Performance Improvement of AODV in Wireless Networks using Reinforcement Learning Algorithms

This paper investigates the application of reinforcement learning (RL) techniques to enhance the performance of the Ad hoc On-Demand Distance Vector (AODV) routing protocol in mobile ad hoc networks (MANETs). MANETs are self-configuring networks consisting of mobile nodes that communicate without the need for a centralized infrastructure. AODV is a widely used routing protocol in MANETs due to its reactive nature, which reduces overhead and conserves energy. This research explores three popular Reinforcement Learning algorithms: SARSA, Q-Learning and Deep Q-Network (DQN) to optimize the AODV protocol's routing decisions. The RL agents are trained to learn the optimal routing paths by interacting with the network environment, considering factors such as link quality, node mobility, and traffic load. The experiments are conducted using network simulators to evaluate the performance improvements achieved by the proposed RL-based enhancements. The results demonstrate significant enhancements in various performance metrics, including reduced end-to-end delay, increased packet delivery ratio, and improved throughput. Furthermore, the RL-based approaches exhibit adaptability to dynamic network conditions, ensuring efficient routing even in highly mobile and unpredictable MANET scenarios. This study offers valuable insights into harnessing RL techniques for improving the efficiency and reliability of routing protocols in mobile ad hoc networks

MPR+SP: Towards a Unified MPR-based MANET Extension for OSPF

International audienceHeterogeneous networks and wireless components - fixed routers as well as mobile routers - emerge as wireless mesh networks are being deployed. Such heterogeneity is bound to become more and more present in the near future as mobile ad hoc networking becomes a reality. While it is possible to cope with heterogeneity by employing different routing protocols for the fixed / wired part and for the wireless / ad hoc part of the network, this may lead to sub-optimal performance, e.g. by way of longer routing paths due to these routing protocols sharing prefixes and "connecting" the network only at distinct gateways between the two routing domains. Thus, the establishment of a single unified routing domain, and the use of a single routing protocol, for such heterogeneous networks is desired. OSPF is a natural candidate for this task, due to its wide deployment, its modularity and its similarity with the popular ad hoc routing protocol OLSR. Multiple OSPF extensions for MANETs have therefore been specified by the IETF. This paper introduces a novel OSPF extension for operation on ad hoc networks, MPR+SP, and compares it with the existing OSPF extensions via simulations, which show that MPR+SP outperforms prior art

Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks

Vehicular Ad Hoc Network (VANET) is an emerging area of wireless ad hoc networks that facilitates ubiquitous connectivity between smart vehicles through Vehicle-to-Vehicle (V2V) or Vehicle-to-Roadside (V2R) and Roadside-to- Vehicle (R2V) communications. This emerging field of technology aims to improve safety of passengers and traffic flow, reduces pollution to the environment and enables in-vehicle entertainment applications. The safety-related applications could reduce accidents by providing drivers with traffic information such as collision avoidances, traffic flow alarms and road surface conditions. Moreover, the passengers could exploit an available infrastructure in order to connect to the internet for infomobility and entertainment applications.Lloret, J.; Ghafoor, KZ.; Rawat, DB.; Xia, F. (2013). Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks. Mobile Networks and Applications. 18(6):749-754. doi:10.1007/s11036-013-0490-7S749754186Lloret J, Canovas A, Catalá A, Garcia M (2013) Group-based protocol and mobility model for VANETs to offer internet access. J Netw Comput Appl 36(3):1027–1038. doi: 10.1016/j.jnca.2012.02.009Khokhar RH, Zia T, Ghafoor KZ, Lloret J, Shiraz M (2013) Realistic and efficient radio propagation model for V2X communications. KSII Trans Internet Inform Syst 7(8):1933–1953. doi: 10.3837/tiis.2013.08.011Ghafoor KZ (2013) Routing protocols in vehicular ad hoc networks: survey and research challenges, Netw Protocol Algorithm 5(4). doi: 10.5296/npa.v5i4.4134Ghafoor KZ, Bakar KA, Lloret J, Ke C-H, Lee KC (2013) Intelligent beaconless geographical routing for urban vehicular environments. Wirel Netw 19(3):345–362. doi: 10.1007/s11276-012-0470-zGhafoor KZ, Bakar KA, Lee K, AL-Hashimi H (2010) A novel delay- and reliability- aware inter-vehicle routing protocol. Netw Protocol Algorithms 2(2):66–88. doi: 10.5296/npa.v2i2.427Dias JAFF, Rodrigues JJPC, Isento JN, Pereira PRBA, Lloret J (2011) Performance assessment of fragmentation mechanisms for vehicular delay-tolerant networks. EURASIP J Wirel Commun Netw 2011(195):1–14. doi: 10.1186/1687-1499-2011-195Zhang D, Yang Z, Raychoudhury V, Chen Z, Lloret J (2013) An energy-efficient routing protocol using movement trend in vehicular Ad-hoc networks. Comput J 58(8):938–946. doi: 10.1093/comjnl/bxt028Ghafoor KZ, Lloret J, Bakar KA, Sadiq AS, Mussa SAB (2013) Beaconing approaches in vehicular Ad Hoc networks: a survey. Wirel Pers Commun. doi: 10.1007/s11277-013-1222-9Sadiq AS, Bakar KA, Ghafoor KZ, Lloret J (2013) An intelligent vertical handover scheme for audio and video streaming in heterogeneous vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0465-8Khamayseh YM (2013) Network size estimation in VANETs. Netw Protocol Algorithm 5(3):136–152. doi: 10.5296/npa.v5i6.3838Rawat DB, Popescu DC, Yan G, Olariu S (2011) Enhancing VANET performance by joint adaptation of transmission power and contention window size. IEEE Trans Parallel Distrib Syst 22(9):1528–1535Yan G, Rawat DB, Bista BB. Provisioning vehicular ad hoc networks with quality of services. Int J Space-Based Situated Comput 2(2):104–111Rawat DB, Bista BB, Yan G, Weigle MC (2011) Securing vehicular ad-hoc networks against malicious drivers: a probabilistic approach, International Conference on Complex, Intelligent, and Software Intensive Systems Pp. 146–151. June 30, 2011Sun W, Xia F, Ma J, Fu T, Sun Y. An optimal ODAM-based broadcast algorithm for vehicular Ad-Hoc Networks. KSII Trans Internet Inform Syst 6(12): 3257–3274Vinel AV, Dudin AN, Andreev SD, Xia F (2010) Performance modeling methodology of emergency dissemination algorithms for vehicular ad-hoc networks, 6th Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010), Pp. 397–400AL-Hashimi HN, Bakar KA, Ghafoor KZ (2010) Inter-domain proxy mobile IPv6 based vehicular network. Netw Protocol Algorithm 2(4):1–15. doi: 10.5296/npa.v2i4.488Ghafoor KZ, Bakar KA, Mohammed MA, Lloret J (2013) Vehicular cloud computing: trends and challenges, in the book “mobile computing over cloud: technologies, services, and applications”. IGI GlobalYan G, Rawat DB, Bista BB (2012) Towards secure vehicular clouds, Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2012), Pp. 370–375Fernández H, Rubio L, Reig J, Rodrigo-Peñarrocha VM, Valero A (2013) Path loss modeling for vehicular system performance and communication protocols evaluation. Mobile Netw Appl. doi: 10.1007/s11036-013-0463-xAllouche Y, Segal M (2013) A cluster-based beaconing approach in VANETs: near optimal topology via proximity information. Mobile Netw Appl. doi: 10.1007/s11036-013-0468-5Merah AF, Samarah S, Boukerche A, Mammeri A (2013) A sequential patterns data mining approach towards vehicular route prediction in VANETs. Mobile Netw Appl. doi: 10.1007/s11036-013-0459-6Zhang D, Huang H, Zhou J, Xia F, Chen Z (2013) Detecting hot road mobility of vehicular Ad Hoc Networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0467-6El Ajaltouni H, Boukerche A, Mammeri A (2013) A multichannel QoS MAC with dynamic transmit opportunity for. Mobile Netw Appl. doi: 10.1007/s11036-013-0475-6Reñé S, Esparza O, Alins J, Mata-Díaz J, Muñoz JL (2013) VSPLIT: a cross-layer architecture for V2I TCP services over. Mobile Netw Appl. doi: 10.1007/s11036-013-0473-8Blanco B, Liberal F (2013) Amaia Aguirregoitia, application of cognitive techniques to adaptive routing for VANETs in city environments. Mobile Netw Appl. doi: 10.1007/s11036-013-0466-7Kim J, Krunz M (2013) Spectrum-aware beaconless geographical routing protocol for cognitive radio enabled vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0476-5Dias JAFF, Rodrigues JJPC, Isento JNG, Niu J (2013) The impact of cooperative nodes on the performance of vehicular delay-tolerant networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0464-9Sadiq AS, Bakar KA, Ghafoor KZ, Lloret J, Khokhar R (2013) An intelligent vertical handover scheme for audio and video streaming in heterogeneous vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0465-8Machado S, Ozón J, González AJ, Ghafoor KZ (2013) Structured peer-to-peer real time video transmission over vehicular Ad Hoc networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0461-zLin C, Wu G, Xia F, Yao L (2013) Enhance the attacking efficiency of the node compromise attack in vehicular Ad-hoc network using connected dominating set. Mobile Netw Appl. doi: 10.1007/s11036-013-0469-

