Joint Admission Control Problem Research Articles

Joint Admission Control and Routing Via Approximate Dynamic Programming for Streaming Video Over Software-Defined Networking

This paper considers the optimization problem of joint admission control and routing for the video streaming service in wired software-defined networking (SDN). With the aid of the network operating system, SDN is able to support the dynamic nature of future network functions and intelligent applications. Against this changing network landscape, we rely on FlowVisor-based virtualization in the context of OpenFlow-based wired SDN to design an open optimization architecture for the joint admission control and routing, which supports flexible and agile deployment of advanced joint admission control and routing strategies. Following this architecture, we interpret the joint admission control and routing problem into the Markov decision process for maximizing the overall “revenue.” In order to solve the issue of the curses of dimensionality, we invoke the function approximation technique in the context of approximate dynamic programming to conceive an online learning framework. By applying kernel-based autonomous feature extraction into the function approximation, we develop an approximate dynamic programming-based joint admission control and routing for video streaming service, which is apt to be implemented in the proposed open architecture. An emulation platform based on FlowVisor, POX, and Mininet is constructed for demonstrating the success of the proposed solution. The experimental results are presented to show the performance improvement of the proposed scheme by comparing it with the Q-learning algorithm and open shortest path first-based benchmark scheme.

Optimal Online Scheduling With Arbitrary Hard Deadlines in Multihop Communication Networks

The problem of online packet scheduling with hard deadlines has been studied extensively in the single-hop setting, whereas it is notoriously difficult in the multihop setting. This difficulty stems from the fact that packet scheduling decisions at each hop influence and are influenced by decisions on other hops, and only a few provably efficient online scheduling algorithms exist in the multihop setting. We consider a multihop wired network (interference-free and full duplex transmissions) in which packets with various deadlines and weights arrive at and are destined to different nodes through given routes. We study the problem of joint admission control and packet scheduling in order to maximize the cumulative weights of the packets that reach their destinations within their deadlines. We first focus on uplink transmissions in the tree topology and show that the well-known Earliest Deadline First algorithm achieves the same performance as the optimal offline algorithm for any feasible arrival pattern. We then address the general topology with multiple source-destination pairs, develop a simple online algorithm, and show that it is O(PM log PM)-competitive, where PM is the maximum route length among all packets. Our algorithm only requires information along the route of each packet, and our result is valid for general arrival samples. Moreover, we show that O(PM log PM)-competitive is the best any online algorithm can do. Via numerical results, we also show that our algorithm achieves performance that is comparable to the noncausal optimal offline algorithm. To the best of our knowledge, this is the first algorithm with a provable (based on a sample-path construction) competitive ratio, subject to hard deadline constraints for general network topologies.

Intelligent Joint Admission Control for Next Generation Wireless Networks

The Heterogeneous Wireless Network (HWN) integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC) handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN) by the initial access network selection or the vertical handover module can be admitted and allocated the suitable resources. In this paper, a decision support system is developed to address the JAC problem in the modern HWN networks. This system combines fuzzy logic and the PROMETHEE II multiple criteria decision making system algorithm, to the problem of JAC. This combination decreases the influence of the dissimilar, imprecise, and contradictory measurements for the JAC criteria coming from different sources. A performance analysis is done and the results are compared with traditional algorithms for JAC. These results demonstrate a significant improvement with our developed algorithm.

Load shedding and distributed resource control of stream processing networks

Recent advances in networking and information technology boost the development of new and advanced services offered over communication systems that integrate a widely heterogeneous mix of applications and computer devices. Without careful traffic control and resource management, the implied dramatic increase in the demand for networking resources and remote application services may lead to substantial degradation of the Quality of Service as experienced by the end users. In this paper, we consider the problem of joint admission control and dynamic resource allocation in a stream processing network so as to optimize the overall system utility. With a primal-dual-based optimization approach, we show that the resource allocation problem and the admission control problem can be decomposed. We then present a distributed algorithm which incorporates a push-and-pull-based admission control mechanism, and a pressure-based c μ rule for resource allocation. We show that the algorithm guarantees the stability of the network and converges to the optimal solution. Various numerical experiments are then presented to demonstrate the quality of the solution and the speed of convergence.