This paper proposes an application-aware multipath packet forwarding framework that integrates Machine Learning Techniques (MLT) and Software Defined Networks (SDN). As the Internet provides a variety of services and their performance requirement has become heterogeneous, it is common to come across the scenario of multiple flows competing for a constrained resource such as bandwidth, less jitter or low latency path. Such factors are application specific requirement that is beyond the knowledge of a simple combination of protocol type and port number. Better overall performance could be achieved if the network is able to prioritize the flows and assign resources based on their application specific requirement. Our system prioritizes each of the flows using MLT and routes it through a path according to the flow priority and network state using SDN. The proof of concept implementation has been done on OpenvSwitch and evaluation results involving a large number of flows exhibited a significant improvement over the traditional network setup. We also report that the port number and protocol are not contributing to determine the application in the decision-making process of Machine Learning (ML).
Weiyang @cite_9 proposed a strategy to overcome traffic congestion and physical impairment in OpenFlow network. They look for an alternate path to avoid congestion by changing the path of high-data-rate IP traffic to circuit switching and also physical impairments like fiber cut. These fiber cuts can be determined by monitoring the abnormality in the path between optical nodes. But our approach proactively finds a better path and inserts the flow rules and hence avoids congestion for sensitive and delay intolerant traffic. Also, the work does not use any application classifier mechanism.
@cite_9
2051343255 2171899087 2160995598 1970554468
This paper introduces a novel technique for access by a cognitive Secondary User (SU) to a spectrum with an incumbent Primary User (PU), which uses Type-I Hybrid ARQ. The technique allows the SU to perform selective retransmissions of previously corrupted SU data packets. The temporal redundancy introduced by the primary ARQ protocol and by the selective SU retransmission process can be exploited by the SU receiver to perform Interference Cancellation (IC) over the entire interference pattern, thus creating a "clean" channel for the decoding of the concurrent message. The chain decoding technique, initiated by a successful decoding operation of a SU or PU message, consists in the iterative application of IC, as previously corrupted messages become decodable. Based on this scheme, we design an optimal policy that maximizes the SU throughput under a constraint on the average long-term PU throughput degradation. We show that the optimal policy can be found by first optimizing the SU access policy using a Markov Decision Process formulation, and then applying a chain decoding protocol defined by five basic rules. Such an approach enables a compact state representation of the protocol, and its efficient numerical optimization. Finally, we show by numerical results the throughput benefit of the proposed technique. We demonstrate multipath routing and wavelength re-assignment in OpenFlow-enabled packet-circuit network, aware of links' bandwidth utilization, applications' protocol, and quality of transmission. Applications are re-routed under traffic congestion and wavelengths are re-assigned under physical impairments. As the operation of our fiber-optic backbone networks migrates from interconnected SONET rings to arbitrary mesh topology, traffic grooming on wavelength-division multiplexing (WDM) mesh networks becomes an extremely important research problem. To address this problem, we propose a new generic graph model for traffic grooming in heterogeneous WDM mesh networks. The novelty of our model is that, by only manipulating the edges of the auxiliary graph created by our model and the weights of these edges, our model can achieve various objectives using different grooming policies, while taking into account various constraints such as transceivers, wavelengths, wavelength-conversion capabilities, and grooming capabilities. Based on the auxiliary graph, we develop an integrated traffic-grooming algorithm (IGABAG) and an integrated grooming procedure (INGPROC) which jointly solve several traffic-grooming subproblems by simply applying the shortest-path computation method. Different grooming policies can be represented by different weight-assignment functions, and the performance of these grooming policies are compared under both nonblocking scenario and blocking scenario. The IGABAG can be applied to both static and dynamic traffic grooming. In static grooming, the traffic-selection scheme is key to achieving good network performance. We propose several traffic-selection schemes based on this model and we evaluate their performance for different network topologies. The throughput of wireless networks can be significantly improved by multi-channel communications compared with single-channel communications since the use of multiple channels can reduce interference influence. In this paper, we study interference-aware topology control and QoS routing in IEEE 802.11-based multi-channel wireless mesh networks with dynamic traffic. Channel assignment and routing are two basic issues in such networks. Different channel assignments can lead to different network topologies. We present a novel definition of co-channel interference. Based on this concept, we formally define and present an effective heuristic for the minimum INterference Survivable Topology Control (INSTC) problem which seeks a channel assignment for the given network such that the induced network topology is interference-minimum among all K-connected topologies. We then formulate the Bandwidth-Aware Routing (BAR) problem for a given network topology, which seeks routes for QoS connection requests with bandwidth requirements. We present a polynomial time optimal algorithm to solve the BAR problem under the assumption that traffic demands are splittable. For the non-splittable case, we present a maximum bottleneck capacity path routing heuristic. Simulation results show that compared with the simple common channel assignment and shortest path routing approach, our scheme improves the system performance by 57 on average in terms of connection blocking ratio.