Analysis of the effects of mobility on the grid location service in ad hoc networks (original) (raw)
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A Mobile Ad-hoc Network (MANET) is a network topology of choice where autonomous nodes form a collaborative community. Position based routing protocols have been studied extensively over the past years, But how to efficiently provide the location information for nodes and how to control location update frequency is still a challenge. In this paper, we address the problem of maintaining location service and propose an energy aware grid location service which efficiently provide location information and conserve energy extending the lifetime of a MANET. The protocol uses hierarchical grid location service to minimize inevitable superfluous flooding by every node, and prevents location updates and queries from traversing the entire network unnecessarily, hence conserving bandwidth and transmission power.
GRID: A fully location-aware routing protocol for mobile ad hoc networks
2001
A mobile ad hoc network (MANET) is one consisting of a set of mobile hosts capable of communicating with each other without the assistance of base stations. One prospective direction to assist routing in such an environment is to use location information provided by positioning devices such as global positioning systems (GPS). In this paper, we propose a new routing protocol called GRID, which tries to exploit location information in route discovery, packet relay, and route maintenance. Existing protocols, as compared to ours, are either not location-aware or partially location-aware in that location knowledge is not fully exploited in all these three aspects. One attractive feature of our protocol is its strong route maintenance capability-the intermediate hosts of a route can perform a "handoff" operation similar to that in cellular systems when it roams away to keep a route alive. This makes routes in the MANET more stable and insensitive to host mobility. Simulation results show that our GRID routing protocol can reduce the probability of route breakage, reduce the number of route discovery packets used, and lengthen routes' lifetime.
Scalability analysis of location management protocols for mobile ad hoc networks
2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733)
With the availability of location based services, applications that use locations for optimal performance will require efficient location management algorithms, where user locations are kept track with minimal system overhead. Geography based routing in mobile ad hoc networks is one such application that uses location information of nodes in a network to route data packets. Previous work in this area has shown that the selection of location management protocol is critical to the performance of such routing algorithms. Many location management schemes have been proposed in literature, and in an effort to quantitatively compare the performance of some of these schemes, we carry out extensive simulations to study SLURP, SLALoM and HGRID, three grid based protocols described in literature. Our study is two pronged-to compare the performance of location management with network mobility as well as traffic load, and to evaluate the effect these protocols have on the performance of geographic routing in mobile ad hoc networks. Our results show that the Hierarchical Grid Location Management protocol (HGRID) achieves steady performance for data throughput and delay, and minimally affects the performance of geographic routing.
Location service in ad-hoc networks: Modeling and analysis
2004
Location-based routing significantly reduces the control overhead in mobile ad hoc networks (MANETs) by utilizing position information of mobile nodes in forwarding decisions. However a location service is needed before any forwarding scheme can be applied. Therefore the scalability of the location services directly affects the overall scalability of location-based routing. Recently, several location service schemes have been proposed, most of which are evaluated based on only one or two performance metrics, and under only the uniform traffic pattern. We believe that a comprehensive comparative study is needed to gain a deeper understanding of the design trade-offs in developing scalable location services. In this paper, we first present a taxonomy of existing schemes and explore the design space and tradeoffs involved. We then develop a common theoretical framework to analyze five existing and representative schemes in terms of three important cost metrics-location maintenance cost, location query cost, and storage cost-and under different traffic patterns. Our analysis shows that the design of location services involves tradeoffs among all three cost metrics, and overlooking any of them may lead to biased conclusions. We also show that some of the schemes are more effective in exploiting localized traffic patterns, thereby more suitable for large scale MANETs, where traffic patterns are more likely to be highly localized.
A scalable location service for geographic ad hoc routing
2000
GLS is a new distributed location service which tracks mobile node locations. GLS combined with geographic forwarding allows the construction of ad hoc mobile networks that scale to a larger number of nodes than possible with previous work. GLS is decentralized and runs on the mobile nodes themselves, requiring no fixed infrastructure. Each mobile node periodically updates a small set of other nodes (its location servers) with its current location. A node sends its position updates to its location servers without knowing their actual identities, assisted by a predefined ordering of node identifiers and a predefined geographic hierarchy. Queries for a mobile node's location also use the predefined identifier ordering and spatial hierarchy to find a location server for that node.
