The performance of a Mobile Ad hoc Network (MANET) is closely related to the capability of the implemented routing protocol to adapt itself to unpredictable changes of topology network and link status. The Optimized Link State Routing (OLSR) protocol is a one key of the proactive routing protocols for MANETs. It is based on the multi-point relays (MPRs) technique to reach all nodes in the network with a limited number of broadcasts. In this paper, we propose new versions of the original OLSR protocol based on a new mobility parameter, in the goal to enhance and adapt it in the presence of the mobility. For this objective we define new three criterions for MPRs selection. The first criteria take for selection, just the mobility of nodes at one-hop. The two others criterions are based on both mobility of nodes at one-hop and two-hops

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Abstract-This paper introduces the original Mobile Intelligent System (MIS) in an embedded Field-Programmable Gate Array (FPGA) architecture. This would allow the construction of autonomous mobile network units which can move in environments that are unknown, inaccessible or hostile for human beings, in order to collect data by various sensors and route it to a distant processing unit.To have a better performing routing process, we propose a new mobility measure. Each node measures its own mobility in the network, based on its neighbors' information. This measure has no unit and is calculated by quantification in regular time intervals.Index Terms-Information systems embedded application, intelligent sensors, wireless sensor network, ad hoc networks, OLSR protocol, multipoint relays, node mobility and mobility quantification I. INTRODUCTION Sensors have become an essential element in all systems where information resulting from the external environment is to make evaluations and act. To have an exact and complete grasp of the subject requires the deployment of several sensors and, possibly, the combination of all retrieved information to better adjust each parameter's sensor.A sensor network is composed of a large number of units called nodes. Each node mainly consists of one or several sensors, a processing unit and a communication module, etc. These nodes communicate between each other according to the network topology and the existence or not of an infrastructure (access points) to forward the information to a control unit outside the measure zone. With these features available, we can imagine an adaptive complex system built on several sensors in a wireless communication system. An original system has been designed and realized: MIS (Mobile Intelligent System) project, which allows integrating three main functions: information' acquisition, processing and routing around an embedded architecture such as FPGA (FieldProgrammable Gate Array).Mobility impacts conditions where routing protocols should operate, the context that nodes can use to communicate, and the problems that protocols should solve.In this paper, we introduce the architecture of the MIS and present a new quantitative measure of mobility reflecting the mobility degree in each MIS. Using OLSR routing protocol, this mobility measure will be exploited by the MIS during the route discovery process to enhance it and adapt it in the presence of high mobility.

This paper proposes a new routing approach that combines the residual bandwidth, energy and mobility of the network nodes. Metrics are designed to cope with high mobility and poor residual energy resources in order to find optimal paths that guarantee QoS constraints. A maximizable routing metric theory has been used to find a metric that selects, during the routing process, routes that are more stable (less mobile), that offer a maximum throughput and that live for a long time. The OLSR (Optimized Link State Routing) protocol, which is an optimization of link state protocols designed for MANETs (Mobile Ad hoc Networks) is used as a test bed in this work. We prove that our proposed composite metrics selects a more stable MPR set than the QOLSR algorithm which is a well known QoS OLSR extension. By mathematical analysis and simulations, we have shown the efficiency of this new approach in terms of routing load, packet delivery fraction, delay and prolonging the network lifetime.