Load Balancing Algorithms In Software Defined Network

Compared with the traditional networks, the SDN networks have shown great advantages in many aspects, but also exist the problem of the load imbalance. If the load distribution uneven in the SDN networks, it will greatly affect the performance of network. Many SDN-based load balancing strategies have been proposed to improve the performance of the SDN networks. Therefore, in this paper a finding form comprehensive review help to improve further understanding of lead b balancing algorithms in SDN

CloudIoT-based Jukebox Platform: a music player for mobile users in Café

Contents services have been provided to people in a variety of ways. Jukebox service is one of the contents streaming which provides an automated music-playing service. User inserts coin and presses a play button, the jukebox automatically selects and plays the record. The Disk Jockey (DJ) in Korean cafeteria (café) received contents desired of customer and played them through the speakers in the store. In this paper, we propose a service platform that reinvented the Korean café DJ in an integrated environment of IoT and cloud computing. The user in a store can request contents (music, video, and message) through the service platform. The contents are provided through the public screen and speaker in the store where the user is located. This allows people in the same location store to enjoy the contents together. The user information and the usage history are collected and managed in the cloud. Therefore, users can receive customized services regardless of stores. We compare our platform to exist services. As a result of the performance evaluation, the proposed platform shows that contents can be efficiently provided to users and adapts IoT-Cloud integrated environments.N/

An SDN-enhanced load balancing technique in the cloud system.

The vast majority of Web services and sites are hosted in various kinds of cloud services, and ordering some level of quality of service (QoS) in such systems requires effective load-balancing policies that choose among multiple clouds. Recently, software-defined networking (SDN) is one of the most promising solutions for load balancing in cloud data center. SDN is characterized by its two distinguished features, including decoupling the control plane from the data plane and providing programmability for network application development. By using these technologies, SDN and cloud computing can improve cloud reliability, manageability, scalability and controllability. SDN-based cloud is a new type cloud in which SDN technology is used to acquire control on network infrastructure and to provide networking-as-a-service (NaaS) in cloud computing environments. In this paper, we introduce an SDN-enhanced Inter cloud Manager (S-ICM) that allocates network flows in the cloud environment. S-ICM consists of two main parts, monitoring and decision making. For monitoring, S-ICM uses SDN control message that observes and collects data, and decision-making is based on the measured network delay of packets. Measurements are used to compare S-ICM with a round robin (RR) allocation of jobs between clouds which spreads the workload equitably, and with a honeybee foraging algorithm (HFA). We see that S-ICM is better at avoiding system saturation than HFA and RR under heavy load formula using RR job scheduler. Measurements are also used to evaluate whether a simple queueing formula can be used to predict system performance for several clouds being operated under an RR scheduling policy, and show the validity of the theoretical approximation.N/