Abstract— A distributed mobility management scheme using a class of Uniform Quorum Systems (UQS) is proposed for ad-hoc networks. In the proposed scheme, location databases are stored in the network nodes them- selves, which form a self-organizing virtual backbone within the flat net- work structure. The databases are dynamically organized into quorums, every two of which intersect at a constant number of databases. Upon lo- cation update or call arrival, a mobile’s location information is written to or read from all the databases of a quorum, chosen in a non-deterministic manner. Compared with a conventional scheme (such as the use of Home Location Register (HLR) ) with fixed associations, this scheme is more suit- able for ad-hoc networks, where the connectivity of the nodes with the rest of the network can be intermittent and sporadic and the databases are rel- atively unstable. We introduce UQS, where the size of quorum intersection is a design parameter that can be tuned to adapt to the traffic and mobil- ity patterns of the network nodes. We propose the construction of UQS through the Balanced Incomplete Block designs. The average cost due to call loss and location updates using such systems is analyzed in the pres- ence of database disconnections. Based on the average cost, we investigate the trade-off between the system reliability and the cost of location updates in the UQS scheme. The problem of optimizing the quorum size under different network traffic and mobility patterns is treated numerically. A dynamic and distributed HLR scheme, as a limiting case of the UQS, is also analyzed and shown to be suboptimal in general. It is also shown that parti- tioning of the network is sometimes necessary to reduce the cost of mobility management.
Selection of path on other hand, is determined by obstruction such as staires,ramps and lifts with such a path, for this movement we uses TIMM mobility models for indoor movement. In a realistic mobility model the nodes movement is the first step to perform mobility management. Different mobility models have different focuses and different application scenarios [1, 2, 3]. Moreover random mobility models, to get enhanced performance, some emerging mobility research papers have modified a method to organize the movement of a small part of elected nodes and develop this movement to improve the network’s overall performance. Mobility models are required to describe movement behavior on different scales. The most of the researchers resort to adding their own adhocmobility models to the traditional wired models. These adhocmobility models seldom reflect actual movement patterns. There are a few models for delineating the mobility of Mobile Users.
With the development of adhoc network technology, its mobility models have recently emerged as a hot area of research. Several current adhocmobility models were introduced in this paper, and a formula to calculate the connectivity probability of mobile adhoc network was proposed. Three of those mobility models were simulated, and the relationship among the number of nodes, the range of nodes and the connectivity probability was given by using curve-fitting firstly in this paper, which provides a judgment criterion for adhoc networking.
The problem of crowd sensing in Vehicular Ad-hoc Network is a most widely researched problem in recent years. Many researchers use various machine learning algorithms to solve the problem of congestion Mobile crowd sensing refers to a broad range of community sensing paradigms. As a special form of crowdsourcing, mobile crowd sensing aims to provide a mechanism to involve participants from the general public to efficiently and effectively contribute and utilize context-related sensing data from their mobile devices in solving specific problems in collaborations. But lack of effective solutions to quantify the relationship among participants in crowd sensing inspires us to form a formidable solution for the same. Thus, it could not effectively allocate the computing tasks and human based tasks of crowd sensing among individuals in VSNs simultaneously. Therefore, one of the problems which have been taken in this paper is about task allocation of crowd sensing in VSNs. The first major step toward achieving this goal will be to determine the effects of different driving environments on the signal propagation within the vehicular cloud framework. Also location based crowd sensing has been utilized by many researchers but there has been very few works in using content aware approach. This papertargets to achieve the goal of crowd sensing using not only location but also velocity and direction of vehicles. The aim is to develop and improved version of Kalman filter to solve the problems of non-linearity in the traditional one. In our problem statement, an expected zone needs to be computed for the possible position of the destination node. It is a circle around the destination that contains the estimated location of the destination node. The Request Zone is a rectangle with source node S in one corner (Xs, Ys), and the Expected Zone containing destination D in the other opposite comer (Xd,Yd).In this protocol, only those neighbours of source node that are present within the request zone forwards the route request packet further. The source node S should know the location of destination node D(Xd,Yd)at time t0 and average speed v with which D is moving. Every time node S initiates a new route discovery process, it the circular expected zone at time t1 with the radius R = v(t1 - t0) and center at location (Xd,Yd). I and J are neighbours of Source node S. But, only node I forwards the packets received from S to its neighbours, since I is within the request zone. The node J discards the message received from S since J is outside the request zone.
Abstract—Over the last decade, many researchers have focused on Mobile AdHoc Networks as the main communication method in disaster recovery situ- ations. In these researches, there has been marginal focus on the mobility pat- terns of nodes in disaster recovery scenarios. In this paper, a deeper analysis has been performed on some of the main mobility models used in testing new pro- tocols and a new mobility model is proposed to incorporate some neglected fac- tors concerned with disaster recovery situations.
