Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75938
Title: Efficient algorithms for throughput maximization in software-defined networks with consolidated middleboxes
Authors: Huang, MT
Liang, WF
Xu, ZC
Guo, S 
Keywords: Software-defined networking
Network function virtualization
Consolidated middleboxes
Throughput maximization
Routing algorithms
Online algorithms
Network resource allocations
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on network and service management, 2017, v. 14, no. 3, p. 631-645 How to cite?
Journal: IEEE transactions on network and service management 
Abstract: Today's computer networks rely on a wide spectrum of specialized middleboxes to improve network security and performance. A promising emerging technique to implementing traditional middleboxes is the consolidated middlebox technique, which implements the middleboxes as software in virtual machines in software-defined networks (SDNs), offering economical, and simplified management for middleboxes. This however poses a great challenge, that is, how to find a cost-optimal routing path for each user request such that the data traffic of the request will pass through the middleboxes in their orders in the service chain of the request, with the objective to maximize the network throughput, subject to various resource capacity constraints in SDNs. In this paper, we study the network throughput maximization problem in an SDN under two different scenarios: one is the snapshot scenario where a set of requests at one time slot is given, we aim to admit as many requests in the set as possible to maximize the network throughput; another is the online scenario in which requests arrive one by one without the knowledge of future arrivals. Given a finite time horizon consisting of T equal time slots, the system must respond to the arrived requests in the beginning of each time slot, by either admitting or rejecting the requests, depending on the resource availabilities in the network. For the snapshot scenario, we first formulate an integer linear program (ILP) solution, we then devise two heuristics that strive for fine tradeoffs between the quality of a solution and the running time of obtaining the solution. For the online scenario, we show how to extend the proposed algorithms for the snapshot scenario to solve the online scenario. We finally evaluate the performance of the proposed algorithms through experimental simulations, based on both real and synthetic network topologies. Experimental results demonstrate that the proposed algorithms admit more requests than the baseline algorithm and the quality of the solutions delivered by heuristics is comparable to the exact solution by the ILP in most cases.
URI: http://hdl.handle.net/10397/75938
ISSN: 1932-4537
EISSN: 1932-4537
DOI: 10.1109/TNSM.2017.2725240
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