Performance comparison of OLSR and BATMAN routing protocols by a MANET testbed in stairs environment

A Mobile Ad-hoc Network (MANET) is a set of mobile terminals, which move in different directions with different speeds. MANETs are found very useful in real applications such as time-lacking implementations and indoor environments. In this paper, we analyze the behavior of Optimized Link State Routing (OLSR) and Better Approach To Mobile Ad-hoc Network (BATMAN) routing protocols, in stairs environment, based on real data from our MANET testbed. We evaluate the performance considering three metrics: throughput, delay and packet loss. We design and implement two experimental scenarios: static stairs scenario and shifting stairs scenario. From our experiments, we show that as the number of hops increases to three or more hops, the performance of the communication decreases. The performance decreases further when the nodes are mobile. However, OLSR shows a better performance than BATMAN.     

Experimental results from a MANET testbed in outdoor bridge environment considering BATMAN routing protocol

A set of wireless mobile terminals, which cooperate by routing packets to each other creates a Mobile Ad-hoc Network (MANET). MANETs are continuing to grow their interest in research environment and they are attracting attention for their potential use in several fields such as collaborative computing and disaster recovery environments. Considering mobility of the terminals, the topology changes rapidly and routing becomes a key process for operation of MANETs. In this paper, we analyze the performance of Better Approach To MANET (BATMAN) routing protocol in an outdoor bridge environment considering mobility and vertical communication. We implement two scenarios on our testbed and evaluate the performance in terms of throughput and packetloss.     

Two Fuzzy-Based Systems for Selection of Actor Nodes inWireless Sensor and Actor Networks: A Comparison Study Considering Security Parameter Effect

A group of wireless devices with the ability to sense physical events (sensors) or/and to perform relatively complicated actions (actors), is referred to as Wireless Sensor and Actor Network (WSAN). In WSANs, sensors gather information about the physical events, while actors perform appropriate actions upon the environment, based on the sensed data shared by sensors. In order to provide effective sensing and acting, a distributed local coordination mechanism is necessary among sensors and actors. In this work, we propose and implement two Fuzzy Based Actor Selection Systems (FBASS): FBASS1 and FBASS2. We focus on actor selection problem and implement two fuzzy-based system. The systems decide whether the actor will be selected for the required job or not, based on data supplied by sensors and actual actor condition. We use three input parameters for FBASS1: Type of Required Action (TRA), Distance to Event (DE) and Remaining Power (RP). In FBASS2, we add the Security (SC) parameter as additional parameter. The output parameter for both systems is Actor Selection Decision (ASD). The simulation results show that the proposed systems decide the actor selection in order to have short delays, low energy consumption and proper task assignment. Comparing FBASS1 with FBASS2, the FBASS2 is more complex than FBASS1, because it has more rules in FRB. However, FBASS2 is able to decide secure actor nodes, which makes the system more secure.     

Importance Sampling Techniques for Path Tracing in Participating Media

We introduce a set of robust importance sampling techniques which allow efficient calculation of direct and indirect lighting from arbitrary light sources in both homogeneous and heterogeneous media. We show how to distribute samples along a ray proportionally to the incoming radiance for point and area lights. In heterogeneous media, we decouple ray marching from light calculations by computing a representation of the transmittance function that can be quickly evaluated during sampling, at the cost of a small amount of bias. This representation also allows the calculation of another probability density function which can direct samples to regions most likely to scatter light. These techniques are orthogonal and can be combined via multiple importance sampling to further reduce variance. Our method has very modest per‐ray memory requirements and does not require any preprocessing, making it simple to integrate into production ray tracing based renderers.