Combining Fairness with Throughput: Online Routing with Multiple Objectives

  title={Combining Fairness with Throughput: Online Routing with Multiple Objectives},
  author={Ashish Goel and Adam Meyerson and Serge A. Plotkin},
  journal={J. Comput. Syst. Sci.},
This paper presents online algorithms for routing and bandwidth allocation which simultaneously approximate fair and max-throughput solutions. In fact, the algorithms solve a more difficult problem: for any bandwidth b, the number of sessions that get bandwidth b in the online algorithm is not smaller than the number of sessions receiving ?b offline, where ? is the competitive ratio. This problem is provably harder than the problem of maximizing throughput (e.g., 4) or the problem of maximizing… 
Pricing for Fairness: Distributed Resource Allocation for Multiple Objectives
It is proved that this algorithm is an O(log ρ)-approximation for all canonical utility functions simultaneously, i.e. without any knowledge of  U, which results in a simple and practical protocol for bandwidth allocation in a network.
Pricing for fairness: distributed resource allocation for multiple objectives
It is proved that this algorithm is an O(log ρ)-approximation for all canonical utility functions simultaneously, i.e. without any knowledge of U, and extended to multi-path routing, and also to a natural pricing mechanism that results in a simple and practical protocol for bandwidth allocation in a network.
Optimal multi-path routing and bandwidth allocation under utility max-min fairness
  • J. Chou, B. Lin
  • Computer Science, Business
    2009 17th International Workshop on Quality of Service
  • 2009
Evaluations of the proposed multi-path utility max-min fair allocation algorithms on a statistical traffic engineering application are presented to show that significantly higher minimum utility can be achieved whenMulti-path routing is considered simultaneously with bandwidth allocation under utilitymax-min fairness, and this higherminimum utility corresponds to significant application performance improvements.
Centralized and Distributed Algorithms for Routing and Weighted Max-Min Fair Bandwidth Allocation
An algorithm for finding an optimal and global per-commodity max-min fair rate vector in a polynomial number of steps and a fast and novel distributed algorithm where each source router can find the routing and the fair rate allocation for its commodities while keeping the locally optimal max-Min fair allocation criteria.
Improved bounds for online routing and packing via a primal-dual approach
  • Niv Buchbinder, J. Naor
  • Computer Science
    2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06)
  • 2006
This work develops a new generic online routing algorithm that outperforms previous algorithms suggested earlier and shows the applicability of the primal-dual method to various models and provides improved algorithms for achieving coordinate-wise competitiveness, maximizing throughput, and minimizing maximum load.
A practical algorithm for balancing the max-min fairness and throughput objectives in traffic engineering
A novel way to balance the throughput and fairness objectives with linear programming is proposed that allows the network operator to precisely control the trade-off by bounding the fairness degradation for each commodity compared to the max-min fair solution or the throughput degradationCompared to the optimal throughput.
The Design of Competitive Online Algorithms via a Primal-Dual Approach
This survey shows in this survey how to extend the primal—dual method to the setting of online algorithms, and shows its applicability to a wide variety of fundamental problems.
Fairness measures for resource allocation
  • Amit Kumar, J. Kleinberg
  • Computer Science
    Proceedings 41st Annual Symposium on Foundations of Computer Science
  • 2000
This work considers the problem of producing solutions that simultaneously approximate all feasible allocations in a coordinate-wise sense, and explores its consequences in a range of discrete optimization problems, including facility location, scheduling, and bandwidth assignment in networks.
A linear programming based approach for computing optimal fair splittable routing
  • D. Nace
  • Computer Science
    Proceedings ISCC 2002 Seventh International Symposium on Computers and Communications
  • 2002
An iterative algorithm for computing fair routing in networks where the available resources are shared among competing flows according to a max-min fair sharing criterion is presented, a linear programming based approach which permits a lexicographical maximization of the vector of fair-share attributed to the connections competing for network resources.
Fair online load balancing
A job-centric and a machine-centric view of fairness are considered, equivalent to the approximate notion of prefix competitiveness proposed by Kleinberg, Rabani and Tardos, as well as to the notion of approximate majorization, and they generalize the well studied notion of max-min fairness.


Fairness in Routing and Load Balancing
This work considers the issue of network routing subject to explicit fairness conditions, and obtains the first approximation algorithms for this basic optimization problem, for single-source unsplittable routings in an arbitrary directed graph.
On-line load balancing with applications to machine scheduling and virtual circuit routing
An algorithm is described that achieves an O (log n) competitive ratio, where n is the number of nodes in the network, for the case where virtual circuits continue to exist forever and for the related machines case, the first algorithm that achieves constant competitive ratio is described.
Routing and admission control in general topology networks with Poisson arrivals
A new routing and admission control algorithm for general topology networks that does not require advance knowledge of the traffic patterns and outperforms greedy admission control over a broad range of network environments is suggested.
Convergence Complexity of Optimistic Rate-Based Flow-Control Algorithms
A new approach is suggested for rate-based flow-control algorithms and of the max-min fairness criteria, which may be considered more “optimistic” and realistic than traditional approaches and shows that under certain conditions the approximate algorithms may converge faster.
Global optimization using local information with applications to flow control
  • Y. Bartal, J. Byers, D. Raz
  • Computer Science
    Proceedings 38th Annual Symposium on Foundations of Computer Science
  • 1997
A distributed algorithm that obtains a (1+/spl epsiv/) approximation to the global optimum solution and runs in a polylogarithmic number of distributed rounds, which is considerably simpler than previous approximation algorithms for positive linear programs, and thus may have practical value in both centralized and distributed settings.
Fast, Fair and Frugal Bandwidth Allocation in ATM Networks
This paper gives a frugal RM cell protocol for ABR that matches the convergence time of the fastest known non-frugal protocol and achieves a quadratic convergence rate.
Analysis and simulation of a fair queueing algorithm
It is found that fair queueing provides several important advantages over the usual first-come-first-serve queueing algorithm: fair allocation of bandwidth, lower delay for sources using less than their full share of bandwidth and protection from ill-behaved sources.
Data Networks
A generalized processor sharing approach to flow control in integrated services networks: the single-node case
Worst-case bounds on delay and backlog are derived for leaky bucket constrained sessions in arbitrary topology networks of generalized processor sharing (GPS) servers and the effectiveness of PGPS in guaranteeing worst-case session delay is demonstrated under certain assignments.
Optimal flows in networks with multiple sources and sinks
The concept of an optimal flow in a multiple source, multiple sink network is defined and an existence proof and an algorithm are given that generalizes maximal flow inA single source, single sink network.