2,877 research outputs found
Workload Equity in Vehicle Routing Problems: A Survey and Analysis
Over the past two decades, equity aspects have been considered in a growing
number of models and methods for vehicle routing problems (VRPs). Equity
concerns most often relate to fairly allocating workloads and to balancing the
utilization of resources, and many practical applications have been reported in
the literature. However, there has been only limited discussion about how
workload equity should be modeled in VRPs, and various measures for optimizing
such objectives have been proposed and implemented without a critical
evaluation of their respective merits and consequences.
This article addresses this gap with an analysis of classical and alternative
equity functions for biobjective VRP models. In our survey, we review and
categorize the existing literature on equitable VRPs. In the analysis, we
identify a set of axiomatic properties that an ideal equity measure should
satisfy, collect six common measures, and point out important connections
between their properties and those of the resulting Pareto-optimal solutions.
To gauge the extent of these implications, we also conduct a numerical study on
small biobjective VRP instances solvable to optimality. Our study reveals two
undesirable consequences when optimizing equity with nonmonotonic functions:
Pareto-optimal solutions can consist of non-TSP-optimal tours, and even if all
tours are TSP optimal, Pareto-optimal solutions can be workload inconsistent,
i.e. composed of tours whose workloads are all equal to or longer than those of
other Pareto-optimal solutions. We show that the extent of these phenomena
should not be underestimated. The results of our biobjective analysis are valid
also for weighted sum, constraint-based, or single-objective models. Based on
this analysis, we conclude that monotonic equity functions are more appropriate
for certain types of VRP models, and suggest promising avenues for further
research.Comment: Accepted Manuscrip
Lying Your Way to Better Traffic Engineering
To optimize the flow of traffic in IP networks, operators do traffic
engineering (TE), i.e., tune routing-protocol parameters in response to traffic
demands. TE in IP networks typically involves configuring static link weights
and splitting traffic between the resulting shortest-paths via the
Equal-Cost-MultiPath (ECMP) mechanism. Unfortunately, ECMP is a notoriously
cumbersome and indirect means for optimizing traffic flow, often leading to
poor network performance. Also, obtaining accurate knowledge of traffic demands
as the input to TE is elusive, and traffic conditions can be highly variable,
further complicating TE. We leverage recently proposed schemes for increasing
ECMP's expressiveness via carefully disseminated bogus information ("lies") to
design COYOTE, a readily deployable TE scheme for robust and efficient network
utilization. COYOTE leverages new algorithmic ideas to configure (static)
traffic splitting ratios that are optimized with respect to all (even
adversarially chosen) traffic scenarios within the operator's "uncertainty
bounds". Our experimental analyses show that COYOTE significantly outperforms
today's prevalent TE schemes in a manner that is robust to traffic uncertainty
and variation. We discuss experiments with a prototype implementation of
COYOTE
Optimizing IGP Link Costs for Improving IP-level Resilience
Recently, major vendors have introduced new router
platforms to the market that support fast IP-level failure pro-
tection out of the box. The implementations are based on the
IP Fast ReRoute–Loop Free Alternates (LFA) standard. LFA
is simple, unobtrusive, and easily deployable. This simplicity,
however, comes at a severe price, in that LFA usually cannot
protect all possible failure scenarios. In this paper, we give new
graph theoretical tools for analyzing LFA failure case coverage
and we seek ways for improvement. In particular, we investigate
how to optimize IGP link costs to maximize the number of
protected failure scenarios, we show that this problem is NP-
complete even in a very restricted formulation, and we give exact
and approximate algorithms to solve it. Our simulation studies
show that a deliberate selection of IGP costs can bring many
networks close to complete LFA-based protection
Combined Intra- and Inter-domain Traffic Engineering using Hot-Potato Aware Link Weights Optimization
A well-known approach to intradomain traffic engineering consists in finding
the set of link weights that minimizes a network-wide objective function for a
given intradomain traffic matrix. This approach is inadequate because it
ignores a potential impact on interdomain routing. Indeed, the resulting set of
link weights may trigger BGP to change the BGP next hop for some destination
prefixes, to enforce hot-potato routing policies. In turn, this results in
changes in the intradomain traffic matrix that have not been anticipated by the
link weights optimizer, possibly leading to degraded network performance.
We propose a BGP-aware link weights optimization method that takes these
effects into account, and even turns them into an advantage. This method uses
the interdomain traffic matrix and other available BGP data, to extend the
intradomain topology with external virtual nodes and links, on which all the
well-tuned heuristics of a classical link weights optimizer can be applied. A
key innovative asset of our method is its ability to also optimize the traffic
on the interdomain peering links. We show, using an operational network as a
case study, that our approach does so efficiently at almost no extra
computational cost.Comment: 12 pages, Short version to be published in ACM SIGMETRICS 2008,
International Conference on Measurement and Modeling of Computer Systems,
June 2-6, 2008, Annapolis, Maryland, US
On green routing and scheduling problem
The vehicle routing and scheduling problem has been studied with much
interest within the last four decades. In this paper, some of the existing
literature dealing with routing and scheduling problems with environmental
issues is reviewed, and a description is provided of the problems that have
been investigated and how they are treated using combinatorial optimization
tools
Aspects of proactive traffic engineering in IP networks
To deliver a reliable communication service over the Internet
it is essential for
the network operator to manage the traffic situation in the network.
The traffic situation is controlled by
the routing function which determines what path traffic follows from source
to destination.
Current practices for setting routing parameters in IP networks are
designed to be simple to manage. This can lead to congestion in
parts of the network while other parts of the network are
far from fully utilized. In this thesis we explore issues related
to optimization of the routing function to balance load in the network
and efficiently deliver a reliable communication service to the users.
The optimization takes into account not only the traffic situation under
normal operational conditions, but also traffic situations that appear
under a wide variety of circumstances deviating from the nominal case.
In order to balance load in the network knowledge of the traffic
situations is needed. Consequently, in this thesis
we investigate methods for efficient derivation of the
traffic situation. The derivation is based on estimation of
traffic demands from link load measurements. The advantage
of using link load measurements is that they are easily obtained and consist
of a limited amount of data that need to be processed. We evaluate and demonstrate how estimation
based on link counts gives the operator a fast and accurate description
of the traffic demands. For the evaluation we have access to a unique data
set of complete traffic demands from an operational
IP backbone.
However, to honor service level agreements at all times the variability
of the traffic needs to be accounted for in the load balancing.
In addition, optimization techniques are often sensitive to errors and
variations in input data. Hence, when an optimized routing setting is
subjected to real traffic demands in the network, performance often
deviate from what can be anticipated from the optimization. Thus,
we identify and model different traffic uncertainties and describe
how the routing setting can be optimized, not only for a nominal case,
but for a wide range of different traffic situations that might appear
in the network.
Our results can be applied in MPLS enabled networks as well as in
networks using link state routing protocols such as the widely used
OSPF and IS-IS protocols. Only minor changes may be needed in current
networks to implement our algorithms.
The contributions of this thesis is that we: demonstrate that it is
possible to estimate the traffic matrix with acceptable precision, and
we develop methods and models for common traffic uncertainties to
account for these uncertainties in the optimization of the routing
configuration. In addition, we identify important properties in the
structure of the traffic to successfully balance uncertain and
varying traffic demands
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