Efficient Resource Allocation for Throughput Maximization in Next-Generation Networks

Software-Defined Networking (SDN) and Network Function Virtualization (NFV) have emerged as the foundation of the next-generation network architecture by introducing great flexibility and network automation capabilities, including automatic response to faults and load changes and programmatic provision of network resources and connections. It has been envisioned that the SDN- and NFV-based next-generation network architecture will play a critical role in providing network services to users, where the desired network services, including data transfer and policy enforcement, are fulfilled by allocating network resources using virtualization technologies. However, the disparity between ever-growing user demands and scarce network resources makes resource allocation exceptionally central to the performance of a network service, because only by effectively allocating these scarce resources can a network service provider satisfy users and maximize the gain from running the service. In this thesis, we study efficient resource allocation for network throughput maximization in next-generation networks, while meeting user resource demands and Quality of Service (QoS) requirements, subject to network resource capacities. This however poses great challenges, namely, (1) how to maximize network throughput, considering that both SDN-enabled switches and links are capacitated, (2) how to maximize the network throughput while taking into account network function and QoS requirements of users, (3) how to dynamically scale and readjust resource allocation for user requests, and (4) how to provision a network service that can satisfy user reliability requirements. To address these challenges, we provide a thorough study of network throughput maximization problems in the context of the next-generation network architecture, by formulating the problems as optimizations problems and developing novel optimization frameworks and algorithms for the problems. Specifically, this thesis makes the following contributions. Firstly, we consider dynamic user request admissions where user requests arrive one by one and the knowledge of future request arrivals is not given as a priori. We develop a novel cost model that accurately captures the usage costs of network resources and propose online algorithms with provable performance guarantees. Secondly, we study the problem of realizing user requests with network function requirements, with the objective of maximizing network throughput, while meeting user QoS requirements, subject to resource capacity constraints. For this problem, we develop two algorithms that strive for the trade-off between the accuracy/quality of a solution and the running time of obtaining the solution. Thirdly, we investigate maximization of network throughput by dynamically scaling network resources while minimizing the overall operational cost of a network. We propose a unified framework for two types of resource scaling {--} vertical scaling and horizontal scaling. Through non-trivial reductions of the problem of concern into several classic problems, we propose an algorithm that has been empirically demonstrated to deliver near-optimal solutions. Fourthly, we deal with the problem of reliability-aware provisioning of network resources for users, with the aim of maximizing network throughput. We devise an approximation algorithm with a logarithmic approximation ratio for the general case of this problem. We also develop constant-factor approximation and exact algorithm for two special cases of the problem, respectively. The formulated problem is a generalization of several classic optimization problems. Finally, in addition to extensive theoretical analyses, we also evaluate the performance of proposed algorithms empirically through experimental simulations based on real and synthetic datasets. Experimental results show that the proposed algorithms significantly outperform existing algorithms

Crystal structure of undecaprenyl-pyrophosphate phosphatase and its role in peptidoglycan biosynthesis

As a protective envelope surrounding the bacterial cell, the peptidoglycan sacculus is a site of vulnerability and an antibiotic target. Peptidoglycan components, assembled in the cytoplasm, are shuttled across the membrane in a cycle that uses undecaprenyl-phosphate. A product of peptidoglycan synthesis, undecaprenyl-pyrophosphate, is converted to undecaprenyl-phosphate for reuse in the cycle by the membrane integral pyrophosphatase, BacA. To understand how BacA functions, we determine its crystal structure at 2.6 Å resolution. The enzyme is open to the periplasm and to the periplasmic leaflet via a pocket that extends into the membrane. Conserved residues map to the pocket where pyrophosphorolysis occurs. BacA incorporates an interdigitated inverted topology repeat, a topology type thus far only reported in transporters and channels. This unique topology raises issues regarding the ancestry of BacA, the possibility that BacA has alternate active sites on either side of the membrane and its possible function as a flippase

Structural insights into the mechanism of the membrane integral N-acyltransferase step in bacterial lipoprotein synthesis

Lipoproteins serve essential roles in the bacterial cell envelope. The posttranslational modification pathway leading to lipoprotein synthesis involves three enzymes. All are potential targets for the development of new antibiotics. Here we report the crystal structure of the last enzyme in the pathway, apolipoprotein N-acyltransferase, Lnt, responsible for adding a third acyl chain to the lipoprotein’s invariant diacylated N-terminal cysteine. Structures of Lnt from Pseudomonas aeruginosa and Escherichia coli have been solved; they are remarkably similar. Both consist of a membrane domain on which sits a globular periplasmic domain. The active site resides above the membrane interface where the domains meet facing into the periplasm. The structures are consistent with the proposed ping-pong reaction mechanism and suggest plausible routes by which substrates and products enter and leave the active site. While Lnt may present challenges for antibiotic development, the structures described should facilitate design of therapeutics with reduced off-target effects

Efficient Algorithms for Throughput Maximization in Software-Defined Networks with Consolidated Middleboxes

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

Throughput Maximization in Software-Defined Networks with Consolidated Middleboxes

