Study on dynamic routing and spectrum assignment in bitrate flexible optical networks

The exponential growth of Internet traffic necessitates high-capacity optical networks and has also highlighted the importance of bandwidth-flexible and multi-granularity transport platforms. Improving both transport capacity and bandwidth flexibility is a significant challenge in optical networks. A bitrate flexible network architecture that is based on orthogonal frequency division multiplexing has been proposed as a promising solution for meeting this challenge. In the current study, we focus on the online routing and spectrum assignment problems in the aforementioned network architecture and introduce a general solution for dynamic bitrate flexible traffic in distributed environments. A novel spectrum representation method based on continuous spectrum segments is introduced into the networks. Segment-based routing and signaling mechanisms provide general solutions that support both the conventional slot-based networks and the ideal fully gridless networks. The routing algorithms and spectrum selection approaches are demonstrated and compared in a simulation. Performance estimation indicates that random spectrum segment assignment achieves the lowest capacity blocking rate in light traffic, whereas the adaptive routing plus minimum residual spectrum scheme obtains the lowest capacity blocking rate under heavy traffic.     

Dynamic network evolution, with examples from AT&T's evolvingdynamic network

Dynamic network evolution achieves network performance improvement and cost reduction by taking advantage of new advanced technologies being introduced into the network to achieve greater network flexibility and efficiency. The author describes the evolution of dynamic networks, with examples drawn from the AT&T DNHR network deployed in the '80s and RTNR network deployed in the '90s. Dynamic traffic routing implements an integrated class-of-service routing feature for extending dynamic routing to emerging services, and provides a self-healing network capability to ensure a network-wide path selection and immediate adaptation to failure. Dynamic traffic routing brings benefits to customers in terms of new service flexibility and improved service quality and reliability, at reduced cost     

An algorithm for configuring embedded networks in reconfigurable telecommunication networks

This paper considers a problem of configuring logical networks by employing a self-planning facility in a telecommunication network carrying voice-grade calls to make the least-cost configuration where the involved system cost includes hop cost and lost-call traffic cost. The hop cost depends on the number of self-planning facilities included on routing path connecting the associated node pairs, while the lost-call traffic cost is incurred due to link capacities. The configuration problem is analyzed through dimensioning and routing on a reconfigurable network in a mixed 0/1 nonlinear programming approach for which lower bounds are found by Lagrangian relaxation embedded in a hybrid search procedure for the associated dual problem. Heuristic solution procedures are exploited and their efficiencies are tested with various numerical examples.     

A Lagrangian-Relaxation Based Network Profit Optimization For Mesh SONET-Over-WDM Networks

In Wavelength Division Multiplexing (WDM) networks, the huge capacity of wavelength channels is generally much larger than the bandwidth requirement of individual traffic streams from network users. Traffic grooming techniques aggregate low-bandwidth traffic streams onto high-bandwidth wavelength channels. In this paper, we study the optimization problem of grooming the static traffic in mesh Synchronous Optical Network (SONET) over WDM networks. The problem is formulated as a constrained integer linear programming problem and an innovative optimization objective is developed as network profit optimization. The routing cost in the SONET and WDM layers as well as the revenue generated by accepting SONET traffic demands are modelled. Through the optimization process, SONET traffic demands will be selectively accepted based on the profit (i.e., the excess of revenue over network cost) they generate. Consiering the complexity of the network optimization problem, a decomposition approach using Lagrangian relaxation is proposed. The overall relaxed dual problem is decomposed into routing and wavelength assignment and SONET traffic routing sub-problems. The subgradient approach is used to optimize the derived dual function by updating the Lagrange multipliers. To generate a feasible network routing scheme, a heuristic algorithm is proposed based on the dual solution. A systematic approach to obtain theoretical performance bounds is presented for an arbitrary topology mesh network. This is the first time that such theoretical performance bounds are obtained for SONET traffic grooming in mesh topology networks. The optimization results of sample networks indicate that the roposed algorithm achieves good sub-optimal solutions. Finally, the influence of various network parameters is studied.     

Capacity dimensioning and routing for hybrid satellite and terrestrial systems

Satellite network architecture plays an important role in the success of a satellite business. For future commercial broadband data satellite networks integrated with the terrestrial network, satellite network topology, link capacity, and routing have major impacts on the cost of the network and the amount of revenue the network can generate. To find the most cost-effective satellite network topology, we propose a unified mathematical framework using a two-stage stochastic programming formulation. The solution to the stochastic programming formulation gives optimal link capacities and an optimal routing strategy for different network topologies, taking into account uncertainties in long-term aggregate traffic statistic estimation. Using a simple satellite network example, we show the feasible topology regions for three different satellite topologies and show that, for some parameter values, the hybrid topology is more cost effective than nonhybrid topologies. In the limit of high traffic rejection cost, stochastic dimensioning reduces to static dimensioning. We study worst case static dimensioning for a general geosynchronous earth orbit satellite network and show the feasible topology regions, as well as effective cost comparisons for different topologies. We conclude with a discussion on network cost and architectural flexibility relating to satellite network design.     

