Global expansion model for mobile networks

In this letter, we propose a global model to solve the expansion problem of universal mobile telecommunications system (UMTS) networks. Since the network expansion problem is a generalization of the network design problem, the proposed model can be used for the design of UMTS networks. The proposed model deals simultaneously with the cell, the access network and the core network planning subproblems. This global approach has the advantage of providing better results since, in general, optimal solutions to all subproblems do not provide an optimal solution to the global problem. Moreover, this model fits real life situations in which mobile users have the choice to subscribe or to leave a service providers. Numerical results are presented and analyzed.     

A low-cost cellular mobile communication system: a hierarchicaloptimization network resource planning approach

This paper deals with the optimization of the design and radio network resource planning for cellular mobile communication systems. The key element to be considered for mobile network planning is cost. A hierarchical optimization planning method (HOP) is utilized since there are so many factors like system performance, terrain features, base station parameters, and cost factors which are involved in the large-scale system design. We present a three-level optimization approach for designing a cellular mobile system. It determines the cell number, cell site allocation, and the specific base station parameters in order to minimize the total system cost and to comply with the required system performance. The problem is formulated as a large combinatorial optimization model which can determine the optimal number of cells and select the best base stations' locations. The simulated annealing approach is developed to solve the hard combinatorial problem. Simulation results demonstrate the feasibility and effectiveness of the HOP approach for radio network planning     

A decomposition algorithm for capacity expansion of local accessnetworks

The authors study how to expand capacity of the local access network to meet projected demand over a given planning horizon at minimum cost. The alternatives for capacity expansion include both copper cable and digital multiplexer. They show how the problem can be modeled as an integer programming problem; however, the size of the problem for a typical network and the discontinuous cost structure of the expansion facilities preclude the use of a general purpose integer programming code to solve it. A decomposition approach that takes advantage of the structure of the problem and allows the problem to be solved in a reasonable amount of time is proposed. The solution methods described have been implemented and computational results are discussed. The algorithm forms a part of the network planning system NETCAP that has been in use since 1989     

Capacity Planning of Survivable Mesh-based Transport Networks under Demand Uncertainty

Almost all existing work on the design of survivable networks is based on a specific demand forecast to which one optimizes routing and transport capacity assignment for a single target planning view. In practice these single-forecast models may be used repetitively by a planner to consider a range of different scenarios individually, hoping to develop intuition about how to proceed. But this is not the same as having a planning method that can inherently and quantitatively consider a range of possible futures all at once. Our approach considers both the cost of initial design construction and the expected cost of possible augmentations or “recourse” actions required in the future, adapting the network to accommodate different actual future demands. In practice, these recourse actions might include lighting up a new DWDM channel on an existing fiber or pulling-in additional cables, or leasing additional capacity from third party network operators, and so on. A stochastic linear programming approach is used to achieve designs for which the total cost of current outlays plus the expected future recourse costs is minimized. Realistic aspects of optical networking such as network survivability based on shared spare capacity and the modularity and economy-of-scale effects are considered. These are not only important practical details to reflect in planning, but they give the “future-proof” design problem for such networks some unique aspects. For instance, what is the working capacity under one future scenario that may not waste capacity if that demand scenario does not materialize, because the same channels may be used as shared spare capacity under other future scenarios. Similarly economy-of-scale effects bear uniquely on the future-proof planning problem, as the least-cost strategy on a life-cycle basis may actually be to place more capacity today than current requirements would suggest. This is of obvious relevance to planners given the recent hard times in the telecommunications industry, causing a tendency to minimize costs now regardless of the consequences.     

Topological planning and design of UMTS mobile networks: a survey

In this paper, we present a literature review on the topological planning problem of third generation (3G) cellular networks based on the universal mobile telecommunications system (UMTS) standard. After describing the UMTS architecture, we introduce each subproblem and present major works that have been done. The cell, the access and the core network planning problems have all been considered as well as a more global approach (when more than one subproblems are considered simultaneously). Both planning and expansion algorithms are also included in this review. The goal of this paper is to present and classify the different research works that have been done so that it can be used as a starting point for future research on topological design of UMTS networks. Copyright © 2008 John Wiley & Sons, Ltd.     