Today’s computer networks rely on a wide spectrum of specialized middleboxes to improve their security and performance. Traditional middleboxes that are implemented by dedicated hardware are expensive and hard to manage. A promising technique of consolidated middleboxes – implementing traditional middleboxes in Virtual Machines (VMs) – offers economical yet simplified management of middleboxes in Software-Defined Networks (SDNs). However there are still challenges to realizing user routing requests with network function enforcement (a sequence of middleboxes) while maximizing the network throughput, due to various resource constraints on SDNs, such as forwarding table capacity at each switch, bandwidth resource capacity at each link, and computing resource capacity at each server (Physical Machine). In this paper, we study the problem of maximizing the network throughput of an SDN by admitting as many user requests as possible, where each user request has both bandwidth and computing resource demands to implement its network functions (consolidated middleboxes). We first formulate the problem as a novel network throughput maximization problem. We then provide an Integer Linear Program (ILP) solution for it if the problem size is small, otherwise, we devise two heuristics that strive for the fine tradeoff between the accuracy of solutions and the running times of achieving the solutions. We finally evaluate the performance of the proposed algorithms by simulations, based on real and synthetic network topologies. Experimental results demonstrate that the proposed algorithms are very promising

Simple Preparation of Diverse Neoagaro-Oligosaccharides

A simple method for obtaining pure and well-defined oligosaccharides was established by hydrolyzing agar with β-agarase from Vibrio natriegens. The conditions for enzymolysis were optimized as follows: a temperature of 45 °C, a pH of 8.5, a substrate concentration of 0.3%, an enzyme amount of 100 U/g and an enzymolysis time of 20 h. Neoagaro-oligosaccharides with different degrees of polymerization were obtained by hydrolyzing agar with β-agarase for different lengths of time. After removing pigments using activated carbon and salts by dialyzing, the enzyme hydrolysis solution was separated with Bio-Gel P2 column chromatography. Neoagaro-oligosaccharides with different degrees of polymerization were acquired. By comparing with authentic standard substances, along with further confirmation by FTIR, MS and NMR, structures of the purified neoagaro-oligosaccharides were identified as neoagarobiose (NA2), neoagaroteraose (NA4), neoagarohexaose (NA6), neoagarooctaose (NA8), neoagaro-decaose (NA10) and neoagarododecaose (NA12) with purities of more than 97.0%. The present study established a method for the preparation of various neoagaro-oligosaccharides that may be of great significance for further study of their bioactivities

Approximation and Online Algorithms for NFV-Enabled Multicasting in SDNs

Multicasting is a fundamental functionality of networks for many applications including online conferencing, event monitoring, video streaming, and system monitoring in data centers. To ensure multicasting reliable, secure and scalable, a service chain consisting of network functions (e.g., firewalls, Intrusion Detection Systems (IDSs), and transcoders) usually is associated with each multicast request. Such a multicast request is referred to as an NFV-enabled multicast request. In this paper we study NFV-enabled multicasting in a Software-Defined Network (SDN) with the aims to minimize the implementation cost of each NFV-enabled multicast request or maximize the network throughput for a sequence of NFV-enabled requests, subject to network resource capacity constraints. We first formulate novel NFV-enabled multicasting and online NFV-enabled multicasting problems. We then devise the very first approximation algorithm with an approximation ratio of 2K for the NFV-enabled multicasting problem if the number of servers for implementing the network functions of each request is no more than a constant K (1). We also study dynamic admissions of NFV-enabled multicast requests without the knowledge of future request arrivals with the objective to maximize the network throughput, for which we propose an online algorithm with a competitive ratio of O(log n) when K = 1, where n is the number of nodes in the network. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed algorithms outperform other existing heuristics

The Potential of Neoagaro-Oligosaccharides as a Treatment of Type II Diabetes in Mice

Type 2 diabetes mellitus (T2DM) accounts for more than 90% of cases of diabetes mellitus, which is harmful to human health. Herein, neoagaro-oligosaccharides (NAOs) were prepared and their potential as a treatment of T2DM was evaluated in KunMing (KM) mice. Specifically, a T2DM mice model was established by the combination of a high-fat diet (HFD) and alloxan injection. Consequently, the mice were given different doses of NAOs (100, 200, or 400 mg/kg) and the differences among groups of mice were recorded. As a result of the NAOs treatment, the fasting blood glucose (FBG) was lowered and the glucose tolerance was improved as compared with the model group. As indicated by the immunohistochemistry assay, the NAOs treatment was able to ameliorate hepatic macrovesicular steatosis and hepatocyte swelling, while it also recovered the number of pancreatic β-cells. Additionally, NAOs administration benefited the antioxidative capacity in mice as evidenced by the upregulation of both glutathione peroxidase and superoxide dismutase activity and the significant reduction of the malondialdehyde concentration. Furthermore, NAOs, as presented by Western blotting, increased the expression of p-ERK1/2, p-JNK, NQO1, HO-1, and PPARγ, via the MAPK, Nrf2, and PPARγ signaling pathways, respectively. In conclusion, NAOs can be used to treat some complications caused by T2DM, and are beneficial in controlling the level of blood glucose and ameliorating the damage of the liver and pancreatic islands