Uniform waveband assignment in optical mesh networks

The cost of an optical network in wavelength division multiplexing (WDM) networks can be reduced using optical reconfigurable optical add/drop multiplexers (ROADMs), which allow traffic to pass through without the need for an expensive optical-electro-optical (O-E-O) conversion. Waveband switching (WBS) is another technique to reduce the network cost by grouping consecutive wavelengths and switching them together using a single port per waveband. WBS has attracted the attention of researchers for its efficiency in reducing switching complexity and therefore cost in WDM optical networks. In this paper, we consider the problem of switching wavelengths as non-overlapping uniform wavebands, per link, for mesh networks using the minimum number of wavebands. Given a fixed band size b _s , we give integer linear programming formulations and present a heuristic solution to minimize the number of ROADMs (number of wavebands) in mesh networks that support a given traffic pattern. We show that the number of ROADMs (or number of ports in band-switching cross-connects) can be reduced significantly in mesh networks with WBS compared to wavelength switching using either the ILP or the heuristic algorithm. We also examine the performance of our band assignment algorithms under dynamic traffic.     

Achieving near-optimal traffic engineering solutions for current OSPF/IS-IS networks

Traffic engineering aims to distribute traffic so as to "optimize" some performance criterion. This optimal distribution of traffic depends on both the routing protocol and the forwarding mechanisms in use in the network. In IP networks running the OSPF or IS-IS protocols, routing is over shortest paths, and forwarding mechanisms distribute traffic "uniformly" over equal cost shortest paths. These constraints often make achieving an optimal distribution of traffic impossible. In this paper, we propose and evaluate an approach that can realize near optimal traffic distribution without changes to routing protocols and forwarding mechanisms. In addition, we explore the tradeoff that exists between performance and the configuration overhead that our solution requires. The paper's contributions are in formulating and evaluating an approach to traffic engineering in IP networks that achieves near-optimal performance while preserving the existing infrastructure.     

An efficient algorithm for virtual-wavelength-path routing minimizing average number of hops

We present a novel heuristic algorithm for routing and wavelength assignment in virtual-wavelength-path (VWP) routed wavelength-division multiplexed optical networks. We are the first to take up the approach of both minimizing the network cost, as well as maximizing the resource utilization. Our algorithm not only minimizes the number of wavelengths required for supporting the given traffic demand on any given topology, but also aims to minimize the mean hop length of all the lightpaths which in turn maximizes the resource utilization. The algorithm initially assigns the minimum hop path to each route and then performs efficient rerouting to reduce the number of wavelengths required while also trying to minimize the average hop length. To further reduce the network cost, we also propose a wavelength assignment procedure for VWP routed networks which minimizes the number of wavelength converters required. Our algorithm has been tested on various topologies for different types of traffic demands and has been found to give solutions much better than previous standards for this problem.     

Combining GA with Splitting Methods for Rearrangeably Nonblocking Grooming of Dynamic Traffic in SONET Ring Networks

SONET/WDM rings are widely deployed in today’s networks. To reduce the total cost of such a network, an efficient way is using the traffic grooming technique to minimize the number of add/drop multiplexers (ADMs) on the ring. Since traffic often changes frequently, the problem of supporting dynamic traffic patterns with minimum number of ADMs and wavelengths becomes incresingly important, which is referred to as grooming of dynamic traffic. In this paper, we will deal with rearrangeably nonblocking grooming of arbitrary dynamic traffic in such ring networks. We will discuss in detail the benefit of splitting methods to such a grooming way and apply them to this kind of grooming. A novel genetic algorithm (GA) approach with a hierarchical chromosome structure for each individual is proposed in combination with splitting methods to address such grooming problems. Computer simulation results under different conditions show that our algorithm is efficient in reducing both the numbers of ADMs and wavelengths.     