Enumeration of minimal paths of modified networks

A method is presented for enumeration of minimal paths of networks generated by sequential modifications of an initial network, based upon step wise reformation of minimal paths sets associated with network modifications. The method can be applied for an effective enumeration of minimal paths of various extensions and reinforcements of an existing network in the network reliability analysis for the expansion planning. An illustrative example is included.     

Cross-layer network planning for multi-radio multi-channel cognitive wireless networks

We propose a general network planning framework for multi-radio multi-channel wireless networks. Under this framework, data routing, resource allocation, and scheduling are jointly designed to maximize a network utility function. We first treat such a cross-layer design problem with fixed radio distributions across the nodes and formulate it as a large-scale convex optimization problem. A primal-dual method together with the column-generation technique is proposed to efficiently solve this problem. We then consider the radio allocation problem, i.e., the optimal placement of radios within the network to maximize the network utility function. This problem is formulated as a large- scale combinatorial optimization problem. We derive the necessary conditions that the optimal solution should satisfy, and then develop a sequential optimization scheme to solve this problem. Simulation studies are carried out to assess the performance of the proposed cross-layer network planning framework. It is seen that the proposed approach can significantly enhance the overall network performance.     

Generalized Survivable Network

Two important requirements for future backbone networks are full survivability against link failures and dynamic bandwidth provisioning. We demonstrate how these two requirements can be met by introducing a new survivable network concept called the generalized survivable network (GSN), which has the special property that it remains survivable no matter how traffic is provisioned dynamically, as long as the input and output constraints at the nodes are fixed. A rigorous mathematical framework for designing the GSN is presented. In particular, we focus on the GSN capacity planning problem, which finds the edge capacities for a given physical network topology with the input/output constraints at the nodes. We employ fixed single-path routing which leads to wide-sense nonblocking GSNs. We show how the initial, infeasible formal mixed integer linear programming formulation can be transformed into a more feasible problem using the duality transformation. A procedure for finding the realizable lower bound for the cost is also presented. A two-phase approach is proposed for solving the GSNCPP. We have carried out numerical computations for ten networks with different topologies and found that the cost of a GSN is only a fraction (from 39% to 97%) more than the average cost of a static survivable network. The framework is applicable to survivable network planning for ASTN/ASON, VPN, and IP networks as well as bandwidth-on-demand resource allocation.     

Survivable MPLS Over Optical Transport Networks: Cost and Resource Usage Analysis

In this paper we study different options for the survivability implementation in MPLS over optical transport networks (OTN) in terms of network resource usage and configuration cost. We investigate two approaches to the survivability deployment: single layer and multilayer survivability and present various methods for spare capacity allocation (SCA) to reroute disrupted traffic. The comparative analysis shows the influence of the offered traffic granularity and the physical network structure on the survivability cost: for high bandwidth LSPs, close to the optical channel capacity, the multilayer survivability outperforms the single layer one, whereas for low bandwidth LSPs the single layer survivability is more cost-efficient. On the other hand, sparse networks of low connectivity parameter use more wavelengths for optical path routing and increase the configuration cost, as compared with dense networks. We demonstrate that by mapping efficiently the spare capacity of the MPLS layer onto the resources of the optical layer one can achieve up to 22% savings in the total configuration cost and up to 37% in the optical layer cost. Further savings (up to 9 %) in the wavelength use can be obtained with the integrated approach to network configuration over the sequential one, however, at the increase in the optimization problem complexity. These results are based on a cost model with different cost variations, and were obtained for networks targeted to a nationwide coverage     

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     

Grade-of-service differentiated static resource allocation schemes in WDM networks

This paper presents a study on the Grade-of-Service (GoS) differentiation of static resource allocation in lightpath routed WDM networks, where lightpath requests between node pairs are given. Each request is associated with a service grade. The goal is to maintain certain service levels for the requests of all grades. The service levels are measured in terms of their acceptance ratios. We solve this network optimization problem by adopting a penalty-based framework, in which network design and operation goals can be evaluated based on cost/revenue. We propose a static GoS differentiation model as one minimizing the total rejection and cost penalty, in which the rejection penalty reflects the revenue of accepting a request, and the cost penalty reflects the resource consumption of providing a lightpath to a request. Then, a solution based on the Lagrangian relaxation and subgradient methods is used to solve the proposed optimization problem. Three different application scenarios are presented: static GoS differentiation of requests between the same node pair, static GoS differentiation of requests between different node pairs, and an integration of static GoS differentiation into the network profit objective. The fairness issues and the impact of relative penalty factors are discussed to provide guidelines for network planning.     