Group mobility has been taken as the basis for the rou- ting scheme design in mobile adhoc networks due to its realistic meanings. Different from entity mobility, in which nodes move independently among each other, group mobility assumes some nodes move in a group, and they have similar moving behavior. Thus, the topo- logy within a group will keep connected most often. Group mobility could be extracted in many practical scenarios, especially in those cooperative scenarios. For example, a group of soldiers generally move together to execute a common task in the military operation. So far, a number of group mobility models have been proposed, like Reference Point Group Mobility (RPGM)  and Community-Based Mobility . Other group mobility models could be found in .
Many applications of mobile adhoc network are expected to operate in a highly dynamic environment with high host mobility. Network performance thus depends on how well routing protocols adapt to the topology dynamics. Researchers have studied the influence of mobility models on the perfor- mance of routing protocols with regard to some mobility metrics. Not surprisingly, similar conclusions [1, 8, 11, 12] have been reached by different groups. A specific model captures only one of the many possible mobility character- istics. To evaluate protocols, it is inadequate to use only one model. Various models that span across all different mobility characteristics are needed. When evaluating a sin- gle protocol, this protocol is run on various models to see how its performance changes on different models. It is found that the performance of a specific protocol varies if underly- ing mobility models are different. When evaluating a group of protocols, these protocols are run on a single model to see how these protocols rank with this modeled motion. It is found that the rank of protocols varies if underlying mo- bility models are different. In a word, routing protocols are influenced by different mobility models in different ways.
The BER at the end of a multi-hop route with the mobility characteristics performance  of the nodes and the routing strategy, are derived. Two node mobility models are considered: Direction-Persistent (DP) and Direction-Non- persistent (DNP). In particular, two network switching scenarios namely: (i) Opportunistic Non-Reservation-Based Switching (ONRBS), where a message flows from source to destination by opportunistically choosing the available shortest consecutive links; and (ii) Reservation-Based Switching (RBS), where, after the creation of a multi-hop route from source to destination, the message is ―forced‖ to flow over the reserved links, regardless of their actual lengths are analyzed. The network performance is evaluated in ideal (without inter-node interference, INI) and realistic (with INI) cases. It is observed the use of ONRBS allows supporting, at the cost of heavier control traffic, a higher mobility level than the use of RBS. The larger the traffic load (and, consequently, the INI, the lower is the impact of the routing strategy (i.e., RBS versus ONRBS) on the network performance. RBS-based WLANs, a DNP mobility model leads to a better performance, since frequent changes of directions average out, forcing the nodes to move around their original positions in a route, rather than moving far away and, therefore, disrupting connectivity. The same switching scenarios and node mobility models  are consider improving the robustness of BER against mobility from ONRBS, wrt RBS, is evaluated. It is shown that DP mobility causes a much more profound reduction in the end-to-end route BER than DNP mobility. The conclusion is more pronounced in WLAN employing RBS. Overall, the results show that if the MAC protocol is not efficient in canceling or mitigating the interference, then the role of the switching/ routing strategy in network performance is quite minor. In RBS-based WLANs, DNP mobility supports a better performance than DP mobility, since frequent changes of directions average out, forcing the nodes to move around their original positions, rather than moving far away and, therefore, affecting connectivity. Switching and, therefore, routing plays a vital role in WLANs only if the MAC protocol is effective against the interference. If communications in the network are affected by significant interference, then the selection of the switching scheme does not significantly improve the performance.
In-vehicle domain is a local network between vehicles and this network is composed of two types of units: (1) On-Board Units (OBUs) and (ii) one or more Application Units (AUs). An OBU is a communication capability (Wired and/or Wireless) device and AU is a device executing one or more applications. These applications make use of the OBU communication capabilities. The AU is a portable device such as laptop or PDA connected with OBU. Usually, the connection between OBU and AU is either wired or wirelessly connected using Bluetooth, WUSB or UWB. Both the units are working in different operation and reside on the same physical unit. In an adhoc domain, the vehicle networks are equipped with OBUs and Road Side Units (RSUs). The RSUs are fixed on the side of roads. The various moving vehicles of OBUs form a network called MANET and here OBUs are equipped with communication devices, including at least a short range wireless communication device dedicated for road safety. Mobile nodes of OBUs and static nodes of RSUs can be seen as nodes of an adhoc network. An RSU which can be attached to an infrastructure network can be used to connect with the Internet. The primary objective of RSU is to improve road safety by sending, receiving, or forwarding data in the adhoc domain. RSUs can be communicated directly with each other or via multi hop. There are two accesses in an infrastructure domain. They are RSU and Hot Spot. RSUs are permitted to access the infrastructure by OBUs and thus, OBUs are to be connected to the Internet. OBUs may communicate with Internet via public, commercial, or private hot spots (Wi-Fi hot spots). If OBUs are integrated with cellular radio networks, they can also be utilizing cellular radio networks communication capabilities even if RSUs and Hot Spots are not available.
