Resource allocation in communication networks using abstraction and constraint satisfaction

The fundamental issue of quality-of-service (QoS) routing has triggered a lot of research during the last few years. However, the proposed algorithms attempt to route communication demands only on a call by call basis, without taking into account future traffic. There are nonetheless cases where the traffic profile is known. In this paper, we address this related problem to QoS routing, more specifically, the off-line planning of bandwidth allocation to demands known in advance. Shortest-path routing is the traditional technique applied to this problem. However, this can lead to poor network utilization and even congestion. We show how an abstraction technique combined with systematic search algorithms and heuristics derived from artificial intelligence make it possible to solve this problem more efficiently and in much tighter networks, in terms of bandwidth usage. In addition, this abstraction technique also allows to explain during search why some allocation problems are indeed infeasible. Then, the network regions between which bandwidth must be added are then identified.     

Topology based placement of multicast capable nodes for supporting efficient multicast communication in WDM optical networks

Most existing algorithms for the problem of optical signal splitter placement or multicast splitting-capable node placement in a WDM network are based on the performance of attempting a large set of randomly generated multicast sessions in the network. Experiments show that placement of multicast capable nodes based on their importance for routing one set of multicast sessions may not be a right choice for another set of multicast sessions. In this work, we propose placement algorithms that are based on network topology and the relative importance of a node in routing multicast sessions, which is measured by our proposed metrics. Since a network topology is fixed once given, the proposed algorithms are essentially network traffic independent. We evaluate the proposed placement algorithms given static sets of multicast sessions as well as under dynamic traffic conditions, which are routed using our splitter constrained multicast routing algorithm. Our results show that the proposed algorithms perform better, compared to existing algorithms.     

Optimal Routing for Wireless Mesh Networks With Dynamic Traffic Demand

Wireless mesh networks have attracted increasing attention and deployment as a high-performance and low-cost solution to last-mile broadband Internet access. Traffic routing plays a critical role in determining the performance of a wireless mesh network. To investigate the best routing solution, existing work proposes to formulate the mesh network routing problem as an optimization problem. In this problem formulation, traffic demand is usually implicitly assumed as static and known a priori. Contradictorily, recent studies of wireless network traces show that the traffic demand, even being aggregated at access points, is highly dynamic and hard to estimate. Thus, in order to apply the optimization-based routing solution into practice, one must take into account the dynamic and unpredictable nature of wireless traffic demand. This paper presents an integrated framework for wireless mesh network routing under dynamic traffic demand. This framework consists of two important components: traffic estimation and routing optimization. By studying the traces collected at wireless access points, we first present a traffic estimation method which predicts future traffic demand based on its historical data using time-series analysis. This method provides not only the mean value of the future traffic demand estimation but also its statistical distribution. We further investigate the optimal routing strategies for wireless mesh network which take these two forms of traffic demand estimations as inputs. The goal is to balance the traffic load so that minimum congestion will be incurred. This routing objective could be transformed into the throughput optimization problem where the throughput of aggregated flows is maximized subject to fairness constraints that are weighted by the traffic demands. Based on linear programming, we present two routing algorithms which consider the mean value and the statistical distribution of the predicted traffic demands, respectively. The trace-driven simulation study demonstrates that our integrated traffic estimation and routing optimization framework can effectively incorporate the traffic dynamics in mesh network routing.     

Computing Optimal Max-Min Fair Resource Allocation for Elastic Flows

In this paper, we consider the max-min fair resource allocation problem as applied to elastic flows. We are interested in computing the optimal max-min fair rate allocation. The proposed approach is a linear programming based one and allows the computation of optimal routing paths with regard to max-min fairness, in stable and known traffic conditions. We consider non-bounded access rates, but we show how the proposed approach can handle the case of upper-bounded access rates. A proof of optimality and some computational results are also presented     

Network controller design for SONATA-a large-scale all-optical passive network

This paper describes the network architecture and provides a performance analysis of a passive optical network named SONATA, which has been proposed and demonstrated in the context of the European Union ACTS Program. In this nationwide all-optical network, end terminals access a single passive routing node via PONs using a TDMA/WDMA access scheme based on reservations. The centralized network controller runs resource allocation algorithms in order to avoid conflicts among end terminals. We formally define the resource allocation problem at the network controller, and show that, in general, it is NP-hard. We also provide simple heuristic algorithms to solve the problem. The analysis of the algorithms is performed both via analysis and simulation.     

