This article investigates several network-assisted streaming approaches that rely on active cooperation between video streaming applications and the network. We build a Video Control Plane that enforces Video Quality Fairness among concurrent video flows generated by heterogeneous client devices. For this purpose, a max-min fairness optimization problem is solved at runtime. We compare two approaches to actuate the optimal solution in an Software Defined Networking network: The first one allocates network bandwidth slices to video flows, and the second one guides video players in the video bitrate selection. We assess performance through several QoE-related metrics, such as Video Quality Fairness, video quality, and switching frequency. The impact of client-side adaptation algorithms is also investigated.
The Session Initiation Protocol (SIP) is a signaling protocol for managing various types of real time sessions between parties over an Internet Protocol network. An open issue is the control of overload situations that occur when the incoming flow of requests to a SIP server overcomes the server processing capacity. In particular, call establishment times increase due to overload, which triggers retransmissions and causes a further increase of the total incoming flow of requests. This paper proposes an overload control system for regulating both the queue length and the CPU load of the SIP server. The proposed control system is made of two PI controllers tuned by minimizing a proper cost function using the Extremum Seeking algorithm. A real working implementation of the SIP overload controller has been made in the open source SIP server Kamailio. A performance evaluation and comparison of the proposed controller with the main proposals existing in literature has been carried out. Results show that the proposed control system counteracts overload situations and provides a goodput close to the optimal while maintaining low call establishment delays and retransmission ratios.
The optimization of massive video delivery, with the purpose of improving user engagement by delivering the maximum available quality of experience (QoE) to users, is a hot topic. In this paper we propose a Network Control Plane (NCP) for video streaming aimed at jointly maximizing users QoE and network utilization by reserving bandwidth on a per-flow basis. The NCP is placed on top of the controlled network and cooperates with distributed buffer-based adaptation techniques implemented at the client. It is specifically designed to take into account scalability and adaptivity issues. No communication with external entities involved in the delivery process, such as other networks or the streaming server, is required. We provide a reference implementation and a performance evaluation through simulations.
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