Route Cache Timeout is one of the important parameters of DSR protocol affecting the throughput of the protocol. In this paper, we present our research about the effects of the Route Cache Timeout parameter on the performance of DSR protocol. It’s important to see the effect of Route Cache Timeout on adhoc networks with different characteristics. For example, adhoc networks with different number of nodes and scales; also adhoc networks having different levels of mobility have been used in this work. We carried out our research using the Omnet++ network simulator.
Network-based mobility management protocols Network-based Localized Mobility Management (NetLMM), allows conventional IP devices (for example, devices running standard protocol stacks) to roam freely across wireless stations belonging to the same local domain. This property is appealing from the operator's viewpoint because it allows service providers to enable mobility support without imposing requirements on the terminal side (for example, software and related configuration). Figure-4 represents the type of IPv6 in network-based mobility management.
This simulator was initially developed as network simulator but the latest version NCTUns 4.0 is having capability to integrate some traffic simulation, for example, maps designing and vehicle’s mobility controller. NCTUns can also work as an emulator which has a capability of simulation of various protocols used in both wired and wireless networks. It internally uses LINUX TCP/IP protocol stack and able to run any real life UNIX application program on simulated mode without any modification. It also provides efficient GUI that can help user to draw network topologies, configure the protocol module used inside a node, specification about the moving paths of node, plot network performance graphs, and playback the animation of a logged packet transfer trace. The main drawback of this simulator is that it requires Fedora 9 Linux distribution to be installed.
Mobile Adhoc Networks (MANETs) are self-organizing wireless networks, in which also end nodes act as routers. MANET networking improves the efficiency and range of fixed and mobile internet access and enables totally new applications such as sensor networks. Its offer unique challenges and opportunities to network designers and administrators. They increase system capacity, reduce deployment cost as they require no supportive infrastructure, and reduce administrative cost as they are self configurable and self-adaptable. However, their inherent characteristic of frequent topology changes adds complexity to routing and transport connection management.
Most studies on mobility of MANET protocols [11, 12] focus on node mobility in various environments in which a mobile node might randomly change its speed and direction. Moreover, vehicle movements are often expressed by extending these models and are typically related to road traﬃc condition and are restricted to one dimension. Thus, several traﬃc models [13–15] that represented vehicles as randomly moving particles do not fit for realistic traﬃc pattern. In this work, we proposed an alternative link construction mechanism based on the prediction of possible link break and congestion. A fuzzy congestion detector and a fuzzy link break predictor are proposed to determine whether alternate route construction process should be activated. Particle swarm optimization (PSO) technique is used to adjust the parameters of the membership functions employed in the fuzzy logic systems in order to deal with the volatile characteristics of the VANET. A series of experiments were conducted to compare the proposed scheme with other representative adhoc routing protocols in the literature, including the well-known AODV routing protocol and a recently presented state-of-the-art adhoc routing protocol in the literature, congestion-adaptive routing protocol (CRP) . In CRP, the number of packets currently buﬀered in interface is defined as network load and the congestion is classified into diﬀerent statuses. If congestion is detected at a node, a bypass route is used to ease the congestion. The experimental results showed that the proposed work achieves better performance than other representative schemes in the literatures in terms of several performance metrics such as packet delivery ratio, end-to-end delay, and control overhead.
Geocast was introduced by Navas et al. [4,3]. Geocast algorithms for mobile ad-hoc networks [5,10,7,6], unlike our deterministic solution, only provide probabilistic guarantees. This may not suffice. For example, Dolev et al.  need a deterministic geocast to implement atomic memory. Deterministic solutions are given for multicast [14,16,17] and broadcast  for mobile ad-hoc networks. Both solutions in [14,16] consider a finite and fixed number of mobile nodes arranged somehow in logical or physical structures. They divide the nodes into groups each of which has a special node which coordinates message propagation and collects acknowledgments. Moreover, they make the following stronger than necessary assumption: they require that the network topology stabilizes for periods long enough to ensure delivery. Finally, simulation results  show that the approach proposed in  does not work if nodes move fast. Bounds that allow the algorithms to work correctly are not presented. Chandra et al.  provide a broadcasting algorithm and show by experiments that either all or none of the nodes get the message with high probability. Mohsin et al.  implement (deterministic) broadcast for a synchronous mobile ad-hoc network with restricted movement patterns. In particular, nodes move on top of a grid such that at the beginning of each round nodes are located at grid points. They assume that all nodes move at the same constant speed and direction of movement cannot change within a round. Finally, nodes need to inform their neighbors about their future moving pattern for short future time periods.
