Enabling heterogeneous network function chaining
journal contributionposted on 02.10.2018, 12:27 by Lin Cui, Fung Po TsoFung Po Tso, Song Guo, Weijia Jia, Kaimin Wei, Zhao Wei
Today's data center operators deploy network policies in both physical (e.g., middleboxes, switches) and virtualized (e.g., virtual machines on general purpose servers) network function boxes (NFBs), which reside in different points of the network, to exploit their efficiency and agility respectively. Nevertheless, such heterogeneity has resulted in a great number of independent network nodes that can dynamically generate and implement inconsistent and conflicting network policies, making correct policy implementation a difficult problem to solve. Since these nodes have varying capabilities, services running atop are also faced with profound performance unpredictability. In this paper, we propose a Heterogeneous netwOrk Policy Enforcement (HOPE) scheme to overcome these challenges. HOPE guarantees that network functions (NFs) that implement a policy chain are optimally placed onto heterogeneous NFBs such that the network cost of the policy is minimized. We first experimentally demonstrate that the processing capacity of NFBs is the dominant performance factor. This observation is then used to formulate the Heterogeneous Network Policy Placement problem, which is shown to be NP-Hard. To solve the problem efficiently, an online algorithm is proposed. Our experimental results demonstrate that HOPE achieves the same optimality as Branch-and-bound optimization but is 3 orders of magnitude more efficient.
This work has been partially supportedby Chinese National Research Fund (NSFC) No. 61772235 and 61502202; the Fundamental Research Funds for the Central Universities 21617409; the UK Engineering and Physical Sciences Research Council (EPSRC) grants EP/P004407/2 and EP/P004024/1; FDCT 0007/2018/A1, DCT-MoST Jointproject No. 025/2015/AMJ of SAR Macau; University of Macau Funds No. CPG2018-00032-FST & SRG2018-00111-FST; NSFC Key Project No. 61532013; National China 973 Project No. 2015CB352401; 985 Project of Shanghai Jiao Tong University: WF220103001; Natural Science Foundation of Guangdong Province No. 2017A030313334; and American University of Sharjah.
- Computer Science