No Arabic abstract
Mobile Adhoc Network is a kind of wireless ad hoc network where nodes are connected wirelessly and the network is self configuring. MANET may work in a standalone manner or may be a part of another network. In this paper we have compared Random Walk Mobility Model and Random Waypoint Mobility Model over two reactive routing protocols Dynamic Source Routing (DSR) and Adhoc On-Demand Distance Vector Routing (AODV) protocol and one Proactive routing protocol Distance Sequenced Distance Vector Routing (DSDV) Our analysis showed that DSR, AODV & DSDV under Random Walk and Random Way Point Mobility models have similar results for similar inputs however as the pause time increases so does the difference in performance rises. They show that their motion, direction, angle of direction, speed is same under both mobility models. We have made their analysis on packet delivery ratio, throughput and routing overhead. We have tested them with different criteria like different number of nodes, speed and different maximum number of connections.
The area of mobile ad hoc networking has received considerable attention of the research community in recent years. These networks have gained immense popularity primarily due to their infrastructure-less mode of operation which makes them a suitable candidate for deployment in emergency scenarios like relief operation, battlefield etc., where either the pre-existing infrastructure is totally damaged or it is not possible to establish a new infrastructure quickly. However, MANETs are constrained due to the limited transmission range of the mobile nodes which reduces the total coverage area. Sometimes the infrastructure-less ad hoc network may be combined with a fixed network to form a hybrid network which can cover a wider area with the advantage of having less fixed infrastructure. In such a combined network, for transferring data, we need base stations which act as gateways between the wired and wireless domains. Due to the hybrid nature of these networks, routing is considered a challenging task. Several routing protocols have been proposed and tested under various traffic conditions. However, the simulations of such routing protocols usually do not consider the hybrid network scenario. In this work we have carried out a systematic performance study of the two prominent routing protocols: Destination Sequenced Distance Vector Routing (DSDV) and Dynamic Source Routing (DSR) protocols in the hybrid networking environment. We have analyzed the performance differentials on the basis of three metrics - packet delivery fraction, average end-to-end delay and normalized routing load under varying pause time with different number of sources using NS2 based simulation.
Modern computer networks support interesting new routing models in which traffic flows from a source s to a destination t can be flexibly steered through a sequence of waypoints, such as (hardware) middleboxes or (virtualized) network functions, to create innovative network services like service chains or segment routing. While the benefits and technological challenges of providing such routing models have been articulated and studied intensively over the last years, much less is known about the underlying algorithmic traffic routing problems. This paper shows that the waypoint routing problem features a deep combinatorial structure, and we establish interesting connections to several classic graph theoretical problems. We find that the difficulty of the waypoint routing problem depends on the specific setting, and chart a comprehensive landscape of the computational complexity. In particular, we derive several NP-hardness results, but we also demonstrate that exact polynomial-time algorithms exist for a wide range of practically relevant scenarios.
Reactive routing protocols are gaining popularity due to their event driven nature day by day. In this vary paper, reactive routing is studied precisely. Route request, route reply and route maintenance phases are modeled with respect to control overhead. Control overhead varies with respect to change in various parameters. Our model calculates these variations as well. Besides modeling, we chose three most favored reactive routing protocols as Ad-Hoc on Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Dynamic MANET on Demand (DYMO) for our experiments. We simulated these protocols using ns-2 for a detailed comparison and performance analysis with respect to mobility and scalability issues keeping metrics of throughput, route delay and control over head. Their performances and comparisons are extensively presented in last part of our work.
To ensure seamless communication in wireless multi-hop networks, certain classes of routing protocols are defined. This vary paper, is based upon proactive routing protocols for Wireless multihop networks. Initially, we discuss Destination Sequence Distance Vector (DSDV), Fish-eye State Routing (FSR) and Optimized Link State Routing (OLSR), precisely followed by mathematical frame work of control overhead regarding proactive natured routing protocols. Finally, extensive simulations are done using NS 2 respecting above mentioned routing protocols covering mobility and scalability issues. Said protocols are compared under mobile and dense environments to conclude our performance analysis.
With the popularity of portable wireless devices it is important to model and predict how information or contagions spread by natural human mobility -- for understanding the spreading of deadly infectious diseases and for improving delay tolerant communication schemes. Formally, we model this problem by considering $M$ moving agents, where each agent initially carries a emph{distinct} bit of information. When two agents are at the same location or in close proximity to one another, they share all their information with each other. We would like to know the time it takes until all bits of information reach all agents, called the textit{flood time}, and how it depends on the way agents move, the size and shape of the network and the number of agents moving in the network. We provide rigorous analysis for the MRWP model (which takes paths with minimum number of turns), a convenient model used previously to analyze mobile agents, and find that with high probability the flood time is bounded by $Obig(Nlog Mlceil(N/M) log(NM)rceilbig)$, where $M$ agents move on an $Ntimes N$ grid. In addition to extensive simulations, we use a data set of taxi trajectories to show that our method can successfully predict flood times in both experimental settings and the real world.