Dimensioning of adaptively routed networks

The authors present an algorithm for the multihour dimensioning of telephone networks operating with residual capacity adaptive routing. The method is based on dimensioning techniques for networks operating with nonhierarchical alternate routing and relies on a conservative approximation for traffic evaluation. It is a decomposition method involving a set of fixed-point equations which are solved iteratively until the Kuhn-Tucker conditions are met. The authors investigate the convergence of the method and find that some of the variables of the model are almost stationary after only a few iterations. This leads to some simplifications that make it suitable for large networks with minor modifications. They also investigate the optimality of adaptive routing by comparing it with the optimal routing coefficients and verify the operation of this routing in a network dimensioned for adaptive technique. A question of interest is how well an adaptive algorithm can adapt to dimensioning errors and how well it compares with the optimal routing in these situations     

Dynamic Routing and Wavelength Assignment Using Cost Based Heuristics in WDM Optical Networks

Dynamic routing and wavelength assignment problem in optical networks is a two-step problem that is influenced by the choice of a successful optimal path selection and wavelength assignment. Proper selection techniques reduce the number of wavelengths required in the network and thereby improves traffic grooming. Heuristic algorithms and integer linear programming models help in selection of route and wavelength separately. Hence, the computation time is large which makes the system slow. A cost function is computed which uses independent parameters in the network for the selection of route and wavelength for a call. The heuristic reduces computation time by combining the search of route and wavelength to be assigned. In addition, the network performance is analyzed with and without alternate routing along with proposed heuristics. The selection of proper route and wavelength finding technique is very essential since it improves the grooming factor of the network thereby allowing more traffic support by the network. Our objective is to investigate and propose a cost based heuristics for dynamic traffic routing and wavelength Assignment in WDM optical networks. For this we plan to develop cost functions and heuristics to compute the route and wavelength assignment strategy. Here, our objective is to reduce the computation time for selection of route and wavelength assignment strategy by weighted cost function. The function has to include network parameters for its processing. Our work provides an overview about DRWA by applying cost based heuristics in WDM networks. This paper explains the proposed cost function and its applications in line with selection of independent parameters. The details of other functions like cost function formulation, hop-based route assignment, available wavelength based route assignment, mathematical analysis of proposed cost function are also explained. Results and discussions based on the findings are presented.

     

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.     

A computationally efficient iterative solution of themultidestination optimal dynamic routing problem

The dynamic routing problem for multiple destination networks is considered. The minimum time rather than total delay cost functional is employed. The problem is solved through an iterative link-by-link optimization. Each link capacity is optimally partitioned by examining the upper bounds for the evacuation time imposed through different capacity allocations for each origin/destination pair traffic. The computational complexity per iteration is polynomial in the number of network nodes. This is due to the examination of origin/destination pairs rather then destinations alone as in previous work where a similar approach led to exponential complexity. Sufficient conditions for the convergence of the iterative algorithm to the optimum are given. If these are not satisfied supplementary steps are described which conduct the algorithm to the desired solution. These involve exponential computational complexity     

DDD Network Optimization in Field Engineering--From Theory to Application

This paper deals with some important practical applications of teletraffic theory to field engineering problems. It is shown that the following tasks concerning line switching telephone networks can be mastered by means of a few handy tables: loss calculation and dimensioning of trunk groups for full or limited access; very accurate loss approximation of link systems with an arbitrary number of stages, operating as group selection or traffic concentrating arrays with point-to-group selection mode (regarding this, and also optimal link structures, wiring, etc., see [7] in this issue); dimensioning groups with limited or full access for offered peaked overflow traffic; cost minimizing partition of the traffic in local or toll networks with alternate routing to the various trunk groups; and computerized dimensioning is of course also possible.     

Optimal dimensioning of the WDM unidirectional ECOFRAME optical packet ring

To efficiently support the high rate and the high dynamicity of the traffic in metro networks, an optical packet-switched WDM ring, named ECOFRAME, is proposed. The key features of the proposed ring are optical transparency and statistical multiplexing of optical packets on parallel WDM channels. Such features can be exploited by properly allocating wavelengths and receivers. This paper aims to optimally dimension the unidirectional ECOFRAME rings. The dimensioning at minimum cost (i.e., for wavelengths and receivers) is modeled with an mixed-integer linear programming formulation. An heuristic algorithm is also proposed, and its performance is compared against the optimal solutions and bounds. When considering the receiver and wavelength cost, results indicate that trading the wavelengths for receivers allows cost saving of up to 75% with respect to WDM optical packet rings with a single dedicated wavelength per node (i.e., single receiver at each node).     