On the performance analysis of the minimum-blocking and bandwidth-reallocation channel-assignment (MBCA/BRCA) methods for quality-of-service routing support in mobile multimedia ad hoc networks

Quality-of-service (QoS) routing is the key to support multimedia services in wireless multihop networks. The goal of QoS routing is to find satisfactory paths that support the end-to-end QoS requirements of the multimedia flows. Previous work has demonstrated a framework for supporting QoS routing in mobile ad hoc networks, where two novel mechanisms for dynamic channel assignment, called the minimum-blocking and bandwidth-reallocation channel-assignment (MBCA/BRCA) algorithms, were proposed. MBCA/BRCA are on-demand channel assignment methods that reactively provide a differentiated service treatment to multimedia traffic flows at the link level using novel techniques for end-to-end path QoS maximization. Efficient QoS routing is then accomplished by giving the routing mechanism access to QoS information, thus coupling the coarse grain (routing) and fine grain (congestion control) resource allocation. In this paper, the specifics and individual mechanisms of the MBCA/BRCA algorithms are presented, whereas their effectiveness and the manner in which they interact in order to contribute to the overall protocol performance is examined and documented. The system performance is studied through simulations experiments under various QoS traffic flows and network scenarios. The protocol's behavior and the changes introduced by variations on some of the mechanisms that make up the protocol is further investigated. As demonstrated, the MBCA/BRCA methods are able to increase system's aggregate traffic by 2.8 Kb/s, on average, comparing to a non-MBCA/BRCA dynamic channel-allocation scheme.     

Simulative analysis of optimal resource allocation and routing inIBCN's

The problem of resource allocation for future integrated broadband communication networks (IBCNs) is addressed. It mainly involves resource allocation at the connection level. The resource allocation problem is decomposed into the following interdependent tasks: given that a network can accommodate the bandwidth demand of a call request, determine a route for the corresponding asynchronous transfer mode (ATM) virtual connection; and allocate bandwidth, i.e. links inside the trunks of the chosen route, to this connection according to predefined limits on bandwidth use by various service calls. Various link allocation schemes combined with routing algorithms are examined. Their performance in terms of service call blocking is evaluated using a software package developed, for that purpose. It is shown that the traditional complete sharing (CS) and complete partitioning (CP) policies are not adequate for IBCNs. Movable boundary (MB) policies are more flexible and present near-optimal performance when access of broadband service to narrowband service resources is allowed and suitable routing algorithms are dynamically applied     

A compressive sensing‐based network tomography approach to estimating origin–destination flow traffic in large‐scale backbone networks

A traffic matrix can exhibit the volume of network traffic from origin nodes to destination nodes. It is a critical input parameter to network management and traffic engineering, and thus it is necessary to obtain accurate traffic matrix estimates. Network tomography method is widely used to reconstruct end‐to‐end network traffic from link loads and routing matrix in a large‐scale Internet protocol backbone networks. However, it is a significant challenge because solving network tomography model is an ill‐posed and under‐constrained inverse problem. Compressive sensing reconstruction algorithms have been well known as efficient and precise approaches to deal with the under‐constrained inference problem. Hence, in this paper, we propose a compressive sensing‐based network traffic reconstruction algorithm. Taking into account the constraints in compressive sensing theory, we propose an approach for constructing a novel network tomography model that obeys the constraints of compressive sensing. In the proposed network tomography model, a framework of measurement matrix according to routing matrix is proposed. To obtain optimal traffic matrix estimates, we propose an iteration algorithm to solve the proposed model. Numerical results demonstrate that our method is able to pursuit the trace of each origin–destination flow faithfully. Copyright © 2014 John Wiley & Sons, Ltd.     

Two Techniques for Fast Computation of Constrained Shortest Paths

Computing constrained shortest paths is fundamental to some important network functions such as QoS routing, MPLS path selection, ATM circuit routing, and traffic engineering. The problem is to find the cheapest path that satisfies certain constraints. In particular, finding the cheapest delay-constrained path is critical for real-time data flows such as voice/video calls. Because it is NP-complete, much research has been designing heuristic algorithms that solve the epsiv-approximation of the problem with an adjustable accuracy. A common approach is to discretize (i.e., scale and round) the link delay or link cost, which transforms the original problem to a simpler one solvable in polynomial time. The efficiency of the algorithms directly relates to the magnitude of the errors introduced during discretization. In this paper, we propose two techniques that reduce the discretization errors, which allows faster algorithms to be designed. Reducing the overhead of computing constrained shortest paths is practically important for the successful design of a high-throughput QoS router, which is limited at both processing power and memory space. Our simulations show that the new algorithms reduce the execution time by an order of magnitude on power-law topologies with 1000 nodes. The reduction in memory space is similar.     