Mixed-line-rate optical network design with wavebanding

To cope with ever increasing and more heterogeneous traffic demands, today’s optical backbone networks are expected to support mixed line rates (MLR) over different wavelength channels. MLR networks can be designed to provide flexible rate assignments to low-bit-rate services and high-bit-rate services in a cost-effective manner. But with increasing number of wavelengths in the network, aggregating wavelengths into wavebands can further reduce the network cost.In this study, we incorporate the idea of waveband switching in MLR network design. Wavebanding or grouping of optical paths reduces the optical switch size at the optical cross-connects (OXCs). When several lightpaths share several common links, they can be grouped together and routed as a single waveband. For optical bypass at a transit node, only two optical ports are required for each waveband, hence reducing the port cost. It can be a challenge for an MLR network to waveband wavelengths of different line rates that have different transmission reaches. In our design, we present a suitable switching architecture and propose an efficient and cost-effective approach for wavebanding in an MLR network. The design problem is formulated as a mixed integer linear program (MILP) where the objective is to minimize transponder cost and port cost. A heuristic algorithm for wavebanding in MLR networks is provided. To further optimize our solution, we also present a Simulated Annealing algorithm for wavebanding. Our results show a significant improvement in cost savings compared to single-line-rate (SLR) networks with wavebanding and an MLR network employing only wavelength switching.     

Recurrence times of buffer overflows in Jackson networks

The estimation of the statistics of buffer overflows in networks of queues by means of simulation is inherently costly, simply because of the rarity of these events. An alternative analytic approach is presented, with very low computational cost, for calculating the recurrence time of buffer overflows for Jackson networks in which the recurrence times of buffer overflows in a network are expressed in terms of the recurrence times for overflows of individual buffers, isolated from the network. This result is applied to the buffer allocation problem for queueing networks, providing extensions and further justification for a previously derived heuristic approach to this problem     

Research on social network influence maximization algorithm based on time sequential relationship

For the time sequential relationship between nodes in a dynamic social network,social network influence maximization based on time sequential relationship was proved.The problem was to find k nodes on a time sequential social network to maximize the spread of information.Firstly,the propagation probability between nodes was calculated by the improved degree estimation algorithm.Secondly,in order to solve the problem that WCM models based on static social networks could not be applied to time sequential social networks,an IWCM propagation model was proposed and based on this,a two-stage time sequential social network influence maximization algorithm was proposed.The algorithm used the time sequential heuristic phase and the time sequential greedy phase to select the candidate node with the largest influence estimated value inf (u) and the most influential seeds.At last,the efficiency and accuracy of the TIM algorithm were proved by experiments.In addition,the algorithm combines the advantages of the heuristic algorithm and the greedy algorithm,reducing the calculation range of the marginal revenue from all nodes in the network to the candidate nodes,and greatly shortens the running time of the program while ensuring accuracy.     

A simulation-based process model for managing complex design projects

This paper presents a process modeling and analysis technique for managing complex design projects using advanced simulation. The model computes the probability distribution of lead time in a stochastic, resource-constrained project network where iterations take place among sequential, parallel, and overlapped tasks. The model uses the design structure matrix representation to capture the information flows between tasks. We use a simulation-based analysis to account for many realistic aspects of design process behavior which were not possible in previous analytical models. We propose a heuristic for the stochastic, resource-constrained project scheduling problem in an iterative project network. The model can be used for better project planning and control by identifying leverage points for process improvements, and for evaluating alternative planning and execution strategies. An industrial example is provided to illustrate the utility of the model.     

