying the priority BS-selection, time-division-multiple-access, and probabilistic transmission (PBS-TDMA-PT) techniques. We derive the optimal transmission schemes for all the aforementioned frameworks, respectively. Also conducted is a set of simulation evaluations which compare our proposed schemes with several baseline schemes and show the impact of the delay-QoS requirements, transmit power, and traffic loads on the performances of BS selections for distributed MIMO systems.

On Optimal Power Control for Delay-Constrained Communication Over Fading Channels

In this paper, the problem of optimal power control for delay-constrained communication over fading channels is studied. The objective is to find a power control law that optimizes the link layer performance, specifically, minimizes delay bound violation probability (or equivalently, the packet drop probability), subject to constraints on average power, arrival rate and delay bound. The transmission buffer size is assumed to be finite; hence, when the buffer is full, there will be packet drop. The fading channel under study has a continuous state, e.g., Rayleigh fading. Since directly solving the power control problem (which optimizes the link layer performance) is particularly challenging, the problem is decomposed into three subproblems and the three subproblems are solved iteratively; the resulting scheme is called joint queue length aware (JQLA) power control, which produces a local optimal solution to the three subproblems. It is proved that the solution that simultaneously solves the three subproblems is also an optimal solution to the optimal power control problem. Simulation results show that the JQLA scheme achieves superior performance over the time domain water filling and the truncated channel inversion power control.

Delay-Constrained Optimal Link Scheduling in Wireless Sensor Networks

We consider the optimal link scheduling problem in wireless sensor networks. The optimal link scheduler under our consideration is intended to assign time slots to different users to minimize channel usage subject to constraints on data rate, delay bound, and delay bound violation probability; we study the problem under fading channels and a signal-to-interference-plus-noise-ratio (SINR)-based interference model. To the best of our knowledge, this problem has not been studied previously. We use the effective capacity model to formulate the optimal link scheduling as a mixed-integer optimization problem. We first discuss a simple case, namely, the scheduling with a fixed power allocation, and then extend to the case with variable transmit power. Moreover, because the mixed-integer optimization problem is NP-hard, we propose a computationally feasible column-generation-based iterative algorithm to search for a suboptimal solution to the problem. Finally, we design a medium access control (MAC) protocol to implement our optimal link scheduling strategy in practical wireless networks. Simulation results demonstrate that our proposed scheme achieves a larger throughput, a larger admission region, and a higher power efficiency than a benchmark time-division multiple-access (TDMA) system.

Statistical QoS provisionings for wireless unicast/multicast of multi-layer video streams

Due to the time-varying wireless channels, deterministic quality of service (QoS) is usually difficult to guarantee for real-time multi-layer video transmissions in wireless networks. Consequently, statistical QoS guarantees have become an important alternative in supporting real-time video transmissions. In this paper, we propose an efficient framework to model the statistical delay QoS guarantees, in terms of QoS exponent, effective bandwidth/capacity, and delay-bound violation probability, for multi-layer video transmissions over wireless fading channels. In particular, a separate queue is maintained for each video layer, and the same delay bound and corresponding violation probability threshold are set up for all layers. Applying the effective bandwidth/capacity analyses on the incoming video stream, we obtain a set of QoS exponents for all video layers to effectively characterize this delay QoS requirement.We then develop a set of optimal adaptive transmission schemes to minimize the resource consumption while satisfying the diverse QoS requirements under various scenarios, including video unicast/multicast with and/or without loss tolerance. Simulation results are also presented to demonstrate the impact of statistical QoS provisionings on resource allocations of our proposed adaptive transmission schemes.