860 resultados para mobile ad-hoc networks


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A Cooperative Collision Warning System (CCWS) is an active safety techno- logy for road vehicles that can potentially reduce traffic accidents. It provides a driver with situational awareness and early warnings of any possible colli- sions through an on-board unit. CCWS is still under active research, and one of the important technical problems is safety message dissemination. Safety messages are disseminated in a high-speed mobile environment using wireless communication technology such as Dedicated Short Range Communication (DSRC). The wireless communication in CCWS has a limited bandwidth and can become unreliable when used inefficiently, particularly given the dynamic nature of road traffic conditions. Unreliable communication may significantly reduce the performance of CCWS in preventing collisions. There are two types of safety messages: Routine Safety Messages (RSMs) and Event Safety Messages (ESMs). An RSM contains the up-to-date state of a vehicle, and it must be disseminated repeatedly to its neighbouring vehicles. An ESM is a warning message that must be sent to all the endangered vehi- cles. Existing RSM and ESM dissemination schemes are inefficient, unscalable, and unable to give priority to vehicles in the most danger. Thus, this study investigates more efficient and scalable RSM and ESM dissemination schemes that can make use of the context information generated from a particular traffic scenario. Therefore, this study tackles three technical research prob- lems, vehicular traffic scenario modelling and context information generation, context-aware RSM dissemination, and context-aware ESM dissemination. The most relevant context information in CCWS is the information about possible collisions among vehicles given a current vehicular traffic situation. To generate the context information, this study investigates techniques to model interactions among multiple vehicles based on their up-to-date motion state obtained via RSM. To date, there is no existing model that can represent interactions among multiple vehicles in a speciffic region and at a particular time. The major outcome from the first problem is a new interaction graph model that can be used to easily identify the endangered vehicles and their danger severity. By identifying the endangered vehicles, RSM and ESM dis- semination can be optimised while improving safety at the same time. The new model enables the development of context-aware RSM and ESM dissemination schemes. To disseminate RSM efficiently, this study investigates a context-aware dis- semination scheme that can optimise the RSM dissemination rate to improve safety in various vehicle densities. The major outcome from the second problem is a context-aware RSM dissemination protocol. The context-aware protocol can adaptively adjust the dissemination rate based on an estimated channel load and danger severity of vehicle interactions given by the interaction graph model. Unlike existing RSM dissemination schemes, the proposed adaptive scheme can reduce channel congestion and improve safety by prioritising ve- hicles that are most likely to crash with other vehicles. The proposed RSM protocol has been implemented and evaluated by simulation. The simulation results have shown that the proposed RSM protocol outperforms existing pro- tocols in terms of efficiency, scalability and safety. To disseminate ESM efficiently, this study investigates a context-aware ESM dissemination scheme that can reduce unnecessary transmissions and deliver ESMs to endangered vehicles as fast as possible. The major outcome from the third problem is a context-aware ESM dissemination protocol that uses a multicast routing strategy. Existing ESM protocols use broadcast rout- ing, which is not efficient because ESMs may be sent to a large number of ve- hicles in the area. Using multicast routing improves efficiency because ESMs are sent only to the endangered vehicles. The endangered vehicles can be identified using the interaction graph model. The proposed ESM protocol has been implemented and evaluated by simulation. The simulation results have shown that the proposed ESM protocol can prevent potential accidents from occurring better than existing ESM protocols. The context model and the RSM and ESM dissemination protocols can be implemented in any CCWS development to improve the communication and safety performance of CCWS. In effect, the outcomes contribute to the realisation of CCWS that will ultimately improve road safety and save lives.

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Road traffic accidents can be reduced by providing early warning to drivers through wireless ad hoc networks. When a vehicle detects an event that may lead to an imminent accident, the vehicle disseminates emergency messages to alert other vehicles that may be endangered by the accident. In many existing broadcast-based dissemination schemes, emergency messages may be sent to a large number of vehicles in the area and can be propagated to only one direction. This paper presents a more efficient context aware multicast protocol that disseminates messages only to endangered vehicles that may be affected by the emergency event. The endangered vehicles can be identified by calculating the interaction among vehicles based on their motion properties. To ensure fast delivery, the dissemination follows a routing path obtained by computing a minimum delay tree. The multicast protocol uses a generalized approach that can support any arbitrary road topology. The performance of the multicast protocol is compared with existing broadcast protocols by simulating chain collision accidents on a typical highway. Simulation results show that the multicast protocol outperforms the other protocols in terms of reliability, efficiency, and latency.

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Many applications can benefit from the accurate surface temperature estimates that can be made using a passive thermal-infrared camera. However, the process of radiometric calibration which enables this can be both expensive and time consuming. An ad hoc approach for performing radiometric calibration is proposed which does not require specialized equipment and can be completed in a fraction of the time of the conventional method. The proposed approach utilizes the mechanical properties of the camera to estimate scene temperatures automatically, and uses these target temperatures to model the effect of sensor temperature on the digital output. A comparison with a conventional approach using a blackbody radiation source shows that the accuracy of the method is sufficient for many tasks requiring temperature estimation. Furthermore, a novel visualization method is proposed for displaying the radiometrically calibrated images to human operators. The representation employs an intuitive coloring scheme and allows the viewer to perceive a large variety of temperatures accurately.

