Congestion control in high-speed communication networks using the Smith principle

High-speed communication networks are characterized by large bandwidth-delay products. This may have an adverse impact on the stability of closed-loop congestion control algorithms. In this paper, classical control theory and Smith’s principle are proposed as key tools for designing an effective and simple congestion control law for high-speed data networks. Mathematical analysis shows that the proposed control law guarantees stability of network queues and full utilization of network links in a general network topology and traffic scenario during both transient and steady-state condition. In particular, no data loss is guaranteed using buffers with any capacity, whereas full utilization of links is ensured using buffers with capacity at least equal to the bandwidth-delay product. The control law is transformed to a discrete-time form and is applied to ATM networks. Moreover a comparison with the ERICA algorithm is carried out. Finally, the control law is transformed to a window form and is applied to Internet. The resulting control law surprisingly reveals that today's Transmission Control Protocol/Internet Protocol implements a Smith predictor for congestion control. This provides a theoretical insight into the congestion control mechanism of TCP/IP along with a method to modify and improve this mechanism in a way that is backward compatible.     

Congestion control in utility fair networks

This paper deals with a congestion control framework for elastic and real-time traffic, where the user’s application is associated with a utility function. We allow users to have concave as well as non-concave utility functions, and aim at allocating bandwidth such that utility values are shared fairly. To achieve this, we transform all utilities into strictly concave second order utilities and interpret the resource allocation problem as the global optimization problem of maximizing aggregate second order utility. We propose a new fairness criterion, utility proportional fairness, which is characterized by the unique solution to this problem. Our fairness criterion incorporates utility max–min fairness as a limiting case. Based on our analysis, we obtain congestion control laws at links and sources that (i) are linearly stable regardless of the network topology, provided that a bound on round-trip-times is known, (ii) provide a utility proportional fair resource allocation in equilibrium. We further investigate the efficiency of utility fair resource allocations. Our measure of efficiency is defined as the worst case ratio of the total utility of a utility proportional fair rate vector and the maximum possible total utility. We present a generic technique, which allows to obtain upper bounds on the efficiency loss. For special cases, such as linear and concave utility functions, and non-concave utility functions with bounded domain, we explicitly calculate such upper bounds. Then, we study utility fair resource allocations with respect to bandwidth fairness. We derive a fairness metric assessing the aggressiveness of utility functions. This allows us to design fair utility functions for various applications. Finally, we simulate the proposed algorithms using the NS2 simulator.     

On the use of packet classes in communication networks to enhancecongestion pricing based on marks

This note explores the use of packet classes to enhance Internet congestion pricing based on marks in the framework of Kelly et al. (1997). Two packet classes are used in order to exploit differences in the multidimensional quality-of-service (QoS) requirements within the population of users. Simple scenarios for a link with a finite buffer with and without burstiness are investigated. It is concluded that the use of packet classes provides a margin for error in provisioning and operating a packet network with congestion pricing     

Congestion control algorithm in large-delay uncertain networks

Based on Smith-fuzzy controller, a new active queue management （AQM） algorithm adaptable to the large-delay uncertain networks is presented. It can compensate the negative impact on the queue stability caused by the large delay, and it also maintains strong robustness under the condition of dynamic network fluid. Its stability is proven through Lyapunov method. Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small, the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and, in particular, the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.     

Congestion control algorithm in large-delay uncertain networks

Based on Smith-fuzzy controller, a new active queue management (AQM) algorithm adaptable to the large-delay uncertain networks is presented. It can compensate the negative impact on the queue stability caused by the large delay, and it also maintains strong robustness under the condition of dynamic network fluid. Its stability is proven through Lyapunov method. Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small, the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and, in particular, the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.     

