Accurate and Efficient Monitoring for Virtualized SDN in Clouds

Abstract : This paper presents V-Sight, a network monitoring framework for programmable virtual networks in clouds. Network virtualization based on software-defined networking (SDN-NV) in clouds makes it possible to realize programmable virtual networks; consequently, this technology offers many benefits to cloud services for tenants. However, to the best of our knowledge, network monitoring, which is a prerequisite for managing and optimizing virtual networks, has not been investigated in the context of SDN-NV systems. As the first framework for network monitoring in SDN-NV, we identify three challenges: non-isolated and inaccurate statistics, high monitoring delay, and excessive control channel consumption for gathering statistics. To address these challenges, V-Sight introduces three key mechanisms: 1) statistics virtualization for isolated statistics, 2) transmission disaggregation for reduced transmission delay, and 3) pCollector aggregation for efficient control channel consumption. The evaluation results reveal that V-Sight successfully provides accurate and isolated statistics while reducing the monitoring delay and control channel consumption in orders of magnitude. We also show that V-Sight can achieve a data plane throughput close to that of non-virtualized SDN.

 EXISTING SYSTEM :

 ? The special features of cloud-fog, other existing orchestrations, such as the one from cloud, cannot be applied. ? It can reduce the overall energy consumption by an average of 20%, compared to existing IoT networks. ? There exist already research studies for each layer. In this paper, we introduce some works used SDN in hybrid cloud-fog systems, mostly for connecting the cloud layer to the fog layer, or connecting fog nodes together for different use cases. ? We should consider that fog is tightly linked to the existence of a cloud, and it cannot work in a standalone mode. ? ScalCon outperforms existing schemes in terms of path computation time, path setup latency, end-to-end delay and communication overhead.

 DISADVANTAGE :

 ? One way to solve this problem is for the “hypervisor” software that provides processor virtualization also implements as many virtual NICs (vNICs) as there are VMs. ? However, the problem of routing using ASPs’ policies in a very dynamic multi-cloud environment is not possible since Internet service providers (ISPs) offer no service to dynamically route messages to a different server using an ASP’s policies. ? This is the time when researchers, startups, and all vendors need to pay attention since this is the opportunity to make an impact. ? SDN is expected to make the networks programmable and easily partitionable and virtualizable. These features are required for cloud computing where the network infrastructure is shared by a number of competing entities.

 PROPOSED SYSTEM :

 • In the research paper, the authors proposed a dynamic offloading mechanism among the fog nodes to address the challenge of static offloading and oblivious link selection in vehicular networks. • In the proposed method, the SDN controller collects the statistics, computational capabilities status, and supported services of a fog node, using the fog agent. • To analyze the performance of proposed solutions, the authors considered three environments, where the links and nodes reliability could be good, poor and mixed. • They also proposed an algorithm (which is dependent on partitioning the SDN virtually) to select the optimal access point and optimal place to process the data.

 ADVANTAGE :

 ? The service may be partitioned for improved performance, with each partition hosted on a different group of servers. ? Proxies can be located anywhere on the global Internet. Of course, they should be located in proximity to users and servers for optimal performance. ? This is quite inefficient, but is how current Internet control protocols work. Centralization of control makes sensing the state and adjusting the control dynamically based on state changes much faster than with distributed protocols. ? Each processor can run multiple virtual machines (VMs), and each machine can be used by a different user. ? This is the case with storage, where a large number of inexpensive unreliable disks can be used to make up large reliable storage.