Artificial Intelligence Enabled Software Defined Networking: A Comprehensive Overview <s> Bee colony optimization-based algorithms in SDN <s> In applications such as video surveillance systems, cameras transmit video data streams through network in which quality of received video should be assured. Traditional IP based networks cannot guarantee the required Quality of Service QoS for such applications. Nowadays, Software Defined Network SDN is a popular technology, which assists network management using computer programs. In this paper, a new SDN-based video surveillance system infrastructure is proposed to apply desire traffic engineering for practical video surveillance applications. To keep the quality of received videos adaptively, usually Constraint Shortest Path CSP problem is used which is a NP-complete problem. Hence, heuristic algorithms are suitable candidate for solving such problem. This paper models streaming video data on a surveillance system as a CSP problem, and proposes an artificial bee colony ABC algorithm to find optimal solution to manage the network adaptively and guarantee the required QoS. The simulation results show the effectiveness of the proposed method in terms of QoS metrics. <s> BIB001 </s> Artificial Intelligence Enabled Software Defined Networking: A Comprehensive Overview <s> Bee colony optimization-based algorithms in SDN <s> 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. <s> BIB002
Mohammadi and Javidan BIB001 used ABC algorithm for traffic engineering in SDN-based video surveillance systems. The main goal of this work was to increase the quality of the received video data at monitoring server, which were streamed by cameras. The performance of the proposed method has been compared to Dijkstra routing algorithm in different scenarios. The experimental results showed that the proposed method has achieved better performance compared to Dijkstra algorithm in terms of average end to end delay, packet delivery ratio and PSNR. Kang and Choo BIB002 proposed a system for load balancing in SDN-based cloud systems based on centralized dynamic load balancing approach, which uses the history from each cloud in to reach its decision. The algorithm includes two steps: job selection and job dispatching. It adopts Best-Fit approach, which means that it will dispatch a job to the shortest average response time (ART) among available clouds. The authors compared the performance of their proposed approach to honeybee foraging algorithm (HFA) and round robin (RR) approaches. The experiments showed that the average response time of the proposed system has a higher saturation point than the other two approaches.