Network dimensioning and performance of multiservice, multirateloss networks with dynamic routing

We address a multiservice, multirate loss network environment with dynamic routing. In this setting, we consider multiple traffic load periods (multihour) during the day, and by observing network dynamics, we present a network dimensioning model that consists of two steps: a bandwidth estimation step, followed by a multicommodity flow model for multiple services and traffic loads. For network operations, we discuss a probabilistic admission control policy and three multiservice routing schemes. We have used a ten-node network with multiple asymmetric traffic data sets (partially extracted from an actual network) for our study. It was found that the capacity obtained using the analytic network dimensioning model provides a good estimate of network capacity required for meeting the grade-of-service goal for each service type in each traffic load period; this observation is based on a simulated network environment that uses the proposed admission control and the dynamic routing schemes. Our observation suggests that it may not be not necessary for the dimensioning model to explicitly incorporate an admission control policy, but admission control is needed for network operation to provide desirable grade-of-service     

Interference aware cooperative routing for wireless ad hoc networks

In this paper, we propose a cooperative approach for routing in wireless ad hoc networks. Our solution improves the interference distribution in the network, with an immediate positive impact on the throughput performance and energy efficiency. In determining new routes, we consider not only the cost associated with the current route, but also the potential interference impact of the route on the neighboring nodes.We use this cooperative approach to determine routes for CDMA ad hoc networks, which are known to be severely limited in performance by the near–far effect. Our simulation results using cooperative routing show an improvement in throughput of up to 60% compared to the classic minimum energy routing approach. This improvement is achieved at the expense of only a slight increase in the average energy per bit transmission for an end-to-end path.     

Traffic grooming in WDM ring networks to minimize the maximum electronic port cost

We consider the problem of traffic grooming in WDM ring networks. Traffic grooming is a variant of the well-known logical topology design problem, and is concerned with the development of techniques for combining low speed traffic components onto high speed channels in order to minimize network cost. Previous studies have focused on aggregate representations of the network cost. In this work, we consider a Min-Max objective, in which it is desirable to minimize the cost at the node where this cost is maximum. Such an objective is of high practical value when dimensioning a network for unknown future traffic demands and/or for dynamic traffic scenarios. We present new theoretical results which demonstrate that traffic grooming with the Min-Max objective is NP-complete even when wavelength assignment is not an issue. We also present new polynomial-time traffic grooming algorithms for minimizing the maximum electronic port cost in both unidirectional and bidirectional rings. We evaluate our algorithms through experiments with a wide range of problem instances, by varying the network size, number of wavelengths, traffic load, and traffic pattern. Our results indicate that our algorithms produce solutions which are always close to the optimal and/or the lower bound, and which scale well to large network sizes, large number of wavelengths, and high loads. We also demonstrate that, despite the focus on minimizing the maximum cost, our algorithms also perform well in terms of the aggregate electronic port cost over all ring nodes.     

Multi-hour, multi-traffic class network design for virtualpath-based dynamically reconfigurable wide-area ATM networks

The virtual path (VP) concept has been gaining attention in terms of effective deployment of asynchronous transfer mode (ATM) networks in recent years. In a recent paper, we outlined a framework and models for network design and management of dynamically reconfigurable ATM networks based on the virtual path concept from a network planning and management perspective. Our approach has been based on statistical multiplexing of traffic within a traffic class by using a virtual path for the class and deterministic multiplexing of different virtual paths, and on providing dynamic bandwidth and reconfigurability through virtual path concept depending on traffic load during the course of the day. In this paper, we discuss in detail, a multi-hour, multi-traffic class network (capacity) design model for providing specified quality-of-service in such dynamically reconfigurable networks. This is done based on the observation that statistical multiplexing of virtual circuits for a traffic class in a virtual path, and the deterministic multiplexing of different virtual paths leads to decoupling of the network dimensioning problem into the bandwidth estimation problem and the combined virtual path routing and capacity design problem. We discuss how bandwidth estimation can be done, then how the design problem can be solved by a decomposition algorithm by looking at the dual problem and using subgradient optimization. We provide computational results for realistic network traffic data to show the effectiveness of our approach. We show for the test problems considered, our approach does between 6% to 20% better than a local shortest-path heuristic. We also show that considering network dynamism through variation of traffic during the course of a day by doing dynamic bandwidth and virtual path reconfiguration can save between 10% and 14% in network design costs compared to a static network based on maximum busy hour traffic     

A Novel Energy Efficient and Lifetime Maximization Routing Protocol in Wireless Sensor Networks

The energy consumption is a key design criterion for the routing protocols in wireless sensor networks (WSN). Some of the conventional single path routing schemes may not be optimal to maximize the network lifetime and connectivity. Thus, multipath routing schemes is an optimal alternative to extend the lifetime of WSN. Multipath routing schemes distribute the traffic across multiple paths instead of routing all the traffic along a single path. In this paper, we propose a multipath Energy-Efficient data Routing Protocol for wireless sensor networks (EERP). The latter keeps a set of good paths and chooses one based on the node state and the cost function of this path. In EERP, each node has a number of neighbours through which it can route packets to the base station. A node bases its routing decision on two metrics: state and cost function. It searches its Neighbours Information Table for all its neighbours concerned with minimum cost function. Simulation results show that our EERP protocol minimizes and balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime.