On-line routing of random calls in networks

 We consider a random sequence of calls between nodes in a complete network with link capacities. Each call first tries the direct link. If that link is saturated, then the `first-fit dynamic alternative routing algorithm' sequentially selects up to d random two-link alternative routes, and assigns the call to the first route with spare capacity on each link, if there is such a route. The `balanced dynamic alternative routing algorithm' simultaneously selects d random two-link alternative routes; and the call is accepted on a route minimising the maximum of the loads on its two links, provided neither of these two links is saturated. We determine the capacities needed for these algorithms to route calls successfully, and find that the second `balanced' algorithm requires a much smaller capacity. Our results strengthen and extend the discrete-time results presented in [10]. Received: 10 January 2002 / Revised version: 7 July 2002 / Published online: 28 March 2003     

A system for priority routing and capacity assignment in packet switched networks

A model and its associated solution procedure for the problem of concurrent flow and capacity assignment in a packet switched network are presented. The distinguishing feature of the model lies in the fact that a user defined priority level is associated with each message in the network. Different service requirements and message characteristics are associated with each message class. An algorithm that generates good feasible solutions to the model, together with tight lower bounds on the value of the objective function, is developed. Results of numerical experiments using several network topologies are reported.     

Routing optimization in packet switching communication networks

For routing assignments a special model and an optimization algorithm are proposed. The efficiency of the routing assignments is evaluated by the average value of the total cost of delays for all packets in the network. It is the objective function. The main idea is that traffic, which is transmitted from the source node to the destination node, can be split between two or more logical paths. The minimum of the objective function can be found by varying the traffic on every path and simultaneously from all the source nodes to the destination nodes. If this approach is applied, then the objective function is nonseparable and nonlinear. Because its shape is unknown in advance, an adaptive nonlinear optimization algorithm is proposed. For evaluating its efficiency a special set of test functions has been used.     

Fault-tolerant routing in circulant networks and cycle prefix networks

Reliability and efficiency are important criteria in the design of interconnection networks. Connectivity is a widely used measurement for network fault-tolerance capacities, while diameter determines routing efficiency along individual paths. In practice, we are interested in high-connectivity, small-diameter networks. Recently, Hsu introduced the notion ofw-wide diameter, which unifies diameter and connectivity. This paper investigates thew-wide diameterd _w (G) and two related parameters:w-fault diameterD _w (G) andw-Rabin numberr _w (G). In particular, we determined _w (G) andD _w (G) for 2wK(G) andG is a circulant digraphG(d ⁿ ; 1,d,...,d ^n–1) or a cycle prefix digraph.Supported in part by the National Science Council under grant NSC86-2115-M009-002.     

Multi-period traffic routing in satellite networks

We introduce a traffic routing problem over an extended planning horizon that appears in geosynchronous satellite networks. Unlike terrestrial (e.g., fiber optic) networks, routing on a satellite network is not transparent to the customers. As a result, a route change is associated with significant monetary penalties that are usually in the form of discounts (up to 40%) offered by the satellite provider to the customer that is affected. The notion of these rerouting penalties requires the network planners to explicitly consider these penalties in their routing decisions over multiple time periods and introduces novel challenges that have not been considered previously in the literature. We develop a branch-and-price-and-cut procedure to solve this problem and describe an algorithm for the associated pricing problem. Our computational work demonstrates that the use of a multi-period optimization procedure as opposed to a myopic period-by-period approach can result in cost reductions up to 13% depending on problem characteristics and network size considered. These cost reductions correspond to potential savings of several hundred million dollars for large satellite providers.     

Multi-objective evacuation routing in transportation networks

In this paper, the optimal design and analysis of evacuation routes in transportation networks is examined. An methodology for optimal egress route assignment is suggested. An integer programming (IP) formulation for optimal route assignment is presented, which utilizes M/G/c/c state dependent queueing models to cope with congestion and time delays on road links. M/G/c/c simulation software is used to evaluate performance measures of the evacuation plan: clearance time, total travelled distance and blocking probabilities. Extensive experimental results are included.     

Single-path routing of stochastic flows in networks

The paper revisits a very simple network routing and dimensioning model, with two specific assumptions: the traffic amounts to be routed are Gaussian random variables, and each commodity must use one single route in the network. The need to control congestion leads naturally to probabilistic constraints. The impact of stochastic assumptions on solution algorithms is investigated, when compared to the usual deterministic case.     

Equilibrium routing strategies in data transmission networks

Search for optimal routing (in the game-theoretical sense) in a packet data transmission network is considered. The proposed method reduces the general problem to a particular problem of routing in ring networks. A fast parallel (distributed) algorithm is constructed, which may be used in network-level data transmission protocols. Translated from Chislennye Metody i Vychislitel'nyi Eksperiment, Moscow State University, pp. 107–123, 1998.     

Wavelength routing in optical networks of diameter two

We consider optical networks with routing by wavelength division multiplexing. We show that wavelength switching is unnecessary in routings where communication paths use at most two edges. We then exhibit routings in some explicit pseudo-random graphs, showing that they achieve optimal performance subject to constraints on the number of edges and the maximal degree. We also observe the relative inefficiency of planar networks.     

Hierarchical routing over dynamic wireless networks

The topology of a mobile wireless network changes over time. Maintaining routes between all nodes requires the continuous transmission of control information, which consumes precious power and bandwidth resources. Many routing protocols have been developed, trading off control overhead and route quality. In this paper, we ask whether there exist low‐overhead schemes that produce low‐stretch routes, even in large networks where all the nodes are mobile. We present a scheme that maintains a hierarchical structure within which constant‐stretch routes can be efficiently computed between every pair of nodes. The scheme rebuilds each level of the hierarchy periodically, at a rate that decreases exponentially with the level of the hierarchy. We prove that this scheme achieves constant stretch under a mild smoothness condition on the nodal mobility processes. Furthermore, we prove tight bounds for the network‐wide control overhead under the additional assumption of the connectivity graph forming a doubling metric space. Specifically, we show that for a connectivity model combining the random geometric graph with obstacles, constant‐stretch routes can be maintained with a total overhead of bits of control information per time unit. © 2015 Wiley Periodicals, Inc. Random Struct. Alg., 47, 669–709, 2015     

Contagion and coordination in random networks

We study the problem of spreading a particular behavior among agents located in a random social network. In each period of time, neighboring agents interact strategically playing a 2 ×  2 coordination game. Assuming myopic best-response dynamics, we show that there exists a threshold for the degree of risk dominance of an action such that below that threshold, contagion of the action occurs. This threshold depends on the connectivity distribution of the network. Based on this, we show that the well-known scale-free networks do not always properly support this type of contagion, which is better accomplished by more intermediate variance networks.     

Algorithms for partitioning of large routing networks

Partitioning of large networks is vital for decentralized management and control.This paper presents two algorithms called ‘Hierarchical Recursive Progression-1’ (HRP-1) and ‘Hierarchical Recursive Progression-2’ (HRP-2) for partitioning of large networks into subnetworks of limited size with very few interconnections between them. In other words, we are trying to maximize the internal nodes and minimize the external connections of the subnetworks. The restriction on the size and the external connections is obtained by comparison against a user-defined value for the size of the subnetwork and for external connections via a term called density. The density of a subnetwork is defined as the ratio of the number of external connections and the size of the subnetwork. The two algorithms presented in the paper are based on the principle of subnetwork clustering. At the start of the algorithms,the number of subnetworks is equal to the total number of nodes of the network with each subnetwork containing a single node. Later, subnetworks are merged at various runs of the algorithm to form new subnetworks using connectivity,density and size criteria. The algorithms terminate when all the subnetworks satisfy a user-defined size and density limit. The difference between the algorithms HRP-1 and HRP-2 lies in the definition of density of subnetworks and the way through which the subnetworks are grouped at consecutive iterations of the algorithm. Note that the number of nodes inside the subnetworks never violates the size limit, thereby ensuring even distribution of load on the partitions obtained. Finally, the two algorithms are compared and tested on randomly generated graphs and a part of Paris road Network.     

On routing in VLSI design and communication networks

In this paper, we study the global routing problem in VLSI design and the multicast routing problem in communication networks. First we propose new and realistic models for both problems. In the global routing problem in VLSI design, we are given a lattice graph and subsets of the vertex set. The goal is to generate trees spanning these vertices in the subsets to minimize a linear combination of overall wirelength (edge length) and the number of bends of trees with respect to edge capacity constraints. In the multicast routing problem in communication networks, a graph is given to represent the network, together with subsets of the vertex set. We are required to find trees to span the given subsets and the overall edge length is minimized with respect to capacity constraints. Both problems are APX-hard. We present the integer linear programming (LP) formulation of both problems and solve the LP relaxations by the fast approximation algorithms for min-max resource-sharing problems in [K. Jansen, H. Zhang, Approximation algorithms for general packing problems and their application to the multicast congestion problem, Math. Programming, to appear, doi:10.1007/s10107-007-0106-8] (which is a generalization of the approximation algorithm proposed by Grigoriadis and Khachiyan [Coordination complexity of parallel price-directive decomposition, Math. Oper. Res. 2 (1996) 321-340]). For the global routing problem, we investigate the particular property of lattice graphs and propose a combinatorial technique to overcome the hardness due to the bend-dependent vertex cost. Finally, we develop asymptotic approximation algorithms for both problems with ratios depending on the best known approximation ratio for the minimum Steiner tree problem. They are the first known theoretical approximation bound results for the problems of minimizing the total costs (including both the edge and the bend costs) while spanning all given subsets of vertices.     

Price-directive decomposition applied to routing in telecommunication networks

The telecommunication network design problem is considered to study the level of transmission network. A heuristic approach is defined to solve the combined routing-grouping problem, where the grouping one is solved by a heuristic approach. The routing problem is defined considering reliability constraints, supplementary circuits demands and a piecewise linear objective function to take into account the influence of the grouping. This last model is solved using a price-directive decomposition method, which has allowed us to solve real networks using an exact method.     