Oblivious routing in wireless mesh networks

As new network applications have arisen rapidly in recent years, it is becoming more difficult to predict the exact traffic pattern of a network. In consequence, a routing scheme based on a single traffic demand matrix often leads to a poor performance. Oblivious routing (Racke in Proceedings of the 43rd annual IEEE symposium on foundations of computer science 43–52, 2002) is a technique for tackling the traffic demand uncertainty problem. A routing scheme derived from this principle intends to achieve a predicable performance for a set of traffic matrixes. Oblivious routing can certainly be an effective tool to handle traffic demand uncertainty in a wireless mesh network (WMN). However, a WMN has an additional tool that a wireline network does not have: dynamic bandwidth allocation. A router in a WMN can dynamically assign bandwidth to its attached links. This capability has never been exploited previously in works on oblivious routing for a spatial time division multiple access (STDMA) based WMN. Another useful insight is that although it is impossible to know the exact traffic matrix, it is relatively easy to estimate the amount of the traffic routed through a link when the routing scheme is given. Based on these two insights, we propose a new oblivious routing framework for STDMA WMNs. Both analytical models and simulation results are presented in this paper to prove that the performance—in terms of throughput, queue lengths, and fairness—of the proposed scheme can achieve significant gains over conventional oblivious routing schemes for STDMA based WMNs.     

Dynamic rate adaptation and integrated rate and error control in cellular WCDMA networks

Optimal dynamic rate allocation among mobile stations for variable rate packet data transmission in a cellular wireless network is an NP-complete problem; therefore, suboptimal solutions to this problem are sought for. In this paper, three novel suboptimal dynamic rate adaptation schemes, namely, peak-interference-based rate allocation, sum-interference-based rate allocation, and mean-sense approximation-based rate allocation, are proposed for uplink packet data transmission in cellular variable spreading factor wide-band code division multiple access (WCDMA) networks. The performances of these schemes are compared to the performance of the optimal dynamic link adaptation for which the rate allocation is found by an exhaustive search. The optimality criterion is the maximization of the average number of radio link level frames transmitted per frame time under constrained signal-to-interference-plus-noise ratio (SINR) at the base station receiver. Two different error control alternatives for variable rate packet transmission environment are presented. We demonstrate that the dynamic rate adaptation problem under constrained SINR can be mapped into the radio link level throughput maximization problem with integrated rate and error control. Performance evaluation is carried out under random and directional micromobility models with uncorrelated and correlated long-term fading, respectively, in a cellular WCDMA environment for both the homogeneous (or uniform) and the nonhomogeneous (or nonuniform) traffic load scenarios.     

Routing and wavelength assignment with multigranularity traffic in optical networks

We propose a novel switching architecture of multigranularity optical cross-connects (MG-OXCs) for dealing with multigranularity traffic in the optical domain. MG-OXCs can cooperate with the generalized multiprotocol label switching (MPLS) control plane, which provides the advantages of cost reduction, better scalability in physical size, and unified traffic management. Detailed discussions are provided on the characteristics and implementation issues for the switching architecture. Based on the proposed MG-OXCs, two routing and wavelength assignment (RWA) with tunnel allocation algorithms are presented: dynamic tunnel allocation (DTA) and capacity-balanced static tunnel allocation (CB-STA). In the former, we use fixed alternate routing with k-shortest paths to inspect network resources along each alternate path for dynamically setting up lightpaths. For the latter, fiber and waveband tunnels are allocated into networks at the planning stage (or off-line) according to weighted network link-state (W-NLS). We will show that with the proposed algorithms, the RWA problem with tunnel allocation in the optical networks containing MG-OXCs can be solved effectively. Simulation is conducted on networks with different percentages of switching capacity and traffic load. The simulation results show that DTA is outperformed by CB-STA in the same network environment due to a well-disciplined approach for allocating tunnels with CB-STA.. We also find that the mix of the two approaches yields the best performance given the same network environment apparatus.     

Improved proportional fair dynamic subcarrier allocation with frugality constraint for SC-FDMA system

With the objective of taking full use of channel resource, we proposed two utility based dynamic subcarrier allocation (DSA) algorithms for the single carrier frequency division multiple access (SC-FDMA) system, which are the proportional fair frugality constrained (PF-FC) algorithm and the weighted proportional fair frugality constrained (WPF-FC) algorithm. The two proposed algorithms are designed under the frugality constraint (FC) control consideration so as to avoid service rate waste and improve the spectrum efficiency. Moreover, the queuing buffer model in this paper is established on a finite size structure rather than the traditional infinite queuing manner, which is more consistent with the practical transmission condition. Simulation results indicate that the two proposed algorithms can both achieve significantly better system rate-sum capacity and quality of service (QoS) performance than their primary algorithms, and are more applicable for the heterogeneous traffic.     