Pursue Smart Mobility Model is an optimization of Pursue Mobility Model. In Pursue Mobility Model, all the nodes except the pioneer node have to start from the same point from where the pioneer node has started. But in Pursue Smart Mobility Model, all nodes will start from their nearest segment when the pioneer node reached to the segment.
Key management is a basic part of any secure communication. Group key management protocols based on the decentralized approach can be best suited in mobile adhoc network. However, group key management for large and dynamic groups in MANETs is a difficult problem because of the requirement of scalability and security.Thus this phase proposes a reliable dynamic clustering approach by reducing the packet drop ratio and increasing the key delivery ratio. In many multicast interactions, due to its frequent node mobility, new member can join and current members can leave at any time. The moving behavior of each members in the MANET should be realistic. The pattern of movement of members is classified Proposed Methodology into different mobility models and each one has its own distinct features. It is a crucial part in the performance of MANET. Once the clusters are created within the multicast group, the new CH becomes responsible for the local key management and distribution to their local members, and also for the maintenance of the strongly correlated cluster property. An efficient Cluster Based Multicast Tree (CBMT) using mobility aware Multicast version DSDV for secure multicast key distribution. MDSDV have multicast connectivity between nodes. It sends acknowledgement for each transmission in order to reduce the retransmission. The CHs are elected easily with periodic updates of node join and leave information using multicast tree. This overcomes the issues of end to end delay in multicast transmission and also tolerates the fault that occurs due to node failure. The proposed approach is to achieve secure multicast communication for mobile adhoc networks. This approach uses Multicast version of DSDV routing protocol to maintain routing table periodically. It forms multicast tree among the group members. Each node can determine their present physical location. It quickly adapts to the topology changes. It is used to discover alternate route for failure of existing route. It also sends acknowledgement for each transmission in order to reduce the retransmission. Thus the approach of CBMT using MDSDV tends to have multicast connectivity between the nodes.
In the same context, the paper  presented a new method for clustering in VANETs to select the cluster heads based on the standard deviation of average relative velocity and density matrices in their neighborhood. Vehicle, which is having more homogeneous environments, will become the cluster heads and rest of the vehicles in their communication range will be the Cluster Members (CMs). The simulation results demonstrate the better performance of MADCCA over other clustering algorithms new ALM and MOBICA. Another paper  proposed a new opportunistic routing protocol (DPOR) that uses driving path predictability and vehicular distribution in its route selection procedure. This protocol is composed of two phases: intersection and next hop selection phases. A utility function is calculated to select the next intersection and a new mechanism is also proposed for the next hop selection phase. Simulation results show that DPOR achieves high delivery ratio and low end-to-end delay in the network. Therefore, researchers in  and  developed a new mechanism through mobility integration to enhance network performance in OLSR protocol. The first is based on the mobility rate and the last is based on the formula of mobility to improve OLSR and Mob-OLSR with presenting a new protocol called Mob-2-OLSR.
• WiMAX: Worldwide Interoperability for Microwave Access (WIMAX) is a long range wireless metropolitan area network technology based on the IEEE 802.16 for fixed and 802.16e for mobile access. WiMAX works at 10-66 and 2-11 GHz and provides up to 70 Mbps data rate and covers maximum range of 50 Km. WiMAX supports point to multipoint (PMP) as well as mesh mode. In the PMP mode, multiple subscriber stations (SSs) are connected to one base station (BS) where the access channel from the BS to the SS is called the downlink channel and the one from the SS to BS is called the uplink . The purpose of WiMAX is deployment of broadband wireless access networks by using a global standards. WiMAX is also capable of supporting fast moving users in a mesh network structure. IEEE 802.16e is an amendment to the original WiMAX and provides a high data rate and covers a wide transmission range with reliable communications and high quality of service, which makes it suitable for those applications requiring these features such as multimedia, video and voice over internet protocol applications . WiMAX achieves a high data rate of up to 35 Mbps using MIMO, with an orthogonal frequency division multiplexing (OFDM) and covers a transmission range of 15 Km . Mobile WiMAX aims at maintaining mobile clients connected to a MAN while moving around . Mobile WiMAX is a suitable wireless technology for networked vehicular applications because of its mobility support at vehicular speeds and its inherent wide coverage, which minimizes rate of handover and thus data loss due to disrupted communication .
Abstract: A Mobile Adhoc Network (MANET) is a collection of wireless mobile nodes forming a temporary network without using any existing infrastructure. Since not many MANETs are currently deployed, research in this area is mostly simulation based. This paper focus on performance of Random Waypoint mobility model. We analyse various protocol independent metrics to capture interesting mobility characteristics, including spatial and temporal dependence and geographic restrictions. In this we compare the above charetristics with other mobility models. It also analyse the working of various MANET routing protocols, including DSR, AODV and DSDV with Random Waypoint mobility model.