Essam Natsheh

Adaptive and fuzzy approaches for nodes affinity management in wireless ad-hoc networks

In most of the ad-hoc routing protocols, a static link lifetime (LL) is used for a newly discovered neighbors. Though this works well for networks with fixed infrastructures, it is inadequate for ad-hoc networks due to nodes mobility and frequent breaks of links. To overcome this problem, routing protocols with estimated LL using nodes affinity were introduced. However, these protocols also used the static estimated LL during the connection time. In contrast to that, in this paper two methods are presented to estimate LL based on nodes affinity and then continually update those values depending on changes of the affinity. In the first method, linear function is used to map the relationship between the signal strength fluctuation and LL. In the second method, fuzzy logic system is used to map this relationship in a nonlinear fashion. Significance of the proposed methods is validated using simulation. Results indicate that fuzzy method provides the most efficient and robust LL values for routing protocols.

A Survey on Fuzzy Reasoning Applications for Routing Protocols in Wireless Ad Hoc Networks

Mobile wireless ad-hoc networks are networks without infrastructure, where every node works as a router. In these networks, every node must discover its local neighbors and through those neighbors it will communicate to nodes that are out of its transmission range (multi-hop routing). These networks suffer from all kinds of uncertainty, randomness and fuzziness. This uncertainty is due to high bit error rate (BER) in the wireless channel, increased collisions due to the presence of hidden terminals, signals interference and attenuation, location dependent connection, uni-directional links, and frequent link breaks due to nodes mobility. This emerges the need AbsTRACT

Fuzzy Reasoning Approach for Local Connectivity Management in Mobile Ad Hoc Networks

Routing is an important functional aspect in wireless ad hoc networks that handles discovering and maintaining the paths between nodes within a network. Due to nodes’ mobility, the efficiency of a dynamic ad hoc routing protocol depends highly on updating speed of network topology changes. To achieve continuous updated routing tables, the nodes periodically broadcast short Hello messages to their neighbors. Although benefits of these messages have been proven, many studies show some drawbacks for these messages. In this paper, we adaptively optimize the frequent needs of those messages using a fuzzy logic system. The proposed fuzzy algorithm is used to model the uncertainty measurements for updating local connectivity successfully in time. Extensive performance analysis via simulation proves the effectiveness of the proposed method to improve the accuracy of neighborhood information and, hence, overall network performance.

Routing with a density-based probabilistic algorithm for mobile ad-hoc networks

Ad-hoc networks can operate even when there is a scarcity of network infrastructure. This research examines ad-hoc networks that have varying node densities. These environments can be found in areas struck by disasters to urban city environments. Mobile nodes would not distribute evenly in such environments. Instead, the nodes would likely concentrate around specific landmarks or areas such as public squares with a high number of pedestrians while connecting roads and highways that have a low density of mobile nodes. The main contribution was the integration of a density based probabilistic scheme on AODV to reduce incurred routing overheads and improve packet delivery without significantly affecting the throughput and end to end delays. The proposed AODV--P AODV--Probabilistic protocol was compared against the AODV and OLSR protocols via simulation. The evaluation was based on three different environments: a high density, a variable density and a sparse density. The study showed that the AODV--P had a 28% higher data throughput than AODV and a 42% higher data throughput than OLSR at the three environments. Other performance parameters also showed that AODV--P performed better than AODV or OLSR in sub-optimal network environments due to the improved link lifetimes and lower routing overheads.

Multivariate Fuzzy Analysis for Mobile Ad hoc Network Threat Detection

Detection of malicious, compromised and selfish node attacks is urgently needed to protect Mobile Ad hoc Networks (MANET) and their applications from failures. Once a MANET component is affected by a malicious, compromised or selfish node its operational state shifts from normal state to vulnerable state. Online monitoring mechanisms can collect important MANET network data that can be effectively used to detect abnormal behaviors caused by attacks. In this article we develop an online multivariate analysis algorithm to analyze the behavior of network resources and protocols to proactively detect MANET attacks. This algorithm is based on multivariate fuzzy analysis technique. We have validated the algorithm and demonstrated how it can effectively detect wellknown attacks such as Denial of Service in MANET.

Intelligent Reasoning Approach for Active Queue Management in Wireless Ad Hoc Networks

Mobile ad hoc network is a network without infrastructure where every node has its own protocols and services for powerful cooperation in the network. Every node also has the ability to handle the congestion in its queues during traffic overflow. Traditionally, this was done through DropTail policy where the node drops the incoming packets to its queues during overflow condition. Many studies showed that early dropping of incoming packet is an effective technique to avoid congestion and to minimize the packet latency. Such approach is known as Active Queue Management (AQM). In this article, an enhanced algorithm called fuzzy-AQM is suggested using a fuzzy logic system to achieve the benefits of AQM. Uncertainty associated with queue congestion estimation and lack of mathematical model for estimating the time to start dropping incoming packets makes the fuzzy-AQM algorithm the best choice. Extensive performance analysis via simulation showed the effectiveness of the proposed method for congestion detection and avoidance improving overall network performance.

Links Lifetime Estimation Based on Nodes Affinity in Wireless Ad-hoc Networks

In most of the ad-hoc routing protocols, a static link lifetime (LL) is used for a newly discovered neighbors. Though this works well for networks with fixed infrastructures, it is inadequate for ad-hoc networks due to nodes mobility and frequent breaks of links. To overcome this problem, routing protocols with estimated LL using nodes affinity were introduced. However, these protocols also used the static estimated LL during the connection time. In contrast to that, in this paper two methods are presented to estimate LL based on nodes affinity and then continually update those values depending on changes of the affinity. In the first method, linear function is used to map the relationship between the signal strength fluctuation and LL. In the second method, fuzzy logic system is used to map this relationship in a nonlinear fashion. Significance of the proposed methods is validated using simulation. Results indicate that fuzzy method provides the most efficient and robust LL values for routing protocols.

Effect of Nodes Mobility on Density-Based Probabilistic Routing Algorithm in Ad-hoc Networks

Density-based probabilistic routing algorithm (AODV–Probabilistic) has been introduced for mobile ad hoc networks. Under ideal settings, it has been proven to provide drastic performance improvement over AODV and OLSR routing protocols. In this paper, the authors study the effect of inaccurate location information caused by node mobility under a rich set of scenarios. They identify three different environments: a high density, a variable density and a sparse density. Simulation results show noticeable improvement under the three environments. Under the settings the authors examine, their proposed algorithm achieve up to 22% longer links lifetime than AODV and 45 percent longer links lifetime than OLSR at the three environments, on average, without incurring any additional routing overheads or intense computation.