Photonic slot routing: a cost effective approach to designingall-optical access and metro networks

In the backbone network, the high level of traffic aggregation achieved by numerous users is efficiently served by means of optical circuit switched solutions-the so-called wavelength routing approach. In the access and metro networks, on the contrary, the reduced level of traffic aggregation makes wavelength routing solutions inadequate. The finer and more dynamic bandwidth allocation provided by packet-interleaved optical time-division multiplexing is thus advocated in these network areas. This article presents a survey of an OTDM approach, known as photonic slot routing, or PSR. It is illustrated how this approach may provide a cost-effective solution to deploying all-optical access and metro networks with today's technology     

一种SDN架构下业务属性相关的多径路由算法

面对当前网络中流量的增长、业务种类的增多,SDN中多数的路由算法只支持一种QoS参数,没有兼顾对系统调度服务公平性的考虑,然而多参数限制的QoS 明显是NP 难问题,该问题用普通的路由算法难以解决,引进蚁群算法,在蚁群算法的基础上,将链路的时延、分组丢失率引入蚁群算法中,作为算法选择路径的依据,提出一种新的路由算法。该算法在对不同业务属性的数据流分类的基础上,根据网络的实时状况,为不同业务属性的数据流选择合适的路径,对网络中的数据流进行多路径传输。仿真实验表明,该算法能有效地降低数据流的时延、分组丢失率。     

Sparse Regeneration in Translucent Wavelength-Routed Optical Networks: Architecture,Network Design and Wavelength Routing

In this paper we study an alternate network architecture, called translucent network, to the fully transparent and fully opaque network architectures. In a translucent wavelength-routed optical network, a technique called sparse regeneration is used to overcome the severe lightpath blocking due to signal quality degradation and wavelength contention in a fully transparent network while using much less regenerators than in a fully opaque network. In this paper, we present a node model and a network model that perform sparse regeneration. We address the problem of translucent network design by proposing several regenerator placement algorithms based on different knowledge of future network traffic patterns. We also address the problem of wavelength routing under sparse regeneration by incorporating two regenerator allocation strategies with heuristic wavelength routing algorithms. We compare the performance of different regenerator placement algorithms and wavelength routing schemes through simulation experiments. The benefit of sparse regeneration is quantitatively measured under different network settings.This work was supported by NSF grants (ANI-0074121 and EPS-0091900).Portions of this work have appeared in the Proceedings of the OSA Optical Fiber Communications (OFC 1999) Conference [6] and the Proceedings of the IEEE Global Telecommunications (GLOBECOM 2001) Conference [12].     

Making Routing Robust to Changing Traffic Demands: Algorithms and Evaluation

Intra-domain traffic engineering can significantly enhance the performance of large IP backbone networks. Two important components of traffic engineering are understanding the traffic demands and configuring the routing protocols. These two components are inter-linked, as it is widely believed that an accurate view of traffic is important for optimizing the configuration of routing protocols, and through that, the utilization of the network. This basic premise, however, seems never to have been quantified. How important is accurate knowledge of traffic demands for obtaining good utilization of the network? Since traffic demand values are dynamic and illusive, is it possible to obtain a routing that is "robust" to variations in demands? We develop novel algorithms for constructing optimal robust routings and for evaluating the performance of any given routing on loosely constrained rich sets of traffic demands. Armed with these algorithms we explore these questions on a diverse collection of ISP networks. We arrive at a surprising conclusion: it is possible to obtain a robust routing that guarantees a nearly optimal utilization with a fairly limited knowledge of the applicable traffic demands     

Analysis of DS-CDMA system supporting heterogeneous traffic with decorrelating detector

Single-cell and multiple-cell direct-sequence code-division multiple-access (DS-CDMA) systems supporting heterogeneous traffic are investigated when decorrelating detector is used at receiver. Theoretical analyses and numerical examples are presented to study the effect of imperfect power control on the system performance of the reverse link. As to the forward link, the system performance is analyzed and the power allocation problem at base stations is formulated as a constrained optimization problem. Two algorithms, namely, the optimal algorithm and the unit transmission power allocation (UTXPA) algorithm, are proposed to solve this optimization problem. Computer simulations are presented to compare the performance of the proposed algorithms.     

Centralized and Distributed Algorithms for Routing and Weighted Max-Min Fair Bandwidth Allocation

Given a set of demands between pairs of nodes, we examine the traffic engineering problem of flow routing and fair bandwidth allocation where flows can be split to multiple paths (e.g., MPLS tunnels). This paper presents an algorithm for finding an optimal and global per-commodity max-min fair rate vector in a polynomial number of steps. In addition, we present a fast and novel distributed algorithm where each source router can find the routing and the fair rate allocation for its commodities while keeping the locally optimal max-min fair allocation criteria. The distributed algorithm is a fully polynomial epsilon-approximation (FPTAS) algorithm and is based on a primal-dual alternation technique. We implemented these algorithms to demonstrate its correctness, efficiency, and accuracy.