In order to handle a high traffic demand, dense wireless local area networks (WLANs) have been deployed rapidly in the past years. However, dense WLANs cause two critical issues: wastage of energy and severe interference. To address these issues, the centralized management of dense WLANs has been emerged as a powerful paradigm for improving energy efficiency as well as avoiding severe interference. In this paper, we study the joint optimization problem of power-operation modes in access points (APs), channel selections and user-AP associations for improving energy efficiency and avoiding interference without sacrificing users' demands. To this end, we first formulate it as a mixed-integer programming using the popular Lyapunov approach, but it turns out to be computationally intractable, i.e., NP-hard. To address the issue, we propose a polynomial-time approximation algorithm and prove that it achieves a constant-factor approximation guarantee under mild assumptions. The main novelty underlying our algorithm design is based on a linear programming relaxation combining with two different greedy rounding schemes, where each achieves a constant-factor approximation in different regimes of parameters. We verify the performance of the proposed algorithm via extensive simulations and also demonstrate its practicability by implementing it at commercial APs using a Software-defined Networking framework. Results from our experiments show that it reduces the wasted energy significantly while maintaining even higher throughput.

Barista is a novel architecture that seeks to enable flexible and customizable instantiations of network operating systems (NOSs) for software-defined networks (SDNs). As the NOS is the strategic control center of an SDN, implementing logic for management of network switches as well as higher-level applications, its design is critical to the welfare of the network. In this paper, we focus on three aspects of composable controller design: component synthesis, dynamic event control, and predictive NOS assessment. First, the modular design of the Barista enables flexible composition of functionalities prevalent in contemporary SDN controllers. Second, its event handling mechanism enables dynamic customization of control flows in a NOS. Third, its predictive NOS assessment helps to discover the optimal composition for the requirements specified by operators. These capabilities allow Barista operators to optimally select functionalities and dynamically handle events for their operating requirements while maximizing the resource utilization of the given system. Our results demonstrate that Barista can synthesize NOSs with many functionalities found in commodity controllers with competitive performance profiles.

Some fundamental reasons why our networked systems are still vulnerable to network attacks are because (1) they are more open than necessary; (2) they arehomogeneous, i.e., the same way to exploit a vulnerability on one machine is easily applicable to many other machines (which is particularly a severe issue in cloud computing environments when virtual machines images are heavily reused/cloned); (3) current networked services are merelystatic targets, i.e., they are easily predictable and do not change. While network authentication and access control mechanisms such as firewall and VPN can help reduce the openness (mostly at network perimeter level), they do not help much on the latter two factors. To bridge the gap and greatly complement existing network authentication/access control mechanisms, we propose CloudRand, a new framework to make networked systems/services in the cloudheterogeneous(every host has a different networking interface) andmoving targets(such interfaces keep changing and they are unpredictable to untrusted entities). Inspired by the previous work on host-level (memory or instruction) Address Space Randomization (ASR), we build a lightweight solution to randomize network service interfaces. Thus, even derived from the same image, each virtual machine can have very different network service interfaces and they keep changing to further reduce the attack surface. CloudRand is an application-independent security service, orthogonal to existing application/network security mechanisms such as authentication, encryption, and access control. To fit into different environments such as clouds or enterprise networks, we provide various prototype systems at different levels for flexible deployment choices, e.g., host level (kernel drivers for both Linux and Windows), network level (based on Click modular router or software-defined networking technology), virtual machine hypervisor level (based on Xen), and application level (browser plugin). Our extensive evaluation shows that this solution has low overhead, and it can it can significantly reduce the network attack surface and successfully defeat malware epidemic attacks.

As the network operating system (NOS) is the strategic control center of a software-defined network (SDN), its design is critical to the welfare of the network. Contemporary research has largely focused on specialized NOSs that seek to optimize controller design across one or a few dimensions (e.g., scalability, performance, or security) due to fundamental differences in architectural trade-offs needed to support competing demands. We thus designed Barista, as a new framework that enables flexible and customizable instantiations of network operating systems (NOSs) supporting diverse design choices. The Barista framework incorporates two mechanisms to harmonize architectural differences across design choices: component synthesis and dynamic event control. First, the modular design of the Barista framework enables flexible composition of functionalities prevalent in contemporary SDN controllers. Second, its event-handling mechanism enables dynamic adjustment of control flows in a NOS. These capabilities allow operators to easily enable functionalities and dynamically handle associated events, thereby satisfying network operating requirements. Our results demonstrate that Barista can synthesize NOSs with many functionalities found in commodity NOSs with competitive performance profiles.

We design Barista, as a new framework that seeks to enable flexible and customizable instantiations of network operating systems (NOSs) supporting diverse design choices, using two key features that harmonize architectural differences across design choices: component synthesis and dynamic event control. With these capabilities, Barista operators to easily enable functionalities and dynamically adjust the control flows among those functionalities.

An effort to deploy security devices by the network provider has been increasing as the network is being exposed to various types of network attacks. However, network providers are incapable of handling all types of attacks as each security device is designed for a certain purpose. If an attack breaks out, only one particular device becomes busy in terms of resource usage while others being idle. Moreover, it is hard to adjust a level of security service with respect to the importance of network flow. To address these issues, we propose a new security solution, QoSE, which provides adaptive security services based on Network Function Virtualization (NFV). QoSE provides a capability to manage resource usage that the network flow is not concentrated on a specific node. We design QoSE considering a distributed NFV environment to avoid a single point of failure and a bottleneck problem. Our proposed solution has also shown a quick recovery from fault situation. In addition, we provide a novel resource optimization algorithm to operate security services efficiently. We have implemented a prototype system to verify our ideas and have checked that QoSE shows reasonable performance compared with a common device.

In the past years, the centralized management of dense wireless local area networks has been emerged as a powerful paradigm for improving energy efficiency as well as avoiding severe interference. In this paper, we study the joint optimization on power-operation modes in access points (APs), channel selections and user-AP associations for improving energy efficiency and avoiding interference without sacrificing users' demands. To this end, we first formulate it as a mixed-integer programming using the popular Lyapunov approach, but it turns out to be computationally intractable, i.e., NP-hard. To address the issue, we propose a polynomial-time approximation algorithm and prove that it achieves a constant-factor approximation guarantee under mild assumptions. The main novelty underlying our algorithm design is based on a linear programming relaxation combining with two different greedy rounding schemes, where each achieves a constant-factor approximation in different regimes of parameters. We verify the performance of the proposed algorithm via extensive simulations and also demonstrate its practicability by implementing it at commercial APs using a Software-defined Networking framework, which shows that it reduces the wasted energy significantly while maintaining even higher throughput.