Performance evaluation of shortest multipath source routing scheme

Multipath routing in mobile ad-hoc networks allows the establishment of multiple paths for routing between a source-destination pair. It exploits the resource redundancy and diversity in the underlying network to provide benefits such as fault tolerance, load balancing, bandwidth aggregation and the improvement in quality-of-service metrics such as delay. Previous work shows that on-demand multipath routing schemes achieve better performance under certain scenarios with respect to a number of key performance metrics when compared with traditional single-path routing mechanisms. A multipath routing scheme, referred to as shortest multipath source (SMS) routing based on dynamic source routing (DSR) is proposed here. The mechanism has two novel aspects compared with other on-demand multipath routing schemes: it achieves shorter multiple partial-disjoint paths and allows more rapid recovery from route breaks. The performance differentials are investigated using NS-2 under conditions of varying mobility, offered load and network size. Results reveal that SMS provides a better solution than existing source-based approaches in a truly mobile ad-hoc environment.     

一种新的基于移动预测的MANET路由协议

移动自组网是一种由一系列可以自由移动的节点主机聚集而成的一个临时性动态网络。它没有固定基站，也没有作为控制管理中心的节点主机，由于其拓扑的动态性，其路由协议与其他传统网络有很大的区别。为了能更有效地移动自组网中实现数据的传送，本文提出了一种基于移动预测下的MANET路由协议，该协议综合考虑了传输路径的延时和稳定性，选择在延时限制下平均拥有最稳特性的传输路径，模拟结果表明，这种方法比基于移动预测量稳路径路由协议的传输时延要短，传送成功概率要高，而控制开销却相关不大。     

Genetic algorithm quality of service design in resilient dense wavelength division multiplexing optical networks

The important role of quality of service (QoS) in deployment of a resilient dense wavelength division multiplexing (DWDM) backbone for global networks requires critical design-phase planning optimisation. The design issues of resilient DWDM networks for bandwidth and delay sensitive applications of dedicated path protection are addressed. A genetic algorithm (GA) model has been developed to solve the routing and wavelength assignment problem using binary variable-length chromosome encoding under two different schemes of bandwidth optimisation (BOS) and delay optimisation (DOS).The performance of the new GA-based resiliency model has been evaluated for four benchmark networks: PAN EUROPEAN, COST239, NSFNETand ARPA2. Simulation results show a superior capability and efficiency for the model to solve this complex, multi-constraint and nondeterministic polynomial-hard problem for BOS and DOS. The nonlinear nature of this process reveals a significant sensitivity for optical layer network topology on the optimum-design QoS. The results also demonstrate that the PAN EUROPEAN network shows the highest flexibility for primary path design, NSFNET for the secondary path and ARPA2 comes with the lowest design flexibility for both primary and secondary paths.     

DQN-Based Proactive Trajectory Planning of UAVs in Multi-Access Edge Computing

The main aim of future mobile networks is to provide secure, reliable, intelligent, and seamless connectivity. It also enables mobile network operators to ensure their customer’s a better quality of service (QoS). Nowadays, Unmanned Aerial Vehicles (UAVs) are a significant part of the mobile network due to their continuously growing use in various applications. For better coverage, cost-effective, and seamless service connectivity and provisioning, UAVs have emerged as the best choice for telco operators. UAVs can be used as flying base stations, edge servers, and relay nodes in mobile networks. On the other side, Multi-access Edge Computing (MEC) technology also emerged in the 5G network to provide a better quality of experience (QoE) to users with different QoS requirements. However, UAVs in a mobile network for coverage enhancement and better QoS face several challenges such as trajectory designing, path planning, optimization, QoS assurance, mobility management, etc. The efficient and proactive path planning and optimization in a highly dynamic environment containing buildings and obstacles are challenging. So, an automated Artificial Intelligence (AI) enabled QoS-aware solution is needed for trajectory planning and optimization. Therefore, this work introduces a well-designed AI and MEC-enabled architecture for a UAVs-assisted future network. It has an efficient Deep Reinforcement Learning (DRL) algorithm for real-time and proactive trajectory planning and optimization. It also fulfills QoS-aware service provisioning. A greedy-policy approach is used to maximize the long-term reward for serving more users with QoS. Simulation results reveal the superiority of the proposed DRL mechanism for energy-efficient and QoS-aware trajectory planning over the existing models.     

Load balancing in the provisioning of hose model virtual private networks with multi-path routing

Load balancing in the provisioning of virtual private network (VPN) service in the hose model is studied. Single-path routing and tree routing for the hose model tend to aggregate bandwidth reservations on a small number of links, thus leading to congestion problems in service provider networks. If the link capacity is depleted as a result of improper routing, all future non-VPN traffic will be blocked. We propose a novel multi-objective multi-path (MOMP) routing linear program with the maximum fraction of traffic on a path (MFTP) constraint to solve the problem. The MOMP routing algorithm is able to reduce the bandwidth reservation on the most loaded link by as much as 50%, thus effectively alleviating the potential congestion problems in service provider network. The MFTP constraint provides a guarantee of the availability of multiple paths for each VPN endpoint pair. Further reduction of the bandwidth reservation can be achieved depending on the MFTP value. This is highly significant.     

Fair scheduling with rate control for IEEE 802.16 broadband wireless networks

Although the scheduling problem of the uplink transmission in the IEEE 802.16 broadband wireless access network is extensively discussed, most of the results are limited to the quality of service (QoS) upon throughput and delay requirement. But as in practice only limited wireless resources are made available, a fairness-based scheduling upon each connection?s QoS provides better outcomes. In this study, the authors propose a new fair uplink scheduling for real-time polling service and non-real-time polling service with the proportional sharing of excess bandwidth of the network. To implement the proposed fair scheduling that satisfies the delay requirement and full bandwidth utilisation, the authors introduce the rate control algorithm. With the proposed scheduling, we guarantee the fairness, delay requirement and full bandwidth utilisation which are not fully achieved in the existing results.     

A comparative QoS survey of mobile ad hoc network routing protocols

A mobile ad hoc network (MANET) is a wireless, dynamic, infrastructure-less, self-organized, multi-hop, and decentralized network. Each node in MANET can act as a router as well as a work station. Many routing protocols have been developed to increase the efficiency of MANET. The primary objective of this paper is a detailed QoS comparison of reactive (AODV), proactive (DSDV), and hybrid (ZRP) routing protocols of MANET in order to find which routing protocol works best in a particular network scenario. The analysis was made for TCP-based traffic patterns. The performance differentials were analyzed on the basis of normalized routing overhead, packet loss, packet delivery ratio, control packets, end-to-end delay, packet received, and packet sent with a variation of nodes density and mobility. The results were obtained using the NS-2 simulator.     

An Efficient Greedy Traffic Aware Routing Scheme for Internet of Vehicles

A new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all connected vehicles to communicate with each other and/or with a central server, through other vehicles. Vehicle to Vehicle (V2V) communication is the main component, because the services encompassed in the IoV are based on the vehicles in question, such as transmitter, relay and receiver. This work is focusing on designing and developing a Quality of Service (QoS) routing scheme dedicated to IoV networks. Especially, we aim to improve the Greedy Traffic Aware Routing (GyTAR) protocol to support QoS in IoV networks. To evaluate the proposed approach in terms of QoS in the context of IoV networks, the performance metrics such as average end-to-end delay and packet delivery ratio are taken into consideration to analyse the network situation.     

基于代理的QoS组播路由算法

提出了一种基于代理（Agent)的QoS组播路由算法,它根据一个在网络中漫游的移动代理收集的网络状态来建立保证QoS的组播树,仿真实验表明,该算法是有效的和可行的。     

Q-Learning Based Routing Protocol for Congestion Avoidance

The end-to-end delay in a wired network is strongly dependent on congestion on intermediate nodes. Among lots of feasible approaches to avoid congestion efficiently, congestion-aware routing protocols tend to search for an uncongested path toward the destination through rule-based approaches in reactive/incident-driven and distributed methods. However, these previous approaches have a problem accommodating the changing network environments in autonomous and self-adaptive operations dynamically. To overcome this drawback, we present a new congestion-aware routing protocol based on a Q-learning algorithm in software-defined networks where logically centralized network operation enables intelligent control and management of network resources. In a proposed routing protocol, either one of uncongested neighboring nodes are randomly selected as next hop to distribute traffic load to multiple paths or Q-learning algorithm is applied to decide the next hop by modeling the state, Q-value, and reward function to set the desired path toward the destination. A new reward function that consists of a buffer occupancy, link reliability and hop count is considered. Moreover, look ahead algorithm is employed to update the Q-value with values within two hops simultaneously. This approach leads to a decision of the optimal next hop by taking congestion status in two hops into account, accordingly. Finally, the simulation results presented approximately 20% higher packet delivery ratio and 15% shorter end-to-end delay, compared to those with the existing scheme by avoiding congestion adaptively.     

一种基于多播路由图的最小子树图搜索算法

提出了一种基于网络编码的新的多播路由算法,该算法在搜索信源节点到各接收者路径族的过程中,考虑了不同路径族之间链路的共享,以降低带宽资源消耗,提高网络性能.基于得到的多播路由图,提出了一种最小子树图搜索算法,并利用最小子树图的性质,对相应于多播路由图的子树图进行化简.最后,在最小子树图上进行有效的网络编码,所有的网络编码问题可以简化为搜索多播网络的最小子树图问题.     

Traffic scheduling for multimedia transmission over IEEE 802.11e wireless LAN

As the demand for broadband multimedia wireless is increasing, improving the quality of service (QoS) of the widely deployed IEEE 802.11 wireless LAN has become crucial. In order to attain the QoS required by a wide range of applications, the IEEE 802.11 working group has denned a new standard - the IEEE 802.lie. However, very limited work has been performed to address the QoS transmission problem of real-time video over IEEE 802.11e. A novel measurement-based dynamic transmission opportunity (MBDTXOP) scheme is proposed, which adaptively allocates resources to a variable bit rate (VBR) video on the basis of the estimation of future traffic demand to support efficient QoS transmission of VBR video. The novelty of the proposed scheme, when compared with existing methods, lies in estimating the required network resources by exploiting the characteristics of digital video; this capability enables the MBDTXOP scheme to substantially increase network utilisation while preserving the required QoS for the transmission of VBR video. Simulations comparing the proposed scheme with other mechanisms clearly demonstrate the outstanding performance of the former.     

Flooding-limited for multi-constrained quality-of-service routing protocol in mobile ad hoc networks

Multi-constrained quality-of-service (QoS) routing is used to find routes in a network to satisfy multiple independent QoS constraints. This problem is considered to be NP-complete, and most existing QoS routing algorithms are based on maintaining a global network state at every node. A multi-constrained, flooding-limited, QoS routing method to deal with limited available resources and minimum computation in a dynamic environment is proposed. The solution is based on decomposition of a routing area and a restriction in the exchange of routing information. It reduces the size of the control messages, restricts the amount of routing information, minimises the overhead from the flooding of control traffic and decreases the complexity of path selection. It is also proved that the flooding-limited-path heuristic can achieve very high performance by maintaining entries in each node, which indicates that the performance of the limited-path heuristic is not sensitive to the number of constraints. Simulation results show that this protocol provides better performance than other protocols, especially with regards to end-to-end delay, throughput and packet loss.     

An analytical solution based on mobility and multicriteria optimization for access selection in heterogeneous environment

Providing global connectivity with high speed and guaranteed quality at any place and any time is now becoming a reality due to the integration and co-ordination of different radio access technologies. The internetworking of existing networks with diverse characteristics has been considered attractive to meet the incredible development of interactive multimedia services and ever-growing demands of mobile users. Due to the diverse characteristics of heterogeneous networks, several challenges have to be addressed in terms of quality of service (QoS), mobility management and user preferences. To achieve this goal, an optimal network selection algorithm is needed to select the target network for maximizing the end user satisfaction. The existing works do not consider the integration of utility function with mobile terminal mobility characteristics to minimize ping-pong effects in the integrated networks. An integrated multicriteria network selection algorithm based on multiplicative utility function and residual residence time (RRT) estimation is proposed to keep the mobile users always best connected. Multiplicative weighted utility function considers network conditions, application QoS and user preferences to evaluate the available networks. In this paper, the proposed scheme is implemented with two mainstreams (pedestrian users and high-velocity users). For high-velocity users, RRT and adaptive residence time threshold are also considered to keep the probability of handover failures and unnecessary handovers within the limits. Monte-Carlo simulation results demonstrate that the proposed scheme outperforms against existing approaches.     

HELP-WSN-A Novel Adaptive Multi-Tier Hybrid Intelligent Framework for QoS Aware WSN-IoT Networks

Wireless Sensor Network is considered as the intermediate layer in the paradigm of Internet of things (IoT) and its effectiveness depends on the mode of deployment without sacrificing the performance and energy efficiency. WSN provides ubiquitous access to location, the status of different entities of the environment and data acquisition for long term IoT monitoring. Achieving the high performance of the WSN-IoT network remains to be a real challenge since the deployment of these networks in the large area consumes more power which in turn degrades the performance of the networks. So, developing the robust and QoS (quality of services) aware energy-efficient routing protocol for WSN assisted IoT devices needs its brighter light of research to enhance the network lifetime. This paper proposed a Hybrid Energy Efficient Learning Protocol (HELP). The proposed protocol leverages the multi-tier adaptive framework to minimize energy consumption. HELP works in a two-tier mechanism in which it integrates the powerful Extreme Learning Machines for clustering framework and employs the zonal based optimization technique which works on hybrid Whale-dragonfly algorithms to achieve high QoS parameters. The proposed framework uses the sub-area division algorithm to divide the network area into different zones. Extreme learning machines (ELM) which are employed in this framework categories the Zone's Cluster Head (ZCH) based on distance and energy. After categorizing the zone's cluster head, the optimal routing path for an energy-efficient data transfer will be selected based on the new hybrid whale-swarm algorithms. The extensive simulations were carried out using OMNET++-Python user-defined plugins by injecting the dynamic mobility models in networks to make it a more realistic environment. Furthermore, the effectiveness of the proposed HELP is examined against the existing protocols such as LEACH, M-LEACH, SEP, EACRP and SEEP and results show the proposed framework has outperformed other techniques in terms of QoS parameters such as network lifetime, energy, latency.     

Network lifetime-aware data collection in Underwater Sensor Networks for delay-tolerant applications

Development of energy-efficient data collection and routing schemes for Underwater Wireless Sensor Networks (UWSNs) is a challenging issue due to the peculiarities of the underlying physical layer technology. Since the recharging or replacement of sensor nodes is almost impossible after deployment, the critical issue of network lifetime maximization must be considered right from the beginning of designing the routing schemes. We propose a mobile sink (MS)-based data collection scheme that can extend network lifetime, taking into account power-constrained sensor nodes, partitioned networks with geographically distant data collection points and periodic monitoring applications with delay-tolerance. Lifetime extension is achieved by mitigating the ‘sink neighbourhood problem’ and by deferring the data transmissions until the MS is at the most favourable location for data transfer. Unlike the models available for terrestrial WSNs, we consider non-zero travel time of the MS between data collection points, thus making our model more realistic for UWSNs, both connected and partitioned. The performance of the proposed mobility-assisted data collection scheme is thoroughly investigated using both analytical and simulation models. The analytical results are compared to those of existing models to assess their effectiveness and to investigate the trade-offs. Results show that, with a network size of 60 nodes, the network lifetime achieved by the proposed model is 188% higher than that of static sink model and 91% higher than that of mobile sink model (MSM). The proposed maximum lifetime routing scheme is implemented in the network simulation platform OMNET++, for validating the analytical results as well as for evaluating other performance metrics that are not tractable via analytical methods. Both analytical and simulation results demonstrate the superiority of the proposed model in capturing realistic network conditions and providing useful performance indicators prior to network deployment.     

