Generalized Multi-Constrained Path (G_MCP) QoS Routing Algorithm for Mobile Ad hoc Networks

Abstract

In mobile ad hoc network, efficient routing protocol is required to perform route discovery and maintenance. These protocols can be classified into two main types which are proactive and reactive routing protocols. Most of them usually use the suboptimal path to reach destination without considering QoS parameters. This results in network congestion during high traffic load situation. Hence, many algorithms have been proposed to offer QoS routing to these protocols. However, most of them find the feasible path by using only one or two QoS metrics. This is not enough to support many applications with QoS guaranteed, especially multimedia applications since they have more stringent various QoS requirements. To provide QoS routing in ad hoc network based on such environment, we propose the effective algorithm called Generalized MCP (G_MCP) to find the feasible path based on proposed weighted Connectivity Index (combination of link connectivity and capacity) and non-linear cost (combination of multiple additive QoS metrics using non-linear function). We adopt the fall-back approach. That is, G_MCP will find the path from source to destination by considering weighted Connectivity Index first. If there is a tie, the path with least non-linear cost will be chosen. Based on this approach, G_MCP has the comparable time complexity with the Shortest-Widest Path algorithm. We construct the simulation in a number of scenarios based on proactive protocol called OLSR. According to the simulation results, it is obvious that G_MCP performances are superior than OLSR and Shortest-Widest Path algorithms in terms of throughput, packet delivery ratio, delay and success ratio. Therefore, it can be concluded that G_MCP is able to support various applications and be operated well in highly dynamic mobility environmen

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“…It is shown under its proposed method, terms of all evaluation metrics. In [15] routing in OLSR by considering weighted CI and multiple additive QoS. To verify that OLSR performs well for multimedia a routing protocols when delivering in MANET is carried out in, such as…”

“…To provide QoS, the bandwidth and delay are mainly considered in many previous works proposed in OLSR [11], [12]but they are not suitable in various scenarios where multiple QoS constraints are essential [23], [24]. The concept of Weighted Connectivity Index (CI) is firstly introduced in [13], then used to improve the OLSR performance later on [6], [8], [14], [15]. The detailed derivation of Weighted CI as well as the MPR selection method is described especially [6].…”

“…The detailed derivation of Weighted CI as well as the MPR selection method is described especially [6]. In [15], the non-additive metric such as Weighted CI and multiple additive QoS metrics in path computation method is considered. Recently, the framework called cross-layer design has proved that it can improve the performance of a wireless network, especially MANET [22], [25]~ [27].…”

“…This leads to more stable path between source and destination which can enhance the overall performance of OLSR as well as to reduce the overall power consumption of the network. Our proposed method is compared with standard OLSR [5], [10] and the modified OLSR proposed in [8], [13]- [15] in terms of Throughput, Packet Delivery Ratio (PDR), Average End-to-End (E2E) Delay, Control Overhead and the Average Total Power Consumption [31], [32]. In addition, the computational complexity of all three algorithms is also compared with each other.…”

Experimental performance analysis of topology control in mobile ad hoc networks based on local information no topology heuristic

“…With this highly dynamic and unstable network topology characteristic, network performance may be lower due to higher number of collisions/interferences in dense networks or frequent link break in sparse networks. Hence, many techniques have been proposed to improve performance in highly dynamic ad hoc networks [13,23,24,26]. Moreover, Topology Control is one of these techniques that has also been researched in decades to maintain network connectivity while reducing energy consumption to prolong/extend network lifetime.…”