Deterministic Delay Research Articles

Call Admission Control on Single Node Networks under Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) Scheduler

Multimedia applications such as music or video streaming, video teleconferencing and IP telephony are flourishing in packet-switched networks. Applications that generate such real-time data can have very diverse quality-of-service (QoS) requirements. In order to guarantee diverse QoS requirements, the combined use of a packet scheduling algorithm based on Generalized Processor Sharing (GPS) and leaky bucket traffic regulator is the most successful QoS mechanism. GPS can provide a minimum guaranteed service rate for each session and tight delay bounds for leaky bucket constrained sessions. However, the delay bounds for leaky bucket constrained sessions under GPS are unnecessarily large because each session is served according to its associated constant weight until the session buffer is empty. In order to solve this problem, a scheduling policy called Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) was proposed in [17]. ORC-GPS is a rate-based scheduling like GPS, and controls the service rate in order to lower the delay bounds for leaky bucket constrained sessions. In this paper, we propose a call admission control (CAC) algorithm for ORC-GPS, for leaky-bucket constrained sessions with deterministic delay requirements. This CAC algorithm for ORC-GPS determines the optimal values of parameters of ORC-GPS from the deterministic delay requirements of the sessions. In numerical experiments, we compare the CAC algorithm for ORC-GPS with one for GPS in terms of schedulable region and computational complexity.

Preemptive emergency medium access for wireless sensor networks: performance under realistic network conditions

The proliferation of Wireless Sensor Network (WSN) deployment in threat monitoring applications requires support for emergency–class services with tight Quality–of–Service (QoS) bounds. The CP–EDCA protocol was designed to achieve deterministic delay bounds for emergency–class traffic during distributed wireless network operation. The CP–EDCA scheme could be an ideal choice for prioritised channel access in WSNs, if the performance is demonstrated to be effective under WSN conditions. Here, we evaluate the effectiveness of CP–EDCA protocol under erroneous channel conditions and multi–hop data flow scenarios, which are distinctive features of WSNs. Mathematical and simulation analysis depicts that under typical WSN conditions, distributed preemptions accomplish deterministic delay bounds for emergency traffic even with heavy network loads. Under severe packet losses, CP–EDCA depicted perceivable improvements, relative to IEEE 802.11e standards. Analysis in multi–hop scenarios validates that the channel access preemptions have a significant impact on the end–to–end data flow performance.

Global exponential stability criteria for neural networks with probabilistic delays

The problem of global exponential stability analysis for a class of neural networks (NNs) with probabilistic delays is discussed in this paper. The delay is assumed to follow a given probability density function. This function is discretised into arbitrary number of intervals. In this way, the NN with random time delays is transformed into one with deterministic delays and random parameters. New conditions for the exponential stability of such NNs are obtained by employing new Lyapunov-Krasovskii functionals and novel techniques for achieving delay dependence. It is established that these conditions reduce the conservatism by considering not only the range of the time delays, but also the probability distribution of their variation. Numerical examples are provided to show the advantages of the proposed techniques.

DGRAM: A Delay Guaranteed Routing and MAC Protocol for Wireless Sensor Networks

This paper presents an integrated MAC and routing protocol called Delay Guaranteed Routing and MAC (DGRAM) for delay-sensitive wireless sensor network (WSN) applications. DGRAM is a TDMA-based protocol designed to provide deterministic delay guarantee in an energy-efficient manner. The design is based on slot reuse to reduce latency of a node in accessing the medium, while ensuring that the medium access is contention-free. The transmission and reception slots of nodes are carefully computed so that data is transported from the source toward the sink while the nodes could sleep at the other times to conserve energy. Thus, routes of data packets are integrated into DGRAM, i.e., there is no need for a separate routing protocol in a DGRAM network. We provide a detailed design of time slot assignment and delay analysis of the protocol. We have simulated DGRAM using ns2 simulator and compared the results with those of FlexiTP, which is another TDMA protocol that claims to provide delay guarantee, and with those of a basic TDMA MAC. Simulation results show that the delay experienced by data packets is always less than the analytical delay bound for which the protocol is designed. Also, the TDMA frame size with DGRAM is always lesser compared to that of FlexiTP, which makes the maximum possible delay much lesser than that of FlexiTP. The average delay experienced by packets and the average total energy spent in the network are much lesser in a network using DGRAM than that using FlexiTP or the basic TDMA MAC.

