Multiprotocol Label Switching in Vehicular Ad hoc Network for QoS

Vehicular Ad hoc Networks (VANET) provides a wireless communication between vehicles. VANET applications play a significant role in the transportation sector such as vehicle safety, environmental efficiency, traffic control etc. Vehicular Ad hoc network is a subclass of Mobile Ad hoc networks. One of the main concerns in transportation is quality of service (QoS). In VANET, various solutions proposed for quality of services and these solutions applied on layer 2 and layer 3. In this paper, we proposed a Multiprotocol Label Switching. MPLS is an efficient and effective technique that forwards the packets across the network by using the contents of the labels attached to the IP packets. MPLS is known to be a layer 2.5 technology because it supports both data link layer or layer-2 and layer-3. The use of MPLS as backbone networks has increased over the past few years as compared to traditional IP networks, which were based on Iayer-2 technologies. MPLS is a forwarding method used for backbone network. In this paper, we improve quality of service in term of delay, packet loss and throughput in highway areas

Improving quality of service through road side back-bone network in VANET

The vehicular ad hoc Networks (VANETs) are expected to support a large spectrum of traffic alert, dynamic route planning, file sharing, safety and infotainment applications to improve traffic management. User satisfaction plus in time delivery of real-time messages is the most significant quality evaluation criterion for vehicular applications. High mobility and rapidly changing topologies always lead to intermittent quality of services, higher delay and packet dropping issues in network. To improve the quality of services for multi-hop and dynamic environment, different types of solutions have been proposed. The article introduces multi-protocol label switching based on roadside backbone network to provide widespread, scalable, high-speed, robust quality of services and improve network efficiency. The simulation results showed that proposed model improves data transmission and routing performance in terms of data delivery, throughput, end-to-end delay and achieve adequate utilization of resources

Mobile Networks

The growth in the use of mobile networks has come mainly with the third generation systems and voice traffic. With the current third generation and the arrival of the 4G, the number of mobile users in the world will exceed the number of landlines users. Audio and video streaming have had a significant increase, parallel to the requirements of bandwidth and quality of service demanded by those applications. Mobile networks require that the applications and protocols that have worked successfully in fixed networks can be used with the same level of quality in mobile scenarios. Until the third generation of mobile networks, the need to ensure reliable handovers was still an important issue. On the eve of a new generation of access networks (4G) and increased connectivity between networks of different characteristics commonly called hybrid (satellite, ad-hoc, sensors, wired, WIMAX, LAN, etc.), it is necessary to transfer mechanisms of mobility to future generations of networks. In order to achieve this, it is essential to carry out a comprehensive evaluation of the performance of current protocols and the diverse topologies to suit the new mobility conditions

Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts

Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resource planning and forecasting are essential steps for resource allocation. This study proposes a reliable hybrid dynamic bandwidth slice forecasting framework that combines the long short-term memory (LSTM) neural network and local smoothing methods to improve the network forecasting model. Moreover, the proposed framework can dynamically react to all the changes occurring in the data series. Backbone traffic was used to validate the proposed method. As a result, the forecasting accuracy improved significantly with the proposed framework and with minimal data loss from the smoothing process. The results showed that the hybrid moving average LSTM (MLSTM) achieved the most remarkable improvement in the training and testing forecasts, with 28% and 24% for long-term evolution (LTE) time series and with 35% and 32% for the multiprotocol label switching (MPLS) time series, respectively, while robust locally weighted scatter plot smoothing and LSTM (RLWLSTM) achieved the most significant improvement for upstream traffic with 45%; moreover, the dynamic learning framework achieved improvement percentages that can reach up to 100%

Simulation and Evaluation of Wired and Wireless Networks with NS2, NS3 and OMNET++

Communication systems are emerging rapidly with the revolutionary growth in terms of networking protocols, wired and wireless technologies, user applications and other IEEE standards. Numbers of industrial as well as academic organizations around the globe are bringing in light new innovations and ideas in the field of communication systems. These innovations and ideas require intense evaluation at initial phases of development with the use of real systems in place. Usually the real systems are expensive and not affordable for the evaluation. In this case, network simulators provide a complete cost-effective testbed for the simulation and evaluation of the underlined innovations and ideas. In past, numerous studies were conducted for the performance evaluation of network simulators based on CPU and memory utilization. However, performance evaluation based on other metrics such as congestion window, throughput, delay, packet delivery ratio and packet loss ratio was not conducted intensively. In this thesis, network simulators such as NS2, NS3 and OMNET++ will be evaluated and compared for wired and wireless networks based on congestion window, throughput, delay, packet delivery and packet loss ratio. In the theoretical part, information will be provided about the wired and wireless networks and mathematical interpretation of various components used for these networks. Furthermore, technical details about the network simulators will be presented including architectural design, programming languages and platform libraries. Advantages and disadvantages of these network simulators will also be highlighted. In the last part, the details about the experiments and analysis conducted for wired and wireless networks will be provided. At the end, findings will be concluded and future prospects of the study will be advised.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Review of Path Selection Algorithms with Link Quality and Critical Switch Aware for Heterogeneous Traffic in SDN

Software Defined Networking (SDN) introduced network management flexibility that eludes traditional network architecture. Nevertheless, the pervasive demand for various cloud computing services with different levels of Quality of Service requirements in our contemporary world made network service provisioning challenging. One of these challenges is path selection (PS) for routing heterogeneous traffic with end-to-end quality of service support specific to each traffic class. The challenge had gotten the research community\u27s attention to the extent that many PSAs were proposed. However, a gap still exists that calls for further study. This paper reviews the existing PSA and the Baseline Shortest Path Algorithms (BSPA) upon which many relevant PSA(s) are built to help identify these gaps. The paper categorizes the PSAs into four, based on their path selection criteria, (1) PSAs that use static or dynamic link quality to guide PSD, (2) PSAs that consider the criticality of switch in terms of an update operation, FlowTable limitation or port capacity to guide PSD, (3) PSAs that consider flow variabilities to guide PSD and (4) The PSAs that use ML optimization in their PSD. We then reviewed and compared the techniques\u27 design in each category against the identified SDN PSA design objectives, solution approach, BSPA, and validation approaches. Finally, the paper recommends directions for further research