Abstract not found

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. Experiments using the ns simulator for up to 600 mobile nodes show that the storage and bandwidth requirements of GLS grow slowly with the size of the network. Furthermore, GLS tolerates node failures well: eac...

Early simulation experience with wireless ad hoc networks suggests that their capacity can be surprisingly low, due to the requirement that nodes forward each others’ packets. The achievable capacity depends on network size, traffic patterns, and detailed local radio interactions. This paper examines these factors alone and in combination, using simulation and analysis from first principles. Our results include both specific constants and general scaling relationships helpful in understanding the limitations of wireless ad hoc networks. We examine interactions of the 802.11 MAC and ad hoc forwarding and the effect on capacity for several simple configurations and traffic patterns. While 802.11 discovers reasonably good schedules, we nonetheless observe capacities markedly less than optimal for very simple chain and lattice networks with very regular traffic patterns. We validate some simulation results with experiments. We also show that the traffic pattern determines whether an ad hoc network’s per node capacity will scale to large networks. In particular, we show that for total capacity to scale up with network size the average distance between source and destination nodes must remain small as the network grows. Non-local traffic patterns in which this average distance grows with the network size result in a rapid decrease of per node capacity. Thus the question “Are large ad hoc networks feasible?” reduces to a question about the likely locality of communication in such networks.

We consider routing security in wireless sensor networks. Many sensor network routing protocols have been proposed, but none of them have been designed with security as agq1( We propose securitygcur forrouting in sensor networks, show how attacks agacks ad-hoc and peer-to-peer networks can be adapted into powerful attacks agacks sensor networks, introduce two classes of novel attacks agacks sensor networks----sinkholes and HELLO floods, and analyze the security of all the major sensor networkrouting protocols. We describe crippling attacks against all of them and sug@(5 countermeasures anddesig considerations. This is the first such analysis of secure routing in sensor networks.

We present an overview of ad-hoc routing protocols that make forwarding decisions based on the geographical position of a packet's destination. Other than the destination 's position, each node needs to know only its own position and the position of its one-hop neighbors in order to forward packets. Since it is not necessary to maintain explicit routes, position-based routing does scale well even if the network is highly dynamic. This is a major advantage in a mobile ad-hoc network where the topology may change frequently. The main prerequisite for position-based routing is that a sender can obtain the current position of the destination. Therefore, recently proposed location services are discussed in addition to position-based packet forwarding strategies. We provide a qualitative comparison of the approaches in both areas and investigate opportunities for future research.

Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius. 1.

Mobile Ad Hoc Networks (MANETs) provide rapidly deployable and self-configuring network capacity required in many critical applications, e.g., battlefields, disaster relief and wide area sensing. In this paper we study the problem of efficient data delivery in sparse MANETs where network partitions can last for a significant period. Previous approaches rely on the use of either long range communication which leads to rapid draining of nodes ’ limited batteries, or existing node mobility which results in low data delivery rates and large delays. In this paper, we describe a Message Ferrying (MF) approach to address the problem. MF is a mobility-assisted approach which utilizes a set of special mobile nodes called message ferries (or ferries for short) to provide communication service for nodes in the deployment area. The main idea behind the MF approach is to introduce non-randomness in the movement of nodes and exploit such non-randomness to help deliver data. We study two variations of MF, depending on whether ferries or nodes initiate proactive movement. The MF design exploits mobility to improve data delivery performance and reduce energy consumption in nodes. We evaluate the performance of MF via extensive ns simulations which confirm the MF approach is efficient in both data delivery and energy consumption under a variety of network conditions.

Making effective use of the vast amounts of data gathered by largescale sensor networks will require scalable, self-organizing, and energy-efficient data dissemination algorithms. Previous work has identified data-centric routing as one such method. In an associated position paper [23], we argue that a companion method, data-centric storage (DCS), is also a useful approach. Under DCS, sensed data are stored at a node determined by the name associated with the sensed data. In this paper,

Advances in micro-sensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. In order to constrain communication overhead, dense sensor networks call for new and highly efficient methods for distributing queries to nodes that have observed interesting events in the network. A highly efficient data-centric routing mechanism will offer significant power cost reductions [17], and improve network longevity. Moreover, because of the large amount of system and data redundancy possible, data becomes disassociated from specific node and resides in regions of the network [10][7][8]. This paper describes and evaluates through simulation a scheme we call Rumor Routing, which allows for queries to be delivered to events in the network. Rumor Routing is tunable, and allows for tradeoffs between setup overhead and delivery reliability. It's intended for contexts in which geographic routing criteria are not applicable because a coordinate system is not available or the phenomenon of interest is not geographically correlated.

Unless their developers take security into account at design time, sensor networks and the protocols they depend on will remain vulnerable to denial of service attacks. We identify denial of service weaknesses and solutions for sensor network devices and analyze two network protocols.