Scheduling, Routing, and Flow Control in Stochastic Networks

We consider a noncooperative game framework for combined routing and flow control in a network of parallel links, where the number of users (players) is arbitrarily large. The utility function of each user is related to the power criterion, and is taken as the ratio of some positive power of the total throughput of that user to the average delay seen by the user. The utility function is nonconcave in the flow rates of the user, for which we introduce a scaling to make it well defined as the number of users, N, becomes arbitrarily large. In spite of the lack of concavity, we obtain explicit expressions for the flow rates of the users and their associated routing decisions, which are in O(1/N) Nash equilibrium. This O(1/N) equilibrium solution, which is symmetric across different users and could be multiple in some cases, exhibits a delay-equalizing feature among the links which carry positive flow. The paper also provides the complete optimal solution to the single-user case, and includes several numerical examples to illustrate different features of the solutions in the single- as well as N-user cases, as N becomes arbitrarily large.

The fluid model has proven to be one of the most effective tools for the analysis of stochastic queueing networks, specifically for the analysis of stability. It is known that stability of a fluid model implies positive (Harris) recurrence (stability) of a corresponding stochastic queueing network, and weak stability implies rate stability of a corresponding stochastic network. These results have been established both for cases of specific scheduling policies and for the class of all work conserving policies.However, only partial converse results have been established and in certain cases converse statements do not hold. In this paper we close one of the existing gaps. For the case of networks with two stations we prove that if the fluid model is not weakly stable under the class of all work conserving policies, then any corresponding queueing network is not rate stable under the class of all work conserving policies. We establish the result by building a particular work conserving scheduling policy which makes any corresponding stochastic process transient. An important corollary of our result is that the condition of the form ρ* < 1, which was proven in [7) to be the exact condition for global weak stability of the fluid model, is also the exact global rate stability condition for any corresponding queueing network. Here ρ* is a certain computable parameter of the network involving virtual station and push start conditions.

The fluid model has proven to be one of the most effective tools for the analysis of stochastic queueing networks, specifically for the analysis of stability. It is known that stability of a fluid model implies positive (Harris) recurrence (stability) of a corresponding stochastic queueing network, and weak stability implies rate stability of a corresponding stochastic network. These results have been established both for cases of specific scheduling policies and for the class of all nonidling policies.\n¶\nHowever, only partial converse results have been established and in certain cases converse statements do not hold. In this paper we close one of the existing gaps. For the case of networks with two stations, we prove that if the fluid model is not weakly stable under the class of all nonidling policies, then a corresponding queueing network is not rate stable under the class of all nonidling policies. We establish the result by building a particular nonidling scheduling policy which makes the associated stochastic process transient. An important corollary of our result is that the condition ρ<sup>*</sup>≤1, which was proven in [Oper. Res. 48 (2000) 721–744] to be the exact condition for global weak stability of the fluid model, is also the exact global rate stability condition for an associated queueing network. Here ρ<sup>*</sup> is a certain computable parameter of the network involving virtual station and push start conditions.

Queueing networks are a powerful abstraction for modeling systems involving contention for resources, e.g., manufacturing lines and computer systems. Queueing networks are especially effective in modeling computer communication systems. Most papers concerning queueing models of communication describe analytic solution of queueing models. This paper describes simulation models based on "extended" queueing networks. The primary advantage of using a queueing network representation for simulation of a computer communication system is the high level of description, in comparison with conventional simulation programming languages. For queueing network models to be used effectively for simulation of contention systems, appropriate software is needed. The research queueing package (RESQ) is a general purpose tool for modeling contention for resources and associated system characteristics. RESQ facilitates i) appropriate abstraction of system characteristics through its definitions of extended queueing networks, ii) efficient and convenient definition and revision of models through its integrated interactive and batch model definition interface, and iii) effective experimentation with simulation models through facilities for parameterized sets of experiments, interactive running of simulations and statistical analysis of simulation results. With a tool such as RESQ, an analyst can produce results in days instead of weeks, and so an analyst can answer questions which otherwise would be left unanswered.

Simultaneous optimization of flow-control and scheduling in a single server queue with two job classes: Numerical results and approximation

Efficient implementation of globally-aware network flow control

The objective of this comprehensive review study was to compile a state-of-the-art understanding of the resilience of the transportation system due to natural and man-made disasters. This study identified resilience measurement parameters that can be used to formulate resilience quantification and improvement strategies of a transportation system. Reviewed articles were classified and summarized from two perspectives: (i) modeling based on the mode of transportation; and (ii) modeling based on the mathematical technique used to quantify resilience. One of the unique contributions of this review article is that it compiled the key resilience indices that were analyzed to quantify resilience. This review revealed that the majority of the scholarly articles on the topic of transportation system resilience published since 2006, were focused on the resilience of the roadway-based transportation system, and vulnerability was one of the most explored resilience indices in evaluating transportation system resilience. Several future research directions were identified considering the implications of emerging transportation technologies (e.g., connected and automated vehicle technology). The complex interdependency among critical infrastructure systems such as power, transportation, and communication system, as well as the cybersecurity issues in the advanced intelligent transportation system, will be vital in the resilience analysis of future transportation systems.

Queueing analysis and optimal control of [formula omitted] and [formula omitted] systems

We consider in this study dynamic control policies for slotted Aloha random access systems. New performance bounds are derived when random access is combined with power control for system optimization, and we establish the existence of optimal control approaches for such systems. We analyze throughput and delay when the number of backlogged users is known, where we can explicitly obtain optimal policies and analyze their corresponding performance using Markov Decision Process (MDP) theory with average cost criterion. For the realistic unknown-backlog case, we establish the existence of optimal backlog-minimizing policies for the same range of arrival rates as the ideal known-backlog case by using the theory of MDPs with Borel state space and unbounded costs. We also propose suboptimal control policies with performance close to the optimal without sacrificing stability. These policies perform substantially better than existing Certainty Equivalence controllers.

This paper studies the problem of energy efficiency (EE) maximization via user association, power, and backhaul (BH) flow control in the downlink of millimeter wave BH heterogeneous networks. This problem is mathematically formulated as a mixed-integer non-linear program, which is non-convex. To get a tractable solution, the initial problem is separated into two sub-problems and optimized sequentially. The first is a joint user association and power control sub-problem for the access network (AN) (AN sub-problem). The second is a joint flow and power control sub-problem for the BH network (BH sub-problem). While the BH sub-problem is a convex optimization problem and hence can be efficiently solved, the AN sub-problem assumes the form of a generalized assignment problem, which is known to be NP-hard. To that end, we utilize Lagrangian decomposition to propose two polynomial time solution techniques that obtain a high-quality solution for the AN sub-problem. The first, referred to as Technique A, uses dynamic programming, the subgradient method, and a heuristic. The second, named Technique B, uses the multiplier adjustment method, the sorting algorithm, and a heuristic. Simulation results are used to demonstrate the effectiveness of the proposed energy efficient user association, power, and BH flow control algorithms as compared with benchmark user association schemes that incorporate the BH sub-problem algorithm, in terms of the total AN power, BH power, and overall network (AN plus BH) EE. The computational complexity and practical implementation of the proposed algorithms are discussed.

This paper focuses on flow control in high-speed net-works. Each node in a network handles its local traffic flow only on the basis of the information it is aware of, but it is preferable that the decision-making of each node leads to high performance of the whole network. To this end, we investigate the relationship between the flow control mech-anism of each node and network performance. We consider the situation in which the capacity of a link in the network is changed but individual nodes are not aware of this. Then we investigate the stability and adaptability of the network performance when the capacity of a link is changed, and discuss an appropriate flow control model on the basis of simulation results. 1

Summary form only given. The problem of flow control in ATM networks is a difficult one due to the uncertainties about the flow rates of the data streams coming from various sources of traffic at different nodes of the network. The flow control problem consists of multiplexing the ATM traffic and it is a challenging statistical management strategy where different patterns are directed into the communication channels. During the multiplexing stage, some prescribed performance constraints on the communication parameters should be strictly satisfied. The real motivation for considering an unconventional control technique for flow control in the ATM networks is because with the growing demand for the traffic of the integrated services (including voice and data communications), reliable decisions should be taken in real time. We consider the problem of estimating the statistical parameters of an intelligent control scheme for smoothing the ATM networks based on a neural network architecture. The neural network considered for carrying out the task of flow control runs the statistical estimation as an iterated map. The reason for this architectural design is the need to have a robust estimation scheme, where the convergence to an attractor of the neural dynamics can be enforced to hold in a small number of iterations of the statistical mapping. The neural network is symmetrically connected and this choice reflects a kind of tradeoff between the speed of convergence and the stability of the states during the successive states of the dynamical relaxation. A numerical experiment describing the dynamic performances of the neural controller for the ATM flow control is presented.

Air-space-ground integrated networks are the combine network of the air, space and ground. The ASG-IIN has the problem of level isolated in Multi-level architecture. This article design an Air-space-ground integrated networks layered independent flow control scheme, based on the Air-space-ground framework, which analyze the problems of satellite network flow control, spacecraft flow control and land mobile communications networks flow control. According to the research of complex networks’ situation of establishment in WIT120, secure campus and sturdy power grid, we obtain a high service flow control demand of blend networks. Basing on the token, game theory and neural network, we put forward a series of new method to control the flow in Air-space-ground integrated networks.

International research attention on evacuation issues has increased significantly following the human and natural disasters at the turn of the century, such as 9/11, Hurricane Katrina, Cyclones Idai and Kenneth, the Black Saturday forest fires and tsunamis in Japan. The main problem concerning when a disaster can occur involves studying the risk reduction. Risk, following all the theoretical and experimental studies, is determined by the product of three components: occurrence, vulnerability and exposure. Vulnerability can be improved over time through major infrastructure actions, but absolute security cannot be achieved. When the event will occur with certainty, only exposure remains to reduce the risk to people before the effect hits them. Exposure can be improved, under fixed conditions of occurrence and vulnerability, by improving evacuation. The main problem in terms of evacuating the population from an area is the available transport system, which must be used to its fullest. So, if the system is well managed, the evacuation improves (shorter times), meaning the exposure is reduced, and therefore, the risk is reduced. A key factor in the analysis of transport systems under emergency conditions is the behavior of the user, and therefore, the study of demand. This work identifies the main research lines that are useful for studying demand under exposure-related risk conditions. The classification of demand models that simulate evacuation conditions in relation to the effect on the transportation system is summarized. The contribution proposes a model for updating choice in relation to emergency conditions and utility. The contribution of emerging ICTs to actualization is formally introduced into the models. Intelligent technologies make it possible to improve user decisions, reducing exposure and therefore risk. The proposed model moves within the two approaches of the literature: it is an inter-period dynamic model with the probability expressed within the discrete choice theory; furthermore, it is a sequential dynamic model with the probability dependent on the previous choices. The contribution presents an example of application of the model, developing a transition matrix considering the case of choice updating under two extreme conditions.

A shared network is largely oversubscribed by independent users who make random demands on the network. Network flow control is required for the orderly operation of the network under all potential traffic loads. This paper presents a qualitative analysis of the theory of flow control to circuit-switched and packet-switched networks and pro- ,. poses 4 complementary controls and 1 subtended control to constitute "flow control." They are traffic control, routing and delay control, congestion control, network management control, and end-end flow control. This paper introduces the concept of the "R-T function" to illustrate the synthesis of delays and routing freedoms, and to demonstrate the continuum between overload and congestion phenomena. The application of the qualitative theory of flow control to the Canadian Telephone Network is reviewed and the agreement between the theory and the practice is demonstrated. The telephone network is a prime example of a circuit-switched network which has received the benefit of extensive simulation and analytical studies, as well as a long experience to validate the conclusions reached in this paper.