Radio Communications, 2010
An ad hoc 1 network is defined as a decentralised wireless network that is set up on-the-fly for a specific purpose. These networks were proposed years ago for military use, with the purpose of communicating devices in a highly constrained scenario. Under such a network, devices join and leave the network dynamically; thus, it cannot be expected to have any kind of network infrastructure. This wish for decentralised on-the-fly networks has subsequently expanded to cover several fields besides the military. Today, there are several mobile services requiring the self-organising capabilities that ad hoc networks offer. Examples include packet tracking, online-gaming, and measuring systems, among others. Ad hoc networks have obvious benefits for mobile services, but they also introduce new issues that regular network protocols cannot cope with, including optimum routing, network fragmentation, reduced calculation power, energy-constrained terminals, etc. In ad hoc networks, positioning takes a significant role, mainly due to the on-the-fly condition. In fact, several services require nodes to know the position of the customers in order to perform their duty properly. Wireless sensor networks concentrate most of the services that need positioning to perform their duty. Such networks constitute a subset of ad hoc networks involving dense topologies operating in an ad hoc fashion, and they are composed of small, energy and computation constrained terminals. In ad hoc networks, and especially in wireless sensor networks, nodes are spread over a certain area without a precise knowledge about the topology. In fact, this topology is variable. Accordingly, there are several unknowns (e.g., node density and coverage, network's energy map, the presence of shadowed zones, nodes' placement in the network coverage area) that are likely to constrain the performance of ad hoc services. Knowledge of the terminals' locations can substantially improve the service performance. Positioning is not only important for the service provisioning; it is also crucial in the ad hoc protocol stack development. Due to the changes in the topology and the lack of communication infrastructure, ad hoc protocols have to address several issues not present in regular cellular networks. Routing is one of the best examples of the dependence of ad hoc networks on positioning. Studies such as (Stojmenovic, 2002) demonstrate that only position-based routing protocols are scalable, i.e., able to cope with a higher density of 1 "Ad hoc" is actually a Latin phrase that means "to this (thing, purpose, end, etc.)" 31 www.intechopen.com Radio Communications 620 nodes in the network. The same seems to apply to other management and operation tasks in ad hoc networks. 1.1 The Location problem in ad hoc networks Nodes in an ad hoc network can be grouped into three categories according to the positioning capabilities: beacon nodes, settled nodes, and unknown nodes. Beacon nodes, also known as anchors or landmarks, are those able to compute their position on their own, i.e., without using an ad hoc location algorithm. Accordingly, they implement at least one location technique (e.g., GPS, map matching), which can be used as standalone. Beacon nodes usually constitute the reference frame necessary to set up a location algorithm. Unknown nodes are those nodes that do not know their position yet. When an ad hoc network is set up, all nodes except the beacon nodes are unknown. Settled nodes are unknown nodes that are able to compute their position from the information that they exchange with beacon nodes and/or other settled nodes. The purpose of the ad hoc location system is thus to position as many nodes as possible, turning them from unknown to settled nodes (Bourkerche et al., 2007). Location systems in ad hoc networks function in two steps: local positioning and positioning algorithm. The former is responsible for computing the position of an unknown node from the metrics gathered. The second step consists of the positioning algorithm, which indicates how the position information is managed in order to maximise the number of nodes being settled. 1.2 Measuring the performance of location solutions Performance of location solutions in ad hoc networks can be computed according to several parameters. The main ones are presented below. 1.2.1 Accuracy Ad hoc positioning requires good accuracy since most of the networks in ad hoc mode are deployed in constrained scenarios, often indoors. In such environments, accuracy is especially relevant, since a few meters of error in the position may cause the node to be identified in another room, floor, or even building. Furthermore, nodes are expected to be very close (e.g., in medical applications), and inaccurate positions could hinder operation and maintenance tasks or even prevent location-based applications from performing their duty. Thus, location algorithms for ad hoc networks must produce positions for settled nodes of the highest possible accuracy.
Location information services in mobile ad hoc networks
2002
In recent years, many location based routing protocols have been developed for ad hoc networks. Some of these protocols assume a location service exists which provides location information on all the mobile nodes in the network. In this paper, we evaluate three location service alternatives. One is a reactive protocol; the other two are proactive protocols. Of the proactive protocols, one sends location tables to neighbors and the other sends location information to all nodes. In our evaluation, one proactive protocol proved to have the best performance overall. Thus, we also evaluate the main input parameter associated with this protocol for optimal performance.
Mobility Impact on MANET Routing Protocols In Grid Networks
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2013
Mobile Ad-Hoc Networks (MANETS) is a collection of wireless mobile nodes that are able to dynamically form a temporary network without any aid from fixed infrastructure or centralized administration due to no wired backbone.Ad Hoc networks are formed spontaneously and the nodes are highly mobile.Thispaper presents performance evaluations, comparisons, andanalysis for three routing protocols (AODV, DSR, and OLSR)to bring out their relative meritsundervarying network size and mobilitywith  various speed and pause times. The simulation is carried out using OMNET++ simulator based on the quantitative basic parameters like throughput, Packet transmission Ratio (PTR),packet transmission time delay and protocol overhead .The  nodes are distributed randomly in a grid network topology and mobile nodes moving using Random Waypoint mobility models. The results demonstrate that, undervarious node speeds and pause timesfor different network size, AODVoutperforms DSR and OLSR protocols, with re...
Mobility-enhanced positioning in ad hoc networks
2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003.
This paper discusses and investigates the effects of mobility on positioning of wireless ad hoc networks. We present a Mobility-enhanced Ad hoc Positioning (MAP) scheme, where we leverage on the mobility of nodes within the network. The scheme uses the hop counts information from fixed reference nodes to perform positioning and improves accuracy by using mobile nodes to "bridge" gaps within neighborhoods where accurate information was not available. Simulation shows that using mobility does improve the performance of such "hop count"-based positioning schemes.