QoS in Mobile Ad-Hoc Networks

Sra, Pushp; Chand, Satish

doi:10.1007/s11277-019-06162-y

Cited by 16 publications

(10 citation statements)

References 19 publications

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“…The Quality of Service (QoS) [27] is defined as a set of service requirements that needs to be guaranteed by the network while transporting a packet stream from a source to its destination. The network is expected to assure a set of measurable service attributes to users in terms of end-to-end performance, Power consumption and end to end delay which are more specific to mobile ad hoc networks [28,29]. Furthermore, our concern is to study the efficiency of LE-OLSR in terms of energy consumption and the network lifetime.…”

Section: Qos Metric Performances Evaluation For Le-olsr Within Different Energy Scenariosmentioning

confidence: 99%

LE-OLSR protocol performance evaluation in various energy conditionsof mobile Ad-hoc and sensor wireless networks

Belkheir¹,

Rouissat

Mokaddem

et al. 2020

IJEECS

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<p>A mobile Ad hoc and sensor wireless network commonly includes various mobile devices and sensors with limited resources. In such network, energy constraint and link stability are the most critical parameters to take into consideration when deploying routing mechanisms, to assure reliable communication between nodes.These requirements are due to the network scalability and the absence of a fixed infrastructure, which may cause a rapid depletion of the nodes batteries and leads onto network link breakages. LE-OLSR (Lifetime Enhancement - Optimized Link State Protocol) is a variant of the existing OLSR. This latter is widely used as routing protocol for mobile ad-hoc and wireless sensor networks. LE-OLSR implements a new load balancing algorithm; it takes into account energy constraints of a node when selecting routers, responsible for forwarding data packets over the entire network. The aim of our work is to study and simulate the LE-OLSR protocol behavior in realistic mobile environments, including scenarios with various residual energy constraints schemes. The performed simulations had shown that LE-OLSR performances decrease compared to the case of ideal mobile network. Nevertheless, LE-OLSR had shown persistence and fair results in the realistic environment.The obtained results show that LE-OLSR protocol is an adequate and a prime solution for dense mobile ad hoc networks.</p>

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Section: Qos Metric Performances Evaluation For Le-olsr Within Different Energy Scenariosmentioning

confidence: 99%

LE-OLSR protocol performance evaluation in various energy conditionsof mobile Ad-hoc and sensor wireless networks

Belkheir¹,

Rouissat

Mokaddem

et al. 2020

IJEECS

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show abstract

“…MANETs are often deployed in a range of domains, such as disaster rescue, graphics and healthcare and defensive systems [1]. A maximum QoS is required for MANETs because they endure external and internal problems such as connection failure, topology changes and energy depletion [2][3][4][5][6][7]. So, it is critical to explore and develop unique routing protocols for MANETs.…”

Section: Introductionmentioning

confidence: 99%

Topology Change Aware on Demand Routing Protocol for Improving Reliability and Stability of MANET

2022

IJIES

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In mobile adhoc networks (MANETs), the most essential problem is to ensure the quality-of-service (QoS) during data transmission via multiple paths from a source to the destination node. To tackle this problem, a topological change adaptive adhoc on-demand multipath distance vector (TA-AOMDV) routing protocol was developed, which ensures QoS according to the different parameters for high-speed node mobility. But, it did not consider the path stability related to the node density, which also affects the routing efficiency. Hence, this paper develops a reliable and stable TA-AOMDV (RSTA-AOMDV) routing protocol that applies a new forwarding strategy to enhance the path reliability and stability for data transmission. In this protocol, every origin node relays data packets to the target in a hop-by-hop manner depending on local information gathered from its one-hop adjacent during the forwarding phase. Also, two different metrics are considered: (i) destination region selection (DRS) and (ii) weighted closeness and connectivity (WCC) to find the stable path from the source to the destination node. During the adjacent finding phase, a forwarding node self-selection mechanism is introduced to reduce the communication overhead due to the high node density and severe congestion. Finally, this protocol is simulated for 2 different cases: (1) a varying node mobility and (2) varying number of nodes. In the case of high-speed node mobility, i.e. 50m/s, the RSTA-AOMDV protocol achieves a 50.7 % packet delivery ratio (PDR), 109.4ms end-toend delay (E2E-D), 158.51Kbps throughput, 73.4 % normalized routing overhead (NRO) and 11J mean energy consumption (MEC) compared to other existing protocols. Similarly, in the case of high node densities, i.e. when the number of nodes is 100, the RSTA-AOMDV protocol achieves a 66.5 % PDR, 1485.74ms mean E2E-D, 639.7Kbps throughput, 15 % NRO and 22.7J MEC compared to the existing protocols.

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“…Random node mobility and the unreliability of wireless medium makes routing in MANETs even more difficult. Most of the existing routing protocols make only the best effort to find the shortest route for transmission through solving these problems separately without considering various parameters of QoS performance [10].…”

Section: Introductionmentioning

confidence: 99%

Multipath Routing Protocol Using Genetic Algorithm in Mobile Ad Hoc Networks

Bhardwaj

El-Ocla

2020

IEEE Access

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Mobile ad hoc network (MANET) is a cluster of wireless mobile gadgets that creates a temporary network without seeking support from any infrastructure or central management. Energy consumption should be considered as one of the foremost vital limitations in MANETs because the mobile nodes do not possess a constant power supply and its shortage will minimize the network's lifetime. MANETs get energy from the batteries which get exhausted very quickly because of issues like node mobility, computation power, frequent data retransmissions needed in wireless communication, etc. Secondly, there is a data packet loss caused by different reasons such as traffic congestion or random loss as a result of nodes mobility or noise. This data loss, in turn, would delay packets delivery degrading data transmission in real-time applications. This paper provides management for this combination of major problems in MANETs. We present a new fitness function (FFn) used in the Genetic Algorithm (GA) to obtain the optimized route from those routes offered by the Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol. Accordingly, we propose a routing protocol titled as AOMDV with FFn (AOMDV-FFn). We also integrate the AOMDV mechanism with the genetic algorithm (AOMDV-GA). These protocols provide an optimization process to select the efficient routes that have the highest fitness values implementing the shortest route, maximum residual energy, and less data traffic even if a random loss of data packets happens. In this regard, we introduce a mechanism where the TCP Congestion Control Enhancement for Random Loss (TCP CERL) can be utilized in the FFn to optimize the efficient route. The performance of the proposed mechanisms is compared with other preferred protocols proposed in this area. INDEX TERMS congestion control, energy-efficient protocol, fitness function, genetic algorithm, mobile ad hoc network, multipath routing, shortest distance.

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QoS in Mobile Ad-Hoc Networks

Cited by 16 publications

References 19 publications

LE-OLSR protocol performance evaluation in various energy conditionsof mobile Ad-hoc and sensor wireless networks

LE-OLSR protocol performance evaluation in various energy conditionsof mobile Ad-hoc and sensor wireless networks

Topology Change Aware on Demand Routing Protocol for Improving Reliability and Stability of MANET

Multipath Routing Protocol Using Genetic Algorithm in Mobile Ad Hoc Networks

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