A meta-model for multiobjective routing in MPLS networks

MPLS (Multiprotocol Label Switching) enables the utilisation of explicit routes and other advanced routing mechanisms in multiservice packet networks, capable of dealing with multiple and heterogeneous QoS (Quality of Service) parameters. Firstly the paper presents a discussion of conceptual and methodological issues raised by multiobjective routing optimisation models for MPLS networks. The major contribution is the proposal of a multiobjective routing optimisation framework for MPLS networks. The major features of this modelling framework are: the formulation of a three-level hierarchical routing optimisation problem including network and service performance objectives, the inclusion of fairness objectives in the different levels of optimisation and a two-level stochastic representation of the traffic in the network (traffic flow and packet stream levels). A variant of the general model for two classes of traffic flows, QoS traffic and Best Effort traffic, is also presented. Finally a stochastic teletraffic modelling approach, underlying the optimisation model, is fully described. Work partially supported by programme POSI of the III EC programme cosponsored by FEDER and national funds.     

Sufficient conditions for protection routing in IP networks

Providing fully distributed, fault tolerant, hop-by-hop routing is one of the key challenges for intra-domain IP networks. This can be achieved by storing two next-hops for each destination node in the forwarding table of the routers, and the packets are forwarded to primary next-hop (PNH), unless PNH is unreachable and secondary next-hop (SNH) is used instead. We follow the architecture by Kwong et al. in On the feasibility and efficacy of protection routing in IP networks, University of Pennsylvania (2010), where the routing tables are configured in a centralized way, while the forwarding and failure recovery is in a fully distributed way without relying on any encapsulation and signaling mechanisms for failure notification, to meet the standard IP forwarding paradigm. A network is protected if no single link of node failure results in forwarding loops. Kwong et al. (On the feasibility and efficacy of protection routing in IP networks, University of Pennsylvania 2010) conjectured that network node connectivity is not sufficient for a network to be protectable. In this paper we show that this conjecture is in contradiction with a conjuncture by Hasunuma (Discrete Math 234(1–3):149–157, 2001; in Graph-Theoretic Concepts in Computer Science, Springer, Berlin, pp. 235–245, 2002), and show that every four connected maximal planar graph and every underlying graph of a 2-connected line digraph has feasible protection routing.     

Internet packet routing: Application of a K-quickest path algorithm

This paper describes a study on the application of an algorithm to rank the K-quickest paths to the routing of data packets in Internet networks. For this purpose an experimental framework was developed by considering two types of random generated networks. To simulate values of the IP packet sizes, a truncated Pareto distribution was defined, having in mind to reflect a key feature of Internet traffic, namely its self-similar stochastic nature. Results concerning the average CPU times of the algorithm for the different sets of experiments will be presented and discussed.     

A heuristic approach for capacity expansion of packet networks

We address the problem of expanding transmission capacity of an existing packet network over a multiperiod planning horizon, the objective being low total cost of expansion. Discrete capacity choices, interaction with routing decisions, and economy of scale in the cost of capacity make it extremely difficult to decide when, where and how much capacity to add. A fast heuristic solution method is developed based on the well established Flow Deviation routing algorithm. The heuristic begins by making myopic expansion decisions, which are then subsequently adjusted to account for economies of scale in the cost of capacity. Heuristic solutions are compared to a benchmark which approximates the real cost function by its linear lower envelope. Since the number of possible expansion plans is an exponential function of the number of edges, capacity choices, and periods in the planning horizon, a fast heuristic allows one to look beyond small problems at more realistically sized ones.     

Efficient and fair routing for mesh networks

Inspired by the One Laptop Per Child project, we consider mesh networks that connect devices that cannot recharge their batteries easily. We study how the mesh should retransmit information to make use of the energy stored in each of the nodes effectively. The solution that minimizes the total energy spent by the whole network may be very unfair to some nodes because they bear a disproportionate burden of the traffic. A Nash equilibrium—achieved when nodes minimize the energy they spend—does not model the situation well because, as retransmissions consume battery without increasing the node’s utility, it predicts that nodes refuse to participate. Actually, there are wireless communication protocols, peer-to-peer networks and other systems that provide incentives or impose penalties to encourage nodes to be active and to participate. We explicitly aim at the solution that minimizes the total energy spent by nodes among those that satisfy a fairness constraint. Although this does not guarantee that the solution is at equilibrium, nodes do not have a big incentive to deviate from the proposed solution since they do not view the situation as extremely unfair to them. This is consistent with the recommendation of Beccaria and Bolelli (Proceedings of the 3rd IEEE Vehicle Navigation & Information Systems Conference, pp. 117–126, Oslo, 1992) who proposed to optimize social welfare keeping user needs as constraints. We propose a distributed and online routing algorithm and compare it to an offline, centralized approach. The centralized approach, besides being unrealistic in terms of information requirements, is also NP-hard to solve. For both reasons, we focus on the former and evaluate it by conducting an extensive set of computational experiments that evaluate the efficiency and fairness achieved by our algorithm.