“…In the context of ad-hoc wireless networks, there have been a number of proposals [8] for geographic routing algorithms. Unlike the commonlyused shortest path technique, geographic routing uses the relationship between geographic position and connectivity in a wireless network.…”
Abstract. Wireless sensor networks will be used in a wide range of challenging applications where numerous sensor nodes are linked to monitor and report distributed event occurrences. In contrast to traditional communication networks, the single major resource constraint in sensor networks is power, due to the limited battery life of sensor devices. It has been shown that data-centric methodologies can be used to solve this problem efficiently. In data-centric storage, a recently proposed data dissemination framework, all event data is stored by type at designated nodes in the network and can later be retrieved by distributed mobile access points in the network. In this paper we propose Resilient Data-Centric Storage (R-DCS) as a method to achieve scalability and resilience by replicating data at strategic locations in the sensor network. Through analytical results and simulations, we show that this scheme leads to significant energy savings in reasonably large-sized networks and scales well with increasing node-density and query rate. We also show that R-DCS realizes graceful performance degradation in the presence of clustered as well as isolated node failures, hence making the sensornet data robust.
“…In the context of ad-hoc wireless networks, there have been a number of proposals [8] for geographic routing algorithms. Unlike the commonlyused shortest path technique, geographic routing uses the relationship between geographic position and connectivity in a wireless network.…”
Abstract. Wireless sensor networks will be used in a wide range of challenging applications where numerous sensor nodes are linked to monitor and report distributed event occurrences. In contrast to traditional communication networks, the single major resource constraint in sensor networks is power, due to the limited battery life of sensor devices. It has been shown that data-centric methodologies can be used to solve this problem efficiently. In data-centric storage, a recently proposed data dissemination framework, all event data is stored by type at designated nodes in the network and can later be retrieved by distributed mobile access points in the network. In this paper we propose Resilient Data-Centric Storage (R-DCS) as a method to achieve scalability and resilience by replicating data at strategic locations in the sensor network. Through analytical results and simulations, we show that this scheme leads to significant energy savings in reasonably large-sized networks and scales well with increasing node-density and query rate. We also show that R-DCS realizes graceful performance degradation in the presence of clustered as well as isolated node failures, hence making the sensornet data robust.
“…Position-based routing is a reactive routing used in wireless networks, where the nodes are equipped with a positioning system, such that a message can be forwarded in the direction of the target (see [12] for a survey). Due to the limited range of the radio transceivers, there are local minima and messages have to be routed around void regions (an analog to the fault regions in the mesh network).…”
Abstract. We consider the problem of routing a message in a mesh network with faulty nodes. The number and positions of faulty nodes is unknown. It is known that a flooding strategy like expanding ring search can route a message in the minimum number of steps h while it causes a traffic (i.e. the total number of messages) of O(h 2 ). For optimizing traffic a single-path strategy is optimal producing traffic O(p + h), where p is the perimeter length of the barriers formed by the faulty nodes. Therefore, we define the comparative traffic ratio as a quotient over p + h and the competitive time ratio as a quotient over h. Optimal algorithms with constant ratios are known for time and traffic, but not for both. We are interested in optimizing both parameters and define the combined comparative ratio as the maximum of competitive time ratio and comparative traffic ratio. Single-path strategies using the right-hand rule for traversing barriers as well as multi-path strategies like expanding ring search have a combined comparative ratio of Θ(h). It is an open question whether there exists an online routing strategy optimizing time and traffic for meshes with an unknown set of faulty nodes. We present an online strategy for routing with faulty nodes providing sub-linear combined comparative ratio of h O "q log log h log h " .
“…projects like Fleetnet [1]), both in Europe and the U.S., have already produced results in the investigation of vehicular ad hoc networks. For instance, geographic routing has been selected as routing scheme due to its compliance with application needs and its good performance under extremely dynamic network conditions [2].
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Abstract-Vehicle communication is regarded as one of the major applications of mobile ad hoc networks (MANETs). In these so called vehicular ad hoc networks (VANETs) security and privacy are crucial factors for successful deployment. For example, if each vehicle had a unique identifier and utilized it during its communication, eavesdroppers could easily accumulate location profiles. One approach in the literature proposes to use changing pseudonyms as temporary vehicle identifiers. The basic idea is that the more frequently a vehicle changes its pseudonym, the shorter the period over which it can be tracked will be. However, the impact of such an approach on the system performance has been largely overlooked. Exactly this is our contribution in this paper: we find that changing identifiers has detrimental effects on routing efficiency and increases packet loss. Our investigation provides a set of basic findings that can guide system designers, to achieve both the sought level of protection and performance as well as the right trade-off between the two objectives.I. INTRODUCTION Vehicular ad hoc networks (VANETs) are one of the most promising application scenarios for mobile adhoc networks. With the advent of car-to-car communication, both passenger safety and driving comfort can be improved significantly. A car detecting an icy road could inform follow-up vehicles and thereby prevent accidents. If an accident occurs anyway, inter-vehicle communication could support emergency relief units to reach the accident site faster by warning drivers blocking the road ahead or preemption of traffic lights. Regarding driving comfort, inter-vehicle communication could serve to exchange traffic flow information for improved navigation or intelligent adaptive cruise control.Several research initiatives (e.g. projects like Fleetnet [1]), both in Europe and the U.S., have already produced results in the investigation of vehicular ad hoc networks. For instance, geographic routing has been selected as routing scheme due to its compliance with application needs and its good performance under extremely dynamic network conditions [2].
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