SLA-based QoS pricing in DiffServ networks

The availability of high-speed transmission media and networking equipment in contemporary networks, as well as the evolution of quality-demanding applications has focused research interest on the provision of advanced qualitative services in addition to the traditional best-effort model of the Internet. A number of alternatives for service differentiation and QoS provisioning have been proposed and standardized, but in the case of backbone, transport networks the DiffServ architecture has prevailed, due to its scalability and deployment feasibility. The provisioning of services according to the DiffServ framework has in turn raised the requirements for interdependent, controlled resource allocation and service pricing, with particular needs for pricing mechanisms that preserve the potential and flexibility of DiffServ. At the same time, such mechanisms should reflect resource usage, allocate resources efficiently, reimburse costs or maximize service provision profits and lead customers to requesting services that will maximize their revenue. In this work, after reviewing related research, the principles that a pricing scheme for DiffServ-based services should follow are presented, stressing the differences form traditional Internet pricing. Based on these principles, an analytical approach to pricing a particular class of DiffServ-based services and a methodology for applying this approach in a real network are proposed and evaluated.     

Congestion control based dynamic routing in ATM networks

In this paper we describe briefly a dynamic multi-path algorithm that has been considered for connection oriented asynchronous transfer mode (ATM) networks. Our scheme takes advantage of a cell multiplexing capability that has particular advantage in networks supporting variable bit rate (VBR) traffic. The fundamental objective of the scheme is to propose a congestion control based scheme that bridges the gap between routing and congestion control as the network becomes congested. The proposed routing scheme works as a shortest path first algorithm under light traffic conditions. However, as the shortest path becomes congested under unbalanced heavy traffic, the source uses multiple paths when and if available to distribute the calls and reduce cell loss. This mechanism will provide good Quality of Service for clients within the given constraints. We compare the performance of the proposed scheme with other competitive schemes. The throughput and cell loss performance are compared via simulations. These have been carried out concentrating on a five node network, each with varying traffic patterns, with the intention of gaining insight into the strengths and weaknesses of the various schemes.     

Can you social engineer your way into your network?

At larger customer sites, I am frequently asked to see if I can get into a computer facility or asked to gain access to corporate assets. One of the more successful manners in which to do this is via social engineering.     

Can you social engineer your way into your network?

At larger customer sites, I am frequently asked to see if I can get into a computer facility or asked to gain access to corporate assets. One of the more successful manners in which to do this is via social engineering. Social engineering, is, basically, lying your way into a facility. It takes a certain amount of self-confidence and the ability to talk your way out of situations where you might get caught. It also takes a certain amount of “on your feet” thinking so that you do not get into a situation where you are discovered too soon. The idea is to test the facilities in your purview without getting caught too soon, if at all, so that improvements can be made.     

Loss-cognizant pricing in networks with greedy users

We consider link pricing in packet-switched networks with fixed routing and random congestion losses. Network users are assumed to be greedy in the sense that each user increases its traffic rate in proportion to profit per packet it generates. The main goal of the paper is to devise pricing principles that maximize social welfare, which is taken as either the sum of goodputs or the sum of log-goodputs in the network. We adopt a deterministic fluid model whose analysis leads to pricing policies that stabilize packet generation rates at local maxima of social welfare for a rich set of network topologies. We also give decentralized algorithms to compute the price of packet forwarding at each link. Neither computation nor implementation of prices requires per-flow information. Obtained analytical results are verified via packet level simulations.     

Online pricing for bandwidth provisioning in multi-class networks

We consider the problem of pricing for bandwidth provisioning over a single link, where users arrive according to a known stochastic traffic model. The network administrator controls the resource allocation by setting a price at every epoch, and each user’s response to the price is governed by a demand function. We formulate this problem as a partially observable Markov decision process (POMDP), and explore two novel pricing schemes––reactive pricing and spot pricing––and compare their performance to appropriately tuned flat pricing. We use a gradient-ascent approach in all the three pricing schemes. We provide methods for computing unbiased estimates of the gradient in an online (incremental) fashion. Our simulation results show that our novel schemes take advantage of the known underlying traffic model and significantly outperform the model-free pricing scheme of flat pricing.     