Delay-dependent robust exponential state estimation of Markovian jumping fuzzy Hopfield neural networks with mixed random time-varying delays

This paper investigates delay-dependent robust exponential state estimation of Markovian jumping fuzzy neural networks with mixed random time-varying delay. In this paper, the Takagi–Sugeno (T–S) fuzzy model representation is extended to the robust exponential state estimation of Markovian jumping Hopfield neural networks with mixed random time-varying delays. Moreover probabilistic delay satisfies a certain probability-distribution. By introducing a stochastic variable with a Bernoulli distribution, the neural networks with random time delays is transformed into one with deterministic delays and stochastic parameters. The main purpose is to estimate the neuron states, through available output measurements such that for all admissible time delays, the dynamics of the estimation error is globally exponentially stable in the mean square. Based on the Lyapunov–Krasovskii functional and stochastic analysis approach, several delay-dependent robust state estimators for such T–S fuzzy Markovian jumping Hopfield neural networks can be achieved by solving a linear matrix inequality (LMI), which can be easily facilitated by using some standard numerical packages. The unknown gain matrix is determined by solving a delay-dependent LMI. Finally some numerical examples are provided to demonstrate the effectiveness of the proposed method.

A framework for deterministic delay guarantee in OBS networks

In OBS networks, the delay of control packets in the switch control unit (SCU) of core nodes influences burst loss performance in the optical switching and should be constrained. Furthermore, the end-to-end (E2E) delay requirements of premium services need queueing delay guarantee in network nodes throughout the transmission path. For this purpose, a framework for deterministic delay guarantee is proposed in this article. It incorporates the deterministic delay model in the ingress edge node as well as in the SCUs of core nodes. On this basis, the configuration of the assembler and the offset time is addressed by means of an optimization problem under the delay constraints. Scenario studies are carried out with reference to realistic transport network topologies. Compared to statistical delay models in the literature, the deterministic model has advantages in rendering robust absolute delay guarantee for individual FEC flows, which is especially appreciated in the provisioning of premium services. By performance evaluation in comparison with the statistical models, it is shown that the adopted deterministic delay models lead to practical delay bounds in a magnitude that is close to the delay estimations by stochastic analysis.

Linear quadratic tracking problem for discrete‐time systems with multiple delays in single input channel

AbstractThe linear quadratic tracking problem for discrete‐time systems with multiple delays in single input channel is considered. In this paper, we provide an approach without resorting to system state augmentation. The optimal tracking control is given in terms of the current state, the previous inputs, and the output of an auxiliary backward deterministic delay system which is formulated for the first time in this paper. The solution relies on a Riccati difference equation of the same dimension as the plant (ignoring the delays). The key to our development is the establishment of a duality between the optimal tracking control and the optimal smoothing estimation of an associated stochastic backward system as well as the introduction of the auxiliary backward deterministic delay system. An analysis of the computational complexity of the proposed approach and its comparison with that of the augmentation method, which is to incorporate the delayed inputs into the augmented state, are provided. An example is given to demonstrate the effectiveness of the results. Copyright © 2009 John Wiley & Sons, Ltd.

