Delay Guarantees Research Articles

Delay sensitive resource allocation over high speed IEEE802.11 wireless LANs

We present a novel resource allocation framework based on frame aggregation for providing a statistical Quality of Service (QoS) guarantee in high speed IEEE802.11 Wireless Local Area Networks. Considering link quality fluctuations through the concept of effective capacity, we formulate an optimization problem for resource allocation with QoS guarantees, which are expressed in terms of target delay bound and delay violation probability. Our objective is to have the access point schedule down-links at minimum resource usage, i.e., total time allowance, while their QoS is satisfied. For implementation simplicity, we then consider a surrogate optimization problem based on a few accurate queuing model approximations. We propose a novel metric that qualitatively captures the surplus resource provisioning for a particular statistical delay guarantee, and using this metric, we devise a simple-to-implement Proportional–Integral–Derivative (PID) controller achieving the optimal frame aggregation size according to the time allowance. The proposed PID algorithm independently adapts the amount of time allowance for each link, and it is implemented only at the Access Point without requiring any changes to the IEEE802.11 Medium Access Control layer. More importantly, our resource allocation algorithm does not consider any channel state information, as it only makes use of queue level information, such as the average queue length and link utilization. Via NS-3 simulations as well as real test-bed experiments with the implementation of the algorithm over commodity IEEE 802.11 devices, we demonstrate that the proposed scheme outperforms the Earliest Deadline First (EDF) scheduling with maximum aggregation size and pure deadline-based schemes, both in terms of the maximum number of stations and channel efficiency by 10–30%. These results are also verified with analytical results, which we have obtained from a queuing model based approximation of the system. Applying actual video traffic from HD MPEG4 streams in both simulations and real test-bed experiments, we also show that our proposed algorithm improves the quality of video streaming over a wireless LAN, and it outperforms EDF and deadline based schemes in terms of the video metric, Peak Signal to Noise Ratio.

Traffic Aware Congestion Control Priority Based Efficient Adaptive Multipath Routing in Wired Networks with New Queuing Technique

This paper proposes a novel technique for data transmission from source to destination by using adaptive multipath routing with route adaptability. In this method, each packet is assigned with priority during transmission by considering the recent traffic of the system. Here an original queue up system is proposed to reduce delay at the router level, so that load on the router is reduced. Here in this paper a new routing technique called Traffic Aware Congestion Control Priority based Efficient Adaptive Multipath Routing is compared over a number of multipath routing techniques such as Multi Protocol Label Switching (MPLS) and Minimum Delay and Maximum Flow (MDMF), and Bandwidth Guaranteed Delay Guaranteed (BGDG). Here the proposed algorithm is simulated using NS-2 and simulation results are compared with MPLS, MDMF and BGDG routing techniques with various Quality of Service (QoS) parameters. Simulation results clearly show that proposed technique outcomes recovered likened to existing systems.

Workload scheduling toward worst‐case delay and optimal utility for single‐hop Fog‐IoT architecture

Fog computing is a distributed computing model that can utilise the storage, analysis and processing capabilities of fog nodes near edge devices. Although fog computing can support task processing for various Internet of Things (IoT) systems, Fog-IoT architecture faces several new challenges with the rapid development of IoT systems, especially delay-sensitive IoT systems, such as stochastic and dynamic data arrival, optimal utility and deadline of tasks. To address these challenges, workload scheduling toward worst-case delay and optimal utility for single-hop Fog-IoT architecture are studied and the workload dynamic scheduling algorithm (WDSA) is proposed. The proposed WDSA algorithm can maximise the average throughput utility while guarantees the worst-case delay of task processing. In addition, it is online and needs no prior information about future. The algorithm performance is analysed from the perspective of optimality and worst-case delay, demonstrating that the proposed WDSA algorithm can get an approximate optima and worst-case delay guarantees. Finally, simulation results demonstrate that the efficiency and efficacy of this kind of the algorithm can meet the requirement.

Towards Robust Admission Control in Delay-Constrained Routing Problems

Delay-Constrained Routing (DCR) problems require to route a new flow in a computer network subject to worst-case end-to-end delay guarantees. The delay of a packet flow has three components, one of which is the “queueing delay”, that depends on the scheduling algorithm implemented by the routers of the network. When flows are not independent of each other, i.e., admitting a new flow changes the delay of the existing ones, admission control policies are necessary to ensure that existing flows do not become latency-unfeasible. It has been recently shown that admission control runs contrary to the usual objective function employed in these models, i.e., minimization of the reserved rates, significantly worsening network performance. In this paper we investigate the phenomenon and propose a heuristic way to overcome the problem.

