2 research outputs found
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Intelligent based Packet Scheduling Scheme using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) Technology for 5G. Design and Investigation of Bandwidth Management Technique for Service-Aware Traffic Engineering using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) for 5G
Multi-Protocol Label Switching (MPLS) makes use of traffic engineering (TE)
techniques and a variety of protocols to establish pre-determined highly
efficient routes in Wide Area Network (WAN). Unlike IP networks in which
routing decision has to be made through header analysis on a hop-by-hop
basis, MPLS makes use of a short bit sequence that indicates the forwarding
equivalence class (FEC) of a packet and utilises a predefined routing table to
handle packets of a specific FEC type. Thus header analysis of packets is not
required, resulting in lower latency. In addition, packets of similar
characteristics can be routed in a consistent manner. For example, packets
carrying real-time information can be routed to low latency paths across the
networks. Thus the key success to MPLS is to efficiently control and distribute
the bandwidth available between applications across the networks.
A lot of research effort on bandwidth management in MPLS networks has
already been devoted in the past. However, with the imminent roll out of 5G,
MPLS is seen as a key technology for mobile backhaul. To cope with the 5G
demands of rich, context aware and multimedia-based user applications, more
efficient bandwidth management solutions need to be derived.
This thesis focuses on the design of bandwidth management algorithms, more
specifically QoS scheduling, in MPLS network for 5G mobile backhaul. The
aim is to ensure the reliability and the speed of packet transfer across the
network. As 5G is expected to greatly improve the user experience with
innovative and high quality services, users’ perceived quality of service (QoS)
needs to be taken into account when deriving such bandwidth management
solutions. QoS expectation from users are often subjective and vague. Thus
this thesis proposes the use of fuzzy logic based solution to provide service aware and user-centric bandwidth management in order to satisfy
requirements imposed by the network and users.
Unfortunately, the disadvantage of fuzzy logic is scalability since dependable
fuzzy rules and membership functions increase when the complexity of being
modelled increases. To resolve this issue, this thesis proposes the use of neuro-fuzzy to solicit interpretable IF-THEN rules.The algorithms are
implemented and tested through NS2 and Matlab simulations. The
performance of the algorithms are evaluated and compared with other
conventional algorithms in terms of average throughput, delay, reliability, cost,
packet loss ratio, and utilization rate.
Simulation results show that the neuro-fuzzy based algorithm perform better
than fuzzy and other conventional packet scheduling algorithms using IP and
IP over MPLS technologies.Tertiary Education Trust Fund (TETFUND
Enabling large scale cloud services by software defined wide area network
Interconnecting data centers (DCs) efficiently and using the fully available capacity of existing resources in Wide Area Network (WAN) seems to be one of the most challenging issues for service providers (SPs). In this master memory, we investigate a new approach to optimize traffic engineering in WAN which interconnects DCs (Inter-DC WAN) using Software Defined Networking (SDN). We propose a model to optimize bandwidth allocation to flows belonging at different Classes of Services (CoS) according to their priority and the current network state. The proposed model aims to maximize the throughput in the network and to minimize the overall energy consumption. The proposed model takes into account inter-domain communication and respects underlying technology specifications such as Multi-Protocol Label Switching (MPLS).
To build our model, we consider four mathematical expressions for energy consumption of the topology nodes and links namely: the idle, the fully proportional, the agnostic and the step increasing models, and we adopt the MPLS model for Inter-DC WAN. We propose a deterministic algorithm to solve the optimization problem using Linear Programming (LP) solvers and we compare its performances with two existing models: Microsoft solutions’ SWAN which focuses on throughput maximization, and a base line model which aims to minimize energy consumption while allocating bandwidth to different flows. Experiments in the simulation environment show that the proposed solution can optimally exploit available physical capacity in the network to afford users demand in terms of bandwidth and uses the minimum energy to carry traffic. The proposed optimization model is NP-hard, so we propose a greedy heuristic to improve the runtime of the proposed solution