Optimal polling in communication networks

Polling is the process in which an issuing node of a communication network (polling station) broadcasts a query to every other node in the network and waits to receive a unique response from each of them. Polling can be thought of as a combination of broadcasting and gathering and finds wide applications in the control of distributed systems. In this paper, we consider the problem of polling in minimum time. We give a general lower bound on the minimum number of time units to accomplish polling in any network and we present optimal polling algorithms for several classes of graphs, including hypercubes and recursively decomposable Cayley graphs     

Real-time communication in multihop networks

Communication in real-time systems has to be predictable, because unpredictable delays in the delivery of messages can adversely affect the execution of tasks dependent on these messages. We develop a scheme for providing predictable interprocess communication in real-time systems with (partially connected) point-to-point interconnection networks, which provide guarantees on the maximum delivery time for messages. This scheme is based on the concept of a real-time channel, a unidirectional connection between source and destination. A real-time channel has parameters that describe the performance requirements of the source-destination communication, e.g., from a sensor station to a control site. Once such a channel is established, the communications subsystem guarantees that these performance requirements will be met. We concentrate on methods to compute guarantees for the delivery time of messages belonging to real-time channels. We also address problems associated with allocating buffers for these messages and develop a scheme that preserves delivery time guarantees     

Multicast communication in multicomputer networks

Efficient routing of messages is a key to the performance of multicomputers. Multicast communication refers to the delivery of the same message from a source node to an arbitrary number of destination nodes. While multicast communication is highly demanded in many applications, most of the existing multicomputers do not directly support this service; rather it is indirectly supported by multiple one-to-one or broadcast communications, which result in more network traffic and a waste of system resources. The authors study routing evaluation criteria for multicast communication under different switching technologies. Multicast communication in multicomputers is formulated as a graph theoretical problem. Depending on the evaluation criteria and switching technologies, they study three optimal multicast communication problems, which are equivalent to the finding of the following three subgraphs: optimal multicast path, optimal multicast cycle, and minimal Steiner tree, where the interconnection of a multicomputer defines a host graph. They show that all these optimization problems are NP-complete for the popular 2D-mesh and hypercube host graphs. Heuristic multicast algorithms for these routing problems are proposed     

Real-time communication in FDDI networks

This paper provides a comprehensive study of the use of FDDI networks to support real-time communication in mission-critical systems. Due to the potentially catastrophic results of failure in such systems, it is important to avoid message loss whenever possible. We develop efficient tests to check whether message loss may occur, either due to missing deadlines or due to buffer overflow. These tests are extremely useful in the design and operation of mission-critical systems using FDDI networks. Two types of tests are developed: message-parameter-based tests, which use detailed system knowledge to determine whether loss may occur, and utilization-based tests, which only require knowledge of the overall system load. In order to examine the system performance over a wide range of network loads, we also examine the probability that a randomly chosen message set will not suffer any loss. The work reported in this paper is compatible with the FDDI and SAFENET standards, and can be applied by engineers building real-time systems using these standards.     

Fault-tolerant communication algorithms in toroidal networks

Fault-tolerant communication algorithms for k-ary n-cubes are introduced. These include: One-to-all broadcasting, all-to-all broadcasting, one-to-all personalized communication, and all-to-all personalized communication. Each of these algorithms can tolerate up to (2n-2) node failures provided that k>(2n-2) and k>3. Extensions of these algorithms with up to 2n-1 node failures are also described. The communication complexities of the proposed algorithms are derived when wormhole or store and forward packet routing is used     

Self-stabilizing group communication in directed networks

This paper presents the first self-stabilizing group membership service, multicast service, and resource allocation service for directed networks. The first group communication algorithm is based on a token circulation over a virtual ring. The second algorithm is based on construction of distributed spanning trees. In addition, a technique is presented that emulates, in a self-stabilizing fashion, any undirected communication network over strongly connected directed networks, is presented. A resource allocation asynchronous algorithm for strongly connected directed networks is presented.Received: 23 July 2003, Published online: 29 June 2004Partially supported by NSF Award CCR-0098305, IBM faculty award, STRIMM consortium, and Israel ministry of defense.