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Process models are usually depicted as directed graphs, with nodes representing activities and directed edges control flow. While structured processes with pre-defined control flow have been studied in detail, flexible processes including ad-hoc activities need further investigation. This paper presents flexible process graph, a novel approach to model processes in the context of dynamic environment and adaptive process participants’ behavior. The approach allows defining execution constraints, which are more restrictive than traditional ad-hoc processes and less restrictive than traditional control flow, thereby balancing structured control flow with unstructured ad-hoc activities. Flexible process graph focuses on what can be done to perform a process. Process participants’ routing decisions are based on the current process state. As a formal grounding, the approach uses hypergraphs, where each edge can associate any number of nodes. Hypergraphs are used to define execution semantics of processes formally. We provide a process scenario to motivate and illustrate the approach.

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This paper gives an overview of the INEX 2008 Ad Hoc Track. The main goals of the Ad Hoc Track were two-fold. The first goal was to investigate the value of the internal document structure (as provided by the XML mark-up) for retrieving relevant information. This is a continuation of INEX 2007 and, for this reason, the retrieval results are liberalized to arbitrary passages and measures were chosen to fairly compare systems retrieving elements, ranges of elements, and arbitrary passages. The second goal was to compare focused retrieval to article retrieval more directly than in earlier years. For this reason, standard document retrieval rankings have been derived from all runs, and evaluated with standard measures. In addition, a set of queries targeting Wikipedia have been derived from a proxy log, and the runs are also evaluated against the clicked Wikipedia pages. The INEX 2008 Ad Hoc Track featured three tasks: For the Focused Task a ranked-list of nonoverlapping results (elements or passages) was needed. For the Relevant in Context Task non-overlapping results (elements or passages) were returned grouped by the article from which they came. For the Best in Context Task a single starting point (element start tag or passage start) for each article was needed. We discuss the results for the three tasks, and examine the relative effectiveness of element and passage retrieval. This is examined in the context of content only (CO, or Keyword) search as well as content and structure (CAS, or structured) search. Finally, we look at the ability of focused retrieval techniques to rank articles, using standard document retrieval techniques, both against the judged topics as well as against queries and clicks from a proxy log.

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This article uses the example of the mediatisation of Season 2 of the Australian documentary-cum-reality TV series Go Back to Where You Came From, and the associated #GoBackSBS Twitter feed, to investigate how public opinions are shaped, reshaped and expressed in new hybrid media ecologies. We explore how social media tools like Twitter can support the efforts of a TV production; provide spaces through which the public can engage ad hoc with a public event, be informed, shape their opinions and share them with others; and thus open up new possibilities for public discourse to occur. We suggest that new online public sphericules are emerging that provide spaces within which publics can engage with the cultural social and political realities with which they are confronted. In this way, we highlight the importance of mundane communication to the shaping and constant reshaping of public opinion.

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We present a new approach for creating and implementing an ad-hoc underwater acoustic sensor network based on connecting a small processor to the serial port of a commercial CDMA acoustic modem. The processor acts as a "node controller" providing the networking layer that the modems lack. The ad-hoc networking protocol is based on a modified dynamic source routing (DSR) approach and can be configured for maximising information throughput or minimising energy expenditure. The system was developed in simulation and then evaluated during field trials using a 10 node deployment. Experimental results show reliable multi-hop networking under a variety of network configurations, with the added ability to determine internode ranges to within 1.5 m for localisation.

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This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

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Researchers and practitioners have been preoccupied with identifying ways for larger organizations to acquire and manage knowledge, however far less research attention has been directed towards these same pursuits in small and medium-sized enterprises (SMEs). This paper examines how SMEs engage in knowledge identification and acquisition; in particular how they identify knowledge needs and source this knowledge to enhance their business. The research studied six SMEs in Australia and Denmark. Contrary to prevailing assumptions, the findings suggest that SMEs engage in identification and sourcing of critical knowledge, albeit often with less than formal processes. These organizations relied on business plans to direct knowledge activities and ensure balance between long-range planning and flexibility. The results address a lack of empirical evidence about SME approaches to knowledge identification and acquisition, and demonstrate that although SMEs may approach such activities in an informal way, they are nonetheless deliberate and strategic in their knowledge activities.

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In this paper, we study the performance of client-Access Point (AP) association policies in IEEE 802.11 based WLANs. In many scenarios, clients have a choice of APs with whom they can associate. We are interested in finding association policies which lead to optimal system performance. More specifically, we study the stability of different association policies as a function of the spatial distribution of arriving clients. We find for each policy the range of client arrival rates for which the system is stable. For small networks, we use Lyapunov function methods to formally establish the stability or instability of certain policies in specific scenarios. The RAT heuristic policy introduced in our prior work is shown to have very good stability properties when compared to several other natural policies. We also validate our analytical results by detailed simulation employing the IEEE 802.11 MAC.

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In many IEEE 802.11 WLAN deployments, wireless clients have a choice of access points (AP) to connect to. In current systems, clients associate with the access point with the strongest signal to noise ratio. However, such an association mechanism can lead to unequal load sharing, resulting in diminished system performance. In this paper, we first provide a numerical approach based on stochastic dynamic programming to find the optimal client-AP association algorithm for a small topology consisting of two access points. Using the value iteration algorithm, we determine the optimal association rule for the two-AP topology. Next, utilizing the insights obtained from the optimal association ride for the two-AP case, we propose a near-optimal heuristic that we call RAT. We test the efficacy of RAT by considering more realistic arrival patterns and a larger topology. Our results show that RAT performs very well in these scenarios as well. Moreover, RAT lends itself to a fairly simple implementation.

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This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating–dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating–dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs – these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating–dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.