DFMAC: DTN-Friendly Medium Access Control for Wireless Local Area Networks Supporting Voice/Data Services

In this paper, we consider a wireless communication network for both local nodes residing in densely populated hot spots and nomadic nodes roaming in a large area. Wireless local area networks (WLANs) are deployed in the hot spots, while a delay/ disruption tolerant network (DTN) provides services to nomadic nodes in the large area with low node density. We investigate the radio resource allocation for a DTN/WLAN integrated network, and propose a DTN-friendly medium access control (DFMAC) scheme for the hot spots supporting voice/data services. Analytical models are established to characterize the interactions between a DTN and WLANs under the proposed DFMAC. Numerical and simulation results demonstrate that our proposed MAC scheme can provide a deterministic delay guarantee for the voice services of local nodes, while achieving an efficient performance tradeoff for the data services between nomadic nodes and local nodes.

2-tier hierarchical frame-based queueing for guaranteed delay performance in packet-switched networks

In this letter, we introduce a novel packet scheduling algorithm, so called 2-tier Hierarchical Frame-based Queueing (2tHFQ) that provides a deterministic delay bound without sorting operation complexity. The key idea of 2tHFQ is to divide a given frame into multiple sub-frames with frame indices assigned, and then transmit input packets according to the frame index hierarchy. We analytically predict how delay bound at a node depends on the number of sub-frames. Through NS-2-based network simulations, we also demonstrate a better performance of 2tHFQ under increased traffic loads and a well-controlled packet delay by varying sub-frame numbers.

STOCHASTICALLY SCALABLE FLOW CONTROL

Recent advances in the mathematical analysis of flow control have prompted the creation of the Scalable TCP (STCP) and Exponential RED (E-RED) algorithms. These are designed to be scalable under the popular deterministic delay stability modeling framework. In this article, we analyze stochastic models of STCP and STCP combined with E-RED link behavior. We find that under certain plausible network conditions, these probabilistic models also exhibit scalable behavior. In particular, we derive parameter choice schemes for which the equilibrium coefficients of variation of flow rates are bounded, however large, fast, or complex the network. Our model is shown to exhibit behavior similar to the mean field convergence that has recently been observed in TCP.

Deterministic delay guarantee in OBS edge node for premium services

In optical burst switched (OBS) networks, the queueing delay in ingress edge node is an important performance measure. In this paper, we propose a deterministic delay model and derive the upper bound of the burst queueing delay in an edge node. On this basis, the edge-to-edge delay guarantee framework for premium services is further outlined.

WE-D-211A-02: Modeling and Error Analysis of the Clinical Process in Radiation Therapy

Purpose: To evaluate use of Petri nets industrial system modeling tool for error pathway analysis and error prevention in radiation therapy (RT). Materials and Methods: Petri nets are a common and easily accessible tool for modeling state and event based systems. A Petri net includes “state‐like” objects and “event‐like” objects and the dependencies between the objects. The complete system is represented as a graph consisting of places (states) and transitions (state changes due to occurring events) that are connected by directed arcs. The places on the net can contain any number of mobile elements of the system, referred to as tokens. These tokens are moved from place to place by the “firing” of the transition representing an event in the system. A transition does not have to fire immediately when a token is added to an input place. It may instead have a deterministic or stochastic time delay. Petri nets with randomness in the transitions are called Stochastic Petri Nets. This representation would allow thorough analysis of the system activities. We designed a Petri net representation of our clinical workflow and represented events as transitions and cause for the events as the states. We have collected more than 1000 events through our electronic error reporting software and used Petri Nets to analyze the data. Results: We could identify the fault events and their propagation through the system. We could estimate the corresponding failure probabilities at different stages and their impact on the treatment process. In addition, we can investigate the effects of workflow alteration and patient load on the system performance, and identify optimal system design schemes. Conclusions: The proposed Petri Net approach can achieve early failure detection as well as facilitate event quantification. This can be used for the improvement of patient care and processes in RT.

A data collection protocol for real-time sensor applications

The nature of many sensor applications as well as continuously changing sensor data often imposes real-time requirements on wireless sensor network protocols. Due to numerous design constraints, such as limited bandwidth, memory and energy of sensor platforms, and packet collisions that can potentially lead to an unbounded number of retransmissions, timeliness techniques designed for real-time systems and real-time databases cannot be applied directly to wireless sensor networks. Our objective is to design a protocol for sensor applications that require periodic collection of raw data reports from the entire network in a timely manner. We formulate the problem as a graph coloring problem. We then present TIGRA (Timely Sensor Data Collection using Distributed Graph Coloring) — a distributed heuristic for graph coloring that takes into account application semantics and special characteristics of sensor networks. TIGRA ensures that no interference occurs and spatial channel reuse is maximized by assigning a specific time slot for each node. Although the end-to-end delay incurred by sensor data collection largely depends on a specific topology, platform, and application, TIGRA provides a transmission schedule that guarantees a deterministic delay on sensor data collection.

Time-Driven Access and Forwarding for Industrial Wireless Multihop Networks

The deployment of wireless technologies in industrial networks is very promising mainly due to their inherent flexibility. However, current wireless solutions lack the capability to provide the deterministic, low delay service required by many industrial applications. Moreover, the high level of interference generated by industrial equipment limits the coverage that ensures acceptable performance. Multihop solutions, when combining frame forwarding with higher node density, have the potential to provide the needed coverage while keeping radio communication range short. However, in multihop solutions, the medium access time at each of the nodes traversed additively contributes to the end-to-end delay and the forwarding delay (i.e., the time required for packets to be processed, switched, and queued) at each node is to be added as well. This paper describes time-driven access and forwarding, a solution for guaranteeing deterministic delay, at both the access and forwarding level, in wireless multihop networks, analyzes its properties, and assesses its performance in industrial scenarios.

Consensus reaching in multi-agent packet-switched networks with non-linear coupling

An important task for multi-agent systems (MAS) is to reach a consensus, e.g. to align their velocity vectors. Recent results propose appropriate consensus protocols to achieve such tasks, but most of them do not consider the effect of communication constraints such as the presence of time-delays in the exchange of information between the agents. In this article, we provide conditions for a non-linear, locally passive MAS of arbitrary size to reach a consensus, when the agents communicate over a packet-switched network that is characterised by a given topology. Both the cases of constant and switching topologies are considered. The nature of the communication channel imposes constraints that are modelled using stochastic delays of arbitrary distribution. We first embed this model in another, distributed but deterministic delay model and provide conditions for the error introduced by this simplification. In our main result, we provide conditions for the locally passive MAS with distributed delays to reach a consensus. In the case of a fixed topology, the underlying directed graph has to contain a spanning tree. In the case of a switching topology, only the union graph of all graphs that persist over time is required to contain a spanning tree. These conditions are independent of the distribution and the size of the packet delays. To show attractivity of the consensus set, we use an invariance principle for systems described by functional differential equations based on an appropriate Lyapunov–Razumikhin function. This methodological approach is the main contribution of this work and can also be applied to other consensus problems with delays. We illustrate our results by numerical simulations showing synchronisation of non-linear Kuramoto oscillators over a digital network.

A framework for providing hard delay guarantees and user fairness in Grid computing

We present and theoretically and experimentally analyze a Quality of Service (QoS) framework for Grids that provides (i) deterministic delay bounds to Guaranteed Service (GS) users and (ii) fair sharing of resources to Best Effort (BE) users. The framework adopts concepts from Data Networks and applies them in the Grid environment. We initially describe the proposed framework assuming that task computational workloads are known (or can be estimated), and then provide extensions for the more realistic case where we have no a-priori knowledge of the task workloads. Task migration across multiple resources is also examined in this context. We also look at a specific implementation of the proposed QoS scheme, where we distinguish computational resources, based on the type of users (GS or BE) they serve and the priority they give to each type. We validate experimentally the proposed QoS framework for Grids, verifying that it satisfies the delay guarantees promised to GS users and provides fairness among BE users, while simultaneously improving performance in terms of deadlines missed and resource utilization. In our simulations, data from a real Grid Network are used.

New Stability Criteria for Neural Networks with Distributed and Probabilistic Delays

This paper is concerned with the stability analysis of neural networks with distributed and probabilistic delays. The probabilistic delay satisfies a certain probability distribution. By introducing a stochastic variable with a Bernoulli distribution, the neural network with random time delays is transformed into one with deterministic delays and stochastic parameters. New conditions for the exponential stability of such neural networks are obtained by employing new Lyapunov---Krasovskii functionals and novel techniques for achieving delay dependence. The proposed conditions reduce the conservatism by considering not only the range of the time delays, but also the probability distribution of their variation. A numerical example is provided to show the advantages of the proposed techniques.

Performance Evaluation of Distributed Systems Based on a Discrete Real- and Stochastic-Time Process Algebra

We present a process-algebraic framework for performance evaluation of discrete-time discrete-event systems. The modeling of the system builds on a process algebra with conditionallydistributed discrete-time delays and generally-distributed stochastic delays. In the general case, the performance analysis is done with the toolset of the modeling language χ by means of discrete-event simulation. The process-algebraic setting allows for expansion laws for the parallel composition and the maximal progress operator, so one can directly manipulate the process terms and transform the specification in a required form. This approach is illustrated by specifying and solving the recursive specification of the G/G/1/∞ queue, as well as by specifying a variant of the concurrent alternating bit protocol with generally-distributed unreliable channels. In a specific situation when all delays are assumed deterministic, we turn to performance analysis of probabilistic timed systems. This work employs discrete-time probabilistic reward graphs, which comprise deterministic delays and immediate probabilistic choices. Here, we extend previous investigations on the topic, which only touched long-run analysis, to tackle transient analysis as well. The theoretical results obtained allow us to extend the χ-toolset. For illustrative purposes, we analyze the concurrent alternating bit protocol in the extended environment of the χ-toolset using discrete-event simulation for generallydistributed channels, the developed analytical method for deterministic channels, and Markovian analysis for exponentially-distributed delays.

A Scheduling Algorithm with Dynamic Priority Assignment for WCDMA Systems

In third generation WCDMA systems, shared channels allow many users to jointly utilize a single orthogonal variable spreading factor (OVSF) code. In this paper, we propose a scheduling algorithm with dynamic priority assignment (DPA) which is designed for the downlink-shared channel (DSCH) of 3G WCDMA systems and operates within a cross layer framework. The DPA scheduler has low computational complexity and is able to provide QoS differentiation among traffic flows based on their delay sensitivity. Through the cross layer framework, DPA takes into account the variations of the wireless channel, and exploits processing gain to improve transmission quality and enable service provisioning when possible. Additionally, by providing a guaranteed rate per traffic flow at each scheduling period, DPA can offer a deterministic delay bound to each connection when transmissions are reliable. Stochastic delay guarantees under transmission power limitations are also provided when the traffic flows are identical. Simulation results show that DPA outperforms feasible earliest due date (FEDD), a variation of EDD for wireless environments.

Optimal network rate allocation under end-to-end quality-of-service requirements

We address the problem of allocating transmission rates to a set of network sessions with end-to-end bandwidth and delay requirements. We give a unified convex programming formulation that captures both average and probabilistic delay requirements. Moreover, we present a distributed algorithm and establish its convergence to the global optimum of the overall rate allocation problem. In our algorithm, session sources selfishly update their rates as to maximize their individual benefit (utility minus bandwidth cost), the network partitions end-to-end delay requirements into local per-link delays, and the links adjust their prices to coordinate the sources' and network's decisions, respectively. This algorithm relies on a network utility maximization (NUM) approach, and can be viewed as a generalization of TCP and active queue management (AQM) algorithms to handle end-to-end QoS. We extend our results to deterministic delay requirements when nodes employ Packet-level Generalized Processor Sharing (PGPS) schedulers.