Advances in nanotechnology, large scale computing and communications infrastructure, coupled with recent progress in big data analytics, have enabled linking several billion devices to the Internet. These devices provide unprecedented automation, cognitive capabilities, and situational awareness. This new ecosystem--termed as the Internet-of-Things (IoT)--also provides many entry points into the network through the gadgets that connect to the Internet, making security of IoT systems a complex problem. In this position paper, we argue that in order to build a safer IoT system, we need a radically new approach to security. We propose a new security framework that draws ideas from software defined networks (SDN), and data analytics techniques; this framework provides dynamic policy enforcements on every layer of the protocol stack and can adapt quickly to a diverse set of industry use-cases that IoT deployments cater to. Our proposal does not make any assumptions on the capabilities of the devices - it can work with already deployed as well as new types of devices, while also conforming to a service-centric architecture. Even though our focus is on industrial IoT systems, the ideas presented here are applicable to IoT used in a wide array of applications. The goal of this position paper is to initiate a dialogue among standardization bodies and security experts to help raise awareness about network-centric approaches to IoT security.

We investigate the design of a clean-slate control and management plane for data networks using the abstraction of 4D architecture, utilizing and extending 4D's concept of logically centralized Decision plane that is responsible for managing network-wide resources. In this paper, a dynamically adaptable algorithm for assigning Data plane devices to a physically distributed Decision plane is presented, which enables a network to operate with minimal configuration and human intervention, while providing optimal convergence and robustness against failures. Our work is especially relevant in the context of ISPs and large geographically dispersed enterprise networks, where robust and scalable network-wide control of a large number of heterogeneous devices is desired.

We explore the design of a logically centralized but physically distributed control plane for 4D architecture. 4D architecture proposes centralization of network-wide decision making state and logic in a logical control plane to ease the management complexity of data networks. However, the current design implementations of the 4D control plane are limited to physical centralization. We argue that exploration of physically distributed control plane designs would be beneficial to the scalability and practical deployment of the architecture, and present design guidelines for different routing strategies that can be used to optimize the deployment of distributed 4D architecture.

We study link scheduling in networks with small router buffers, with the goal of minimizing the guaranteed packet loss rate bound for each ingress-egress traffic aggregate (connection). Given a link scheduling algorithm (a service discipline and a packet drop policy), the guaranteed loss rate for a connection is the loss rate under worst-case routing and bandwidth allocations for competing traffic. Under simplifying assumptions, we show that a local min-max fairness property with respect to apportioning loss events among the connections sharing each link, and a condition on the correlation of scheduling decisions at different links are two necessary and (together) sufficient conditions for optimality in the minimization problem. Based on these conditions, we introduce a randomized link-scheduling algorithm called rolling priority where packet scheduling at each link relies exclusively on local information. We show that RP satisfies both conditions and is therefore optimal.