Optimal resource allocation for route selection in ad-hoc networks

Nowadays, the selection of the optimum path in mobile ad hoc networks (MANETS) is being an important issue that should be solved smartly. In this paper, an optimal path selection method is proposed for MANET using the Lagrange multiplier approach. The optimization problem considers the objective function of maximizing bit rate, under the constraints of minimizing the packet loss, and latency. The obtained simulation results show that the proposed Lagrange optimization of rate, delay, and packet loss algorithm (LORDP) improves the selection of optimal path in comparison to ad-hoc on-demand distance vector protocol (AODV). We increased the performance of the system by 10.6 Mbps for bit rate and 0.133 ms for latency

Comparative Analysis of MANET Reactive Protocols

an Ad - hoc network is a group of mobile nodes. In an ad - hoc network a mobile node can directly communicate with the other node that lies in its transmission range or it can forward its information to the other node that will act as an intermediate node and forwards the information to the desired node using multi - hop links. In such a network there is no need of any infrastructure. Ad - hoc networks routing protocols are classified into two categories: Proactive/table - driven and reactive/on - demand. Reactive rou ting protocol is used whenever a communication is requested. There are two types of reactive protocols: AODV (Ad hoc on - demand distance vector protocol) and DSR (Dynamic source routing protocol). In one type of scenario one protocol may perform best while another may perform worst, so there is a need to determine an optimal one out of these in a more dynamic environment. The differences in the working of these protocols lead to significant performance differentials for both of these protocol

Cluster-based route discovery protocol

An ad hoc network is a collection of wireless mobile hosts forming a network without the aid of any established infrastructure or centralized administration. In such an environment, it may be necessary for one mobile host to enlist the aid of other hosts in forwarding a packet to its destination due to the limited range of each mobile host\u27s wireless transmissions. Many protocols have been proposed to route packets between the hosts in such a network; The on-demand routing protocol is a well-known method. It establishes the routes and uses them only when a need arises. For wireless communication channels, the problem is further complicated by the mobility of the nodes, which induces structural changes in the routing. So, the mobility management of mobile nodes is important in mobile ad hoc networks; Clustering is a scheme to build a network control structure that increases network availability, reduces the delay in responding to changes in network state, and improves data security. It promotes more efficient use of resources in controlling large dynamic networks. Clustering is crucial for scalability as the performance can be improved by simply adding more nodes to the cluster; This thesis presents a protocol for routing in ad hoc networks that uses ad-hoc on-demand routing and also takes care of the mobility management. The protocol adapts quickly to frequent host movement, yet requires little or no overhead during periods in which hosts move less frequently. Moreover, the protocol routes packets through a dynamically established and nearly optimal path between two wireless nodes. We propose a self-organizing clustering protocol to store the routing data in multiple nodes and to distribute the routing load. It also achieves higher reliability---if a node in a cluster fails, the data is still accessible via other cluster nodes

A minimum-cost-neighbor multicast routing protocol for mobile wireless ad hoc networks

MiCoN (Minimum-Cost Neighbor) is a new on-demand multicast routing protocol for mobile wireless ad hoc networks. Multicast routing in MiCoN is based on a new multi-route unicast routing protocol for maintaining routes between the network nodes and all group receivers. This routing is guaranteed to be loop-free even in the presence of dropped packets in the wireless network. MiCoN packet forwarding is based on a new local approximation of the optimal multicast tree, achieved by modeling multicasting as a Facility-Location-Problem. Evaluated in ns-2 simulations. MiCoN outperforms ADMR, the previously best performing on-demand multicast routing protocol for mobile ad hoc networks. To support this evaluation, I have also developed a new simulation model for sparse movement scenarios in ad hoc networks. MiCoN achieves better performance than ADMR, in terms of its packet delivery ratio, latency, and overhead in dense scenarios, and substantially outperforms ADMR on these metrics in sparse networks