Parallel plan execution with self-processing networks

A critical issue for space operations is how to develop and apply advanced automation techniques to reduce the cost and complexity of working in space. In this context, it is important to examine how recent advances in self-processing networks can be applied for planning and scheduling tasks. For this reason, we are currently exploring the feasibility of applying self-processing network models to a variety of planning and control problems relevant to spacecraft activities. Our goals are both to demonstrate that self-processing methods are applicable to these problems, and that MIRRORS/II, a general purpose software environment for implementing self-processing models, is sufficiently robust to support development of a wide range of application prototypes. Using MIRRORS/II and marker passing modelling techniques, we implemented a model of the execution of a “Spaceworld” plan which is a simplified model of the Voyager spacecraft which photographed Jupiter, Saturn, and their satellites. This study demonstrates that plan execution, a task usually solved using traditional AI techniques, can be accomplished using a self-processing network. The fact that self-processing networks have been applied to other space-related tasks in addition to the one discussed here demonstrates the general applicability of this approach to planning and control problems relevant to spacecraft activities. This work also demonstrates that MIRRORS/II is a powerful environment for the development/evaluation of self-processing systems.     

Redesigning network topology with technology considerations

We present a redesign methodology that automatically redesigns a network topology while considering the different network technology interfaces. The network redesign problem is to preserve as many as possible of the network devices within the original network topology to satisfy the redesign factors while minimizing the redesign cost and time. The redesign factors can be various parameters that are involved in the design of a network topology, such as the workload and number of clients. In this paper we used a uniform growth of the network workload as the main factor for topology redesign; moreover, our methodology attempts to maintain as many as possible of the network devices within the original topology while satisfying the extra growth of the clients' loads. We formulated the network redesign problem as an optimization problem and used an evolutionary approach to search the redesign space. The experimental results for a three‐level network redesign problem described here demonstrate how valuable the redesign methodology is in finding good solutions with low redesign cost and short redesign time for an enterprise networks consisting of 65 client nodes. Copyright © 2006 John Wiley & Sons, Ltd.     

On the Optimization of Message-Switching Networks

Criteria recently developed by the authors for optimum capacity assignment in message-switching networks are applied to a network model which now contains nodal processors as well as interconnecting links. Linear and stepped cost functions are examined and various performance and cost-performance curves are presented. An efficient design procedure is described for the tedious case of stepped cost functions. For general continuous cost functions and the minimax design the distribution functions of all point-to-point delays can be easily calculated.     

Resource constrained scheduling of hierarchically structured designactivity networks

In this paper, a new approach to the problem of scheduling of design activities with precedence and multiple resource constraints is proposed. In addition to the AND type relationship, OR and EXCLUSIVE OR relationships may also exist between design activities. In order to handle these logical relationships, IDEF3 is used for network representation. A large network of design activities can be arranged in different levels of abstraction. A procedure is proposed to transform an IDEF3 model into a set of alternative precedence networks. In the networks selected, the activities that are resource independent are grouped with a partitioning procedure. In order to increase the efficiency of the search for the best schedule, a procedure based on the Christofides et al. (1987) reduction procedure is introduced to determine a lower bound on the completion time of the hierarchically structured design activity network     

Joint routing and dimensioning of optical burst switching networks

Existing methods for handling routing and dimensioning in dynamic WDM networks solve the two problems separately. The main drawback of this approach is that a global minimum cost solution cannot be guaranteed. Given that wavelengths are costly resources, determining the minimum network cost is of fundamental importance. We propose an approach which jointly solves the routing and dimensioning problems in optical burst switching (OBS) networks, guaranteeing a target blocking per connection. The method finds the set of routes and the number of wavelengths per network link that minimise the total network cost. To accomplish this, an integer linear programming problem is solved. The proposed method was applied to ring networks, where the optimal solution achieves a reduction in the network cost of 10–40% (for traffic loads <0.4, compared to solving both problems separately). In the case of mesh topologies, to reduce the computational complexity of the method, we applied a variation of it which achieves a local minimum. Even so, a reduction of 5–20% (for traffic loads <0.4) in the network cost was obtained. This ability to lower network cost could make the proposed method the best choice to date for dynamic network operators.