Design and implementation of an adaptive feedback queue algorithm over OpenFlow networks

The concurrent presence of different types of traffic in multimedia applications might aggravate a burden on the underlying data network, which is bound to affect the transmission quality of the specified traffic. Recently, several proposals for fulfilling the quality of service (QoS) guarantees have been presented. However, they can only support coarse-grained QoS with no guarantee of throughput, jitter, delay or loss rate for different applications. To address these more challenging problems, an adaptive scheduling algorithm for Parallel data Processing with Multiple Feedback (PPMF) queues based on software defined networks (SDN) is proposed in this paper, which can guarantee the quality of service of high priority traffic in multimedia applications. PPMF combines the queue bandwidth feedback mechanism to realise the automatic adjustment of the queue bandwidth according to the priority of the packet and network conditions, which can effectively solve the problem of network congestion that has been experienced by some queues for a long time. Experimental results show PPMF significantly outperforms other existing scheduling approaches in achieving 35–80% improvement on average time delay by adjusting the bandwidth adaptively, thus ensuring the transmission quality of the specified traffic and avoiding effectively network congestion.

Distributed Real-Time Energy Management in Data Center Microgrids

Data center operators are typically faced with three significant problems when running their data centers, i.e., rising electricity bills, growing carbon footprints and unexpected power outages. To mitigate these issues, running data centers in microgrids is a good choice since microgrids can enhance the energy efficiency, sustainability and reliability of electrical services. Thus, in this paper, we investigate the problem of energy management for multiple data center microgrids. Specifically, we intend to minimize the long-term operational cost of data center microgrids by taking into account the uncertainties in electricity prices, renewable outputs and data center workloads. We first formulate a stochastic programming problem with the considerations of many factors, e.g., providing heterogeneous service delay guarantees for batch workloads, interactive workload allocation, batch workload shedding, electricity buying/selling, battery charging/discharging efficiency, and the ramping constraints of backup generators. Then, we design a realtime and distributed algorithm for the formulated problem based on Lyapunov optimization technique and a variant of alternating direction method of multipliers (ADMM). Moreover, the performance guarantees provided by the proposed algorithm are analyzed. Extensive simulation results indicate the effectiveness of the proposed algorithm in operational cost reduction for data center microgrids.

Achieving Hybrid Wired/Wireless Industrial Networks With WDetServ: Reliability-Based Scheduling for Delay Guarantees

Industrial control systems are foreseen to operate over hybrid wired/wireless networks. While the controller will be deployed in the wired network, sensors and actuators will be deployed in a wireless sensor network (WSN). To support QoS for control systems, an end-to-end delay bound and a target reliability must be provided in both wireless and wired domains. However, for industrial WSNs, guaranteeing reliability is a challenging task because of low-power communications and the harsh wireless environment. In this work, we present the first QoS framework for arbitrary hybrid wired/wireless networks, which guarantees that the delay bound and the target reliability of each application are provided. As part of this framework, we propose the first reliability-based scheduler for WSN able to achieve a target reliability in the presence of dynamic interference. Simulations of the proposed scheduler prove its suitability in different interference scenarios and motivate further work.

Fronthaul Network Modeling and Dimensioning Meeting Ultra-Low Latency Requirements for 5G

Enabling the transport of fronthaul traffic in next-generation cellular networks [fifth-generation (5G)] following the cloud radio access network (C-RAN) architecture requires a redesign of the fronthaul network featuring high capacity and ultra-low latency. With the aim of leveraging statistical multiplexing gains, infrastructure reuse, and, ultimately, cost reduction, the research community is focusing on Ethernet-based packet-switch networks. To this end, we propose using the high queuing delay percen-tiles of the G/G/1 queuing model as the key metric in front-haul network dimensioning. Simulations reveal that Kingman's exponential law of congestion provides accurate estimates on such delays for the particular case of aggregating a number of evolved Common Public Radio Interface fronthaul flows, namely functional splits and II D . We conclude that conventional 10 G, 40 G, and 100 G transponders can cope with multiple legacy 10–20 MHz radio channels with worst-case delay guarantees. Conversely, scaling to 40 and 100 MHz channels will require the introduction of 200G, 400G, and even 1T high-speed transponders.

A survey of hybrid MAC protocols for machine-to-machine communications

Machine-to-machine (M2M) communications are envisaged to present several interesting applications in the coming years. However, they have major setbacks hurdling their massive deployment. A major challenge is ensuring the network and wireless medium robustly accommodate the millions of devices which will be part of this communication paradigm while gracefully accommodating their diverse quality of service requirements. In this regard, medium access control schemes play a vital role. Traditional contention-based protocols are constrained in their performance under high loads while scheduling-based schemes may be faced with limited scalability and poor delay guarantees. Similarly, tree-based contention resolution schemes have some finite delay associated with them. Recently, hybrids of the aforementioned schemes have been studied in literature to solve the problems associated with traditional medium access schemes. This paper surveys the state-of-the-art hybrid schemes for M2M presenting a classification of recent protocols. Furthermore, we give a summary of major areas of interest such as problem solved, approach used and trade-offs. Salient differences in the protocols are identified with insights into opportunities for improvement. Our findings reveal general design guidelines and interesting future directions.

Self-adaptive implicit contention window adjustment mechanism for QoS optimization in wireless sensor networks

Synchronous contention-based medium access control (MAC) protocols play a vital role in the delay guarantee essentially required by many recent delay-sensitive applications. Great efforts have been made to improve the end-to-end delay by means of optimizing the medium access performance. However, their effectiveness is still constrained by the contradiction between reducing the collision probability and idle listening duration. Instead of traditional tradeoff strategies, developing a way to further alleviate the contradiction is definitely beneficial for further improving the medium access performance. To this end, a self-adaptive implicit contention window adjustment mechanism for SMAC (Sensor MAC) is proposed based on the investigation of the medium competition behavior impacting the medium access delay and delay jitter, from the perspective of any given contending node. We mathematically derive the expected medium access delay for revealing the strengths and weaknesses of typical dynamic contention window mechanisms. Moreover, it is discovered that their delay-oriented optimizing window only offers fairly limited improvement in the medium access performance since the uniformly random slot-selection mechanism results in high delay jitter and the contradiction between reducing the collision probability and idle listening duration. In order to overcome this drawback, furthermore, an optimization model of the node contention priority distribution is proposed to alleviate the aforementioned contradiction by means of optimizing slot-selection mechanism. Finally, a self-adaptive implicit contention window adjustment (SICA) mechanism is designed integrating delay-oriented optimizing contention window, contention priority optimization model with the estimation method of contenders' number. Through simulations in OMNeT++, the results demonstrate that the proposed SMAC-SICA outperforms its peers in terms of delay guarantee, energy efficiency and throughput.

Resource allocation algorithm with worst case delay guarantees in energy harvesting body area networks

In Body Area Networks, for energy harvesting-powered, managing the renewable energy to provide delay-sensitive services is of significant importance. In this paper, we propose an online algorithm to allocate resources, i.e., energy and channel, to maximize the user utility while guaranteeing the worst-case delay. To this end, we first formulate a user utility optimization problem, characterizing the stochastic nature of energy harvesting and energy consumption. Furthermore, a priori knowledge of any this processes is not required. Using Lyapunov optimization techniques, we decompose the problem into four sub-problems, i.e., battery management, collecting rate control, transmission power allocation and dropping rate control. Low-complexity online resource allocation algorithm is proposed to address these problems for user utility maximization, while we further analyze the performance of the online algorithm, in terms of the upper bounds of queues, required battery capacity, and the optimality of the proposed algorithm. Simulation results verify our analysis and the efficacy of the proposed algorithm.

Analysis of effective capacity for visible light communication systems with mobility support

Visible light communications (VLCs) are competitive and attractive candidates for next generation indoor communication networks which are required to support mobility and guarantee delay QoS (Quality of Service) for users. User movement in VLC systems changes the propagation path, including the distance, the angle of incidence and irradiance, all of which have a significant impact on channel gain and link capacity. In this paper, we present a user mobility model for indoor VLC systems with the help of discrete time Markov chain theory. Considering a service process with temporal correlation caused by user mobility, we derive the effective capacity (EC) for VLC systems which characterizes the capacity performance subject to the user’s statistical delay QoS. Moreover, the effect of the user’s mobility on effective capacity is revealed.

Quality-Driven Resource Allocation for Wireless Video Transmissions Under Energy Efficiency and Delay Constraints

In this paper, wireless video transmissions are studied under total bandwidth and energy efficiency (EE) constraints. In order to provide the desired performance levels to the end-users in real-time video transmissions, quality of service requirements such as statistical delay constraints are also considered. Effective capacity is used as the throughput metric in the presence of such statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. A multiuser setup where different users have different delay guarantees is addressed. Following characterizations from the rate-distortion theory, a logarithmic model of the quality-rate relation is used for predicting the quality of the reconstructed video in terms of the peak signal-to-noise ratio at the receiver side. The optimal bandwidth allocation and the optimal power allocation/power control policies that maximize the sum video quality subject to total bandwidth and minimum EE constraints are derived. Five different resource allocation strategies are investigated, and simulation results show that the joint optimization of the bandwidth allocation and power control provides the best performance. The tradeoff between EE and video quality is also demonstrated since higher EE results in lower quality of received video sequence.

Unicast QoS Routing Algorithms for SDN: A Comprehensive Survey and Performance Evaluation

A variety of communication networks, such as industrial communication systems, have to provide strict delay guarantees to the carried flows. Fast and close to optimal quality of service (QoS) routing algorithms, e.g., delay-constrained leastcost (DCLC) routing algorithms, are required for routing flows in such networks with strict delay requirements. The emerging software-defined networking (SDN) paradigm centralizes the network control in SDN controllers that can centrally execute QoS routing algorithms. A wide range of QoS routing algorithms have been proposed in the literature and examined in individual studies. However, a comprehensive evaluation framework and quantitative comparison of QoS routing algorithms that can serve as a basis for selecting and further advancing QoS routing in SDN networks is missing in the literature. This makes it difficult to select the most appropriate QoS routing algorithm for a particular use case, e.g., for SDN controlled industrial communications. We close this gap in the literature by conducting a comprehensive up-to-date survey of centralized QoS routing algorithms. We introduce a novel four-dimensional (4D) evaluation framework for QoS routing algorithms, whereby the 4D correspond to the type of topology, two forms of scalability of a topology, and the tightness of the delay constraint. We implemented 26 selected DCLC algorithms and compared their runtime and cost inefficiency within the 4D evaluation framework. While the main conclusion of this evaluation is that the best algorithm depends on the specific sub-space of the 4D space that is targeted, we identify two algorithms, namely Lagrange relaxation-based aggregated cost (LARAC) and search space reduction delay-cost-constrained routing (SSR+DCCR), that perform very well in most of the 4D evaluation space.

Timely Wireless Flows With General Traffic Patterns: Capacity Region and Scheduling Algorithms

Most existing wireless networking solutions are best-effort and do not provide any delay guarantee required by important applications, such as mobile multimedia conferencing and real-time control of cyber-physical systems. Recently, Hou and Kumar provided a novel framework for analyzing and designing delay-guaranteed wireless networking solutions. While inspiring, their idle-time-based analysis applies only to flows with a special traffic pattern called the frame-synchronized setting . The problem remains largely open for general traffic patterns . This paper addresses this challenge by proposing a general framework that characterizes and achieves the complete delay-constrained capacity region with general traffic patterns in single-hop downlink access-point wireless networks. We first show that the timely wireless flow problem is fundamentally an infinite-horizon Markov decision process (MDP). Then, we judiciously combine different simplification methods to prove that the timely capacity region can be characterized by a finite-size convex polygon. This for the first time allows us to characterize the timely capacity region of wireless flows with general traffic patterns. We then design three scheduling policies to optimize network utility and/or support feasible timely throughput vectors for general traffic patterns. The first policy achieves the optimal network utility and supports any feasible timely throughput vector but suffers from the curse of dimensionality. The second and third policies are inspired by our MDP framework and are of much lower complexity. Simulation results show that both achieve near-optimal performance and outperform other existing alternatives.

On the Capacity of Smart Grid Wireless Backhaul With Delay Guarantee and Packet Concatenation

In future smart grids, low channel efficiency due to small data payloads and the delay guarantee of many near-real-time applications would become two important issues. In this paper, we propose to employ a deadline-ordered scheduler with packet concatenation and apply admission control (AC) to resolve these two issues. In order to execute the AC mechanism, the delay bounds in the home area network and the neighborhood area network and the affine arrival curves for modeling the flows injecting into the concentrator are derived using network calculus. The performance of this novel design is illustrated via analytical and simulation results. In addition, the robust header compression protocol is adopted as a benchmark to evaluate the performance with the packet concatenation method. It is shown that the proposed scheduler with packet concatenation significantly improves the capacity of the smart grid wireless backhaul, and our AC mechanism provides a reliable estimate of the capacity.

Deterministic Quality of Service Guarantee for Dynamic Service Chaining in Software Defined Networking

In this paper, we present a systemic approach to provide deterministic delay guarantee for dynamic service chaining in software defined networking (SDN). The delay performance of service chaining in SDN is affected by signaling message exchange in control plane and packet transmissions in data plane, respectively. First, we develop an analytical method to characterize the delay performance of control plane when handling traffic with different priorities according to network calculus (NC) and queuing theory. Second, taking into account the estimated delay in control plane, we propose a novel service traversal mechanism to calculate the optimal traversal path for the service chain. We demonstrate that NC delay analysis can provide deterministic quality of service (QoS)-guaranteed service chaining for any specified delay requirements, whereas theoretical queueing delay analysis can only provide statistical QoS guarantee. In summary, the proposed NC delay analysis can help to understand the network design for a future delay sensitive Internet in which deterministic latency must be guaranteed.

Dynamic scheming the duty cycle in the opportunistic routing sensor network

SummaryIn wireless sensor networks, a lot of applications need the sensed information be transmitted to the sink node within a predefined time threshold. So end‐to‐end delay is an important performance metric in wireless sensor networks. Opportunistic routing protocols have been proposed to reduce the waiting delay. In the duty cycle networks, increasing the duty cycle ratio can also reduce the end‐to‐end delay. However, this method will consume more energy. It is obvious that there exists a trade‐off between delay and energy consumption. So adjusting the duty cycle ratio of each node can investigate this trade‐off. To the best of our knowledge, no existing work takes both of end‐to‐end delay and energy efficiency into consideration in the opportunistic routing networks. In this paper, we want to minimize the whole energy consumption while guaranteeing the expected end‐to‐end delay between the source nodes and the sink node is below the given threshold. To deal with this problem, we propose a dynamic duty cycle scheme which can significantly reduce the energy consumption and guarantee the expected end‐to‐end delay demand in the opportunistic routing network. To be specific, firstly, we formulate a new metric with the wake‐up time slots as the variable to measure the end‐to‐end delay. Secondly, for simplifying the complex problem, we decompose it into a set of single‐hop delay guarantee problems. Feedback controller has been used to solve the problem. We also analyze the influence of the multiple receivers in the same forwarding set. Finally, we conduct extensive simulations to evaluate the performance of the proposed algorithm. The experimental results reveal that our scheme can guarantee the delay requirement, meanwhile, significantly reduce the energy consumption compared with prior schemes.

Constrained max-min fair scheduling of variable-length packet-flows to multiple servers

In this paper, we study a multi-server queuing system wherein each user is constrained to get service only from a specified subset of servers. Fair packet scheduling in such a setting poses novel challenges that we address in this paper. Specifically, we observe that max-min fair allocation of the available resource over different servers (notably bandwidth) in the presence of placement constraints results in different levels of fair service-rates. To achieve the max-min fair service rates, we propose a novel packet scheduler which is inspired by the deficit-round robin (DRR) algorithm. The scheduler allocates tokens to flows in a round-by-round manner, where token allocation to flows at the beginning of each round is weighted max-min fair. So, we have called it multi-server max-min fair DRR (MSMF-DRR). The performance of the MSMF-DRR algorithm in terms of achieving fairness is shown through a worst-case performance analysis. In addition to analytical results, numerical experiments are also carried out to illustrate service isolation and the delay guarantee that are provided by the algorithm. Generally, a scheduler for such a constrained multi-server queuing system can be applicable in many modern data-networking applications, especially in cloud computing wherein virtual machines and/or processes vie for different IT resources distributed over heterogenous servers, while different processes may have preferences over servers owing to their quality-of-service requirements and the heterogeneity of servers.

DSERR: Delay Sensitive Energy Efficient Reliable Routing Algorithm

Routing strategies need to strike a balance between responsiveness and energy efficiency. Achieving this balance poses new challenges that do not coalesce either with infrastructure or ad hoc wireless networks performance requirements. Multiple strategies have emerged as a workable solution to the routing problem. Either of these solutions however cater to but one of the many constraints posed by the networks. To address this issue we propose a delay sensitive energy efficient reliable routing (DSERR) algorithm which achieves application specified soft delays with energy scavenging being the foremost concern. We try to provide soft end-to-end (e2e) delay guarantee that is proportional to the distance between the source and destination. Our algorithm uses the per hop greedy selection for soft real-time guarantees as it is impossible to provide hard guarantees in a dynamic network. DSERR presents a stateless architecture providing hop by hop reliability of data delivery to support desired delivery reliability across the sensor network.