Active measurements are integral to the operation and management of networks, and invaluable to supporting empirical network research. Unfortunately, it is often cost-prohibitive and logistically difficult to widely deploy measurement nodes, especially in the core. In this work, we consider the feasibility of tightly integrating measurement within the infrastructure by using Software Defined Networks (SDNs). We introduce "SDN as Active Measurement Infrastructure" (SAAMI) to enable measurements to originate from any location where SDN is deployed, removing the need for dedicated measurement nodes and increasing vantage point diversity. We implement ping and traceroute using SAAMI, as well as a proof-of-concept custom measurement protocol to demonstrate the power and ease of SAAMI's open framework. Via a large-scale measurement campaign using SDN switches as vantage points, we show that SAAMI is accurate, scalable, and extensible.
Zeng al first posited the notion of SDN controllers instructing switches to send test packets in the context of their Automated Test Packet Generation system in @cite_18 . We extend this idea to the variety of active measurements in use today, and implement such a system in real SDN hardware and software.
@cite_18
2480271867 2051714560 2034677282 2612803454
In this paper we address the problem of Software Defined Networking (SDN) controller placement in large networks. Indeed, to solve the scalability issue raised by the centralized architecture of SDN, multi-controllers deployment (or distributed controllers system) is envisioned. However, the number and the location of controllers in large networks remain an issue. In this context, several works have been proposed to find the optimal placement of SDN controllers. Most of them consider latency among SDN controllers and switches as the main metric. In this work, we go beyond the state of art by proposing a solution that considers at the same time three critical objectives for the optimal placement of controllers: (i) the latency and communication overhead between switches and controllers; (ii)the latency and communication overhead between controllers; (iii) the guarantee of load balancing between controllers. We then solve the system by using Bargaining Game in order to find a fair trade off between these objectives. Simulation results clearly demonstrate the effectiveness of the proposed solution in finding the optimal placement of controllers that enforces this trade-off. In software-defined networking (SDN), a software controller manages a distributed collection of switches by installing and uninstalling packet-forwarding rules in the switches. SDNs allow flexible implementations for expressive and sophisticated network management policies. We consider the problem of verifying that an SDN satisfies a given safety property. We describe Kuai, a distributed enumerative model checker for SDNs. Kuai takes as input a controller implementation written in Murphi, a description of the network topology (switches and connections), and a safety property, and performs a distributed enumerative reachability analysis on a cluster of machines. Kuai uses a set of partial order reduction techniques specific to the SDN domain that help reduce the state space dramatically. In addition, Kuai performs an automatic abstraction to handle unboundedly many packets traversing the network at a given time and unboundedly many control messages between the controller and the switches. We demonstrate the scalability and coverage of Kuai on standard SDN benchmarks. We show that our set of partial order reduction techniques significantly reduces the state spaces of these benchmarks by many orders of magnitude. In addition, Kuai exploits large-scale distribution to quickly search the reduced state space. Software Defined Networking (SDN) has become a popular paradigm for centralized control in many modern networking scenarios such as data centers and cloud. For large data centers hosting many hundreds of thousands of servers, there are few thousands of switches that need to be managed in a centralized fashion, which cannot be done using a single controller node. Previous works have proposed distributed controller architectures to address scalability issues. A key limitation of these works, however, is that the mapping between a switch and a controller is statically configured, which may result in uneven load distribution among the controllers as traffic conditions change dynamically. To address this problem, we propose ElastiCon, an elastic distributed controller architecture in which the controller pool is dynamically grown or shrunk according to traffic conditions. To address the load imbalance caused due to spatial and temporal variations in the traffic conditions, ElastiCon automatically balances the load across controllers thus ensuring good performance at all times irrespective of the traffic dynamics. We propose a novel switch migration protocol for enabling such load shifting, which conforms with the Openflow standard. We further design the algorithms for controller load balancing and elasticity. We also build a prototype of ElastiCon and evaluate it extensively to demonstrate the efficacy of our design. With the popularization and spread of SDN, the size of SDN networks is increasing; the controller placement is a key problem in software defined networks (SDNs). In this paper, an optimized controller placement method is proposed, which takes into consideration the load of controllers, co-located deployment and propagation latency to determine the optimal number and location of controllers. Firstly, multi-objective genetic algorithm is used to get the connection relationship of controllers and switches, so the network can be partitioned into several domains. Secondly, minimum delay algorithm is adopted to find an optimal location which has a minimizing sum of the distance to the other points in each domain. Finally, in this article, the results obtained from the analytic and experimental performance can evaluate the benefits that could be achieved by deploying our scheme for the SDN controller placement problem.