Network planning and design

About: Network planning and design is a research topic. Over the lifetime, 12393 publications have been published within this topic receiving 229776 citations. The topic is also known as: network design.

Oblivious network design

Abstract: Consider the following network design problem: given a network G = (V, E), source-sink pairs {si, ti} arrive and desire to send a unit of flow between themselves. The cost of the routing is this: if edge e carries a total of fe flow (from all the terminal pairs), the cost is given by Σ el(fe), where l is some concave cost function; the goal is to minimize the total cost incurred. However, we want the routing to be oblivious: when terminal pair {si, ti} makes its routing decisions, it does not know the current flow on the edges of the network, nor the identity of the other pairs in the system. Moreover, it does not even know the identity of the function l, merely knowing that l is a concave function of the total flow on the edge. How should it (obliviously) route its one unit of flow? Can we get competitive algorithms for this problem?In this paper, we develop a framework to model oblivious network design problems (of which the above problem is a special case), and give algorithms with poly-logarithmic competitive ratio for problems in this framework (and hence for this problem). Abstractly, given a problem like the one above, the solution is a multicommodity flow producing a "load" on each edge of Le = l(f1(e),f2(e), ..., fk(e)), and the total cost is given by an "aggregation function" agg (Le1,...,Lem) of the loads of all edges. Our goal is to develop oblivious algorithms that approximately minimize the total cost of the routing, knowing the aggregation function agg, but merely knowing that l lies in some class C, and having no other information about the current state of the network. Hence we want algorithms that are simultaneously "function-oblivious" as well as "traffic-oblivious".The aggregation functions we consider are the max and σ objective functions, which correspond to the well-known measures of congestion and total cost of a network; in this paper, we prove the following:• If the aggregation function is Σ, we give an oblivious algorithm with O(log2n) competitive ratio whenever the load function l is in the class of monotone sub-additive functions. (Recall that our algorithm is also "function-oblivious"; it works whenever each edge has a load function l in the class.)• For the case when the aggregation function is max, we give an oblivious algorithm with O(log2n log log n) competitive ratio, when the load function l is a norm; we also show that such a competitive ratio is not possible for general sub-additive functions.These are the first such general results about oblivious algorithms for network design problems, and we hope the ideas and techniques will lead to more and improved results in this area.

Scheduled Service Network Design for Freight Rail Transportation

Abstract: This paper addresses the scheduled service network design problem for freight rail transportation. The proposed model integrates service selection and scheduling, car classification and blocking, train makeup, and routing of time-dependent customer shipments based on a cyclic three-layer space--time network representation of the associated operations and decisions and their relations and time dimensions. This paper also proposes a matheuristic solution methodology integrating slope scaling, a dynamic block-generation mechanism, long-term-memory-based perturbation strategies, and ellipsoidal search, a new intensification mechanism to thoroughly explore very large neighborhoods of elite solutions restricted using information from the history of the search. Experimental results show that the proposed solution method is efficient and robust, yielding high-quality solutions for realistically sized problem instances.

Game-theoretic models for reliable path-length and energy-constrained routing with data aggregation in wireless sensor networks

Abstract: Path length, path reliability, and sensor energy-consumption are three major constraints affecting routing in resource constrained, unreliable wireless sensor networks. By considering the implicit collaborative imperative for sensors to achieve overall network objectives subject to individual resource consumption, we develop a game-theoretic model of reliable, length and energy-constrained, sensor-centric information routing in sensor networks. We define two distinct payoff (benefit) functions and show that computing optimally reliable energy-constrained paths is NP-Hard under both models for arbitrary sensor networks. We then show that optimal length-constrained paths can be computed in polynomial time in a distributed manner (using O(E) messages) for popular sensor network implementations using geographic routing. We also develop sensor-centric metrics called path weakness to measure the qualitative performance of different routing schemes and provide theoretical limits on the inapproximability of computing paths with bounded weakness. Heuristics for computing optimal paths in arbitrary sensor networks are described along with simulation results comparing performance with other routing algorithms.

Linear Programming Models for the User and System Optimal Dynamic Network Design Problem: Formulations, Comparisons and Extensions

Abstract: In this paper we formulate a network design model in which the traffic flows satisfy dynamic user equilibrium conditions for a single destination. The model presented here incorporates the Cell Transmission Model (CTM); a traffic flow model capable of capturing shockwaves and link spillovers. Comparisons are made between the properties of the Dynamic User equilibrium Network Design Problem (DUE NDP) and an existing Dynamic System Optimal (DSO) NDP formulation. Both network design models have different objective functions with similar constraint sets which are linear and convex. Numerical demonstrations are made on multiple networks to demonstrate the efficacy of the model and demonstrate important differences between the DUE and DSO NDP approaches. In addition, the flexibility of the approach is demonstrated by extending the formulation to account for demand uncertainty. This is formulated as a stochastic programming problem and initial test results are demonstrated on test networks. It is observed that not accounting for demand uncertainty explicitly, provides sub-optimal solution to the DUE NDP problem.

Framework for network survivability performance

Abstract: The article is based on the results of ANSI Technical Subcommittee T1A1 activities in the area of a general framework for telecommunication network survivability performance. The issues of users' expectations and requirements, outage categorization, and a framework for analysis of survivability techniques are discussed. Based on the survivability framework, models for network survivability assessment and analysis are considered, and performance measures are described. Examples illustrate the application of this framework in network design and planning. >