一种支持多跳无线网QoS业务的MAC层接入协议

提供一定的服务质量保证(QoS)是多跳无线网络研究中的热点和难点,本文基于TDMA/FDMA机制提出了一种支持多信道多跳无线网络话音级QoS业务的MAC层接入协议RA/SRN。该协议以RBRP协议思想为基础,针对无线信道中隐藏、暴露终端造成的信道利用率降低和分组冲突问题进行改进设计,减小了信道冲突概率,提高了信道利用率,降低了信道接入时延,为网络层QoS路由协议提供了良好的支持。     

Multilayer flavoured dynamic source routing in mobile ad-hoc networks

Dynamic source routing (DSR, introduced in 1996) is one of the most frequently used routing protocols for mobile ad-hoc networks (MANETs). Numerous MANET protocols were created based on DSR's algorithm. In addition to inheriting the overall performance specifications of DSR, these MANET protocols are designed to perform optimised for specific functionality. To name a few, these functionalities include: hierarchical routing, security-aware routing and multipath routing. Such flavoured DSR schemes (X-DSR) are often compared against the original DSR protocol through simulation results. The purpose of this survey is to first introduce DSR in detail, discuss most of the DSR flavours, point out their specific features, and to present a complete survey of the analyses given in the current literature against the original DSR protocol. Following this in-depth discussion, we introduce an X-DSR-aware management architecture, which utilises a multilayer scheme that imports parameters from different layers (network, data-link and physical) and performs current network condition matching compared to the closest pre-defined network condition groups. The output of such a match is the selection of the most optimal routing protocol, which satisfies most of the criteria of the predefined condition group.     

Source selection routing algorithms in integrated cellular networks

Integrated cellular networks (ICNs) are normally constructed by adding ad hoc overlay on cellular networks to solve the latter's flexibility and capacity expansion problems. In such networks, routing plays a critical role in finding a route to divert congested traffic from a congested cell to another less crowded cell. Much work has been conducted on routing protocols in ICNs, whereas no dedicated work has been found for an important aspect of routing, namely source selection. The process of a source selection can be an algorithm that is designed for selecting a proper pseudo- source to release its occupying channel to a blocked mobile user. Consequently, this pseudo-source diverts its ongoing call to another cell by using a free channel in a neighbour cell via a relaying route. Based on an introduction of a representative ICN infrastructure, three source selection algorithms are proposed. Both numerical analysis and evaluation results are presented, which show the efficiency of the algorithms and their different abilities in adapting to different network situations, such as traffic density and cell capacity.     

Single Failure Routing Protection Algorithm in the Hybrid SDN Network

Loop free alternate (LFA) is a routing protection scheme that is currently deployed in commercial routers. However, LFA cannot handle all single network component failure scenarios in traditional networks. As Internet service providers have begun to deploy software defined network (SDN) technology, the Internet will be in a hybrid SDN network where traditional and SDN devices coexist for a long time. Therefore, this study aims to deploy the LFA scheme in hybrid SDN network architecture to handle all possible single network component failure scenarios. First, the deployment of LFA scheme in a hybrid SDN network is described as a 0-1 integer linear programming (ILP) problem. Then, two greedy algorithms, namely, greedy algorithm for LFA based on hybrid SDN (GALFAHSDN) and improved greedy algorithm for LFA based on hybrid SDN (IGALFAHSDN), are proposed to solve the proposed problem. Finally, both algorithms are tested in the simulation environment and the real platform. Experiment results show that GALFAHSDN and IGALFAHSDN can cope with all single network component failure scenarios when only a small number of nodes are upgraded to SDN nodes. The path stretch of the two algorithms is less than 1.36.