915 resultados para Wireless communications


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We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

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An ad hoc network is composed of mobile nodes without any infrastructure. Recent trends in applications of mobile ad hoc networks rely on increased group oriented services. Hence multicast support is critical for ad hoc networks. We also need to provide service differentiation schemes for different group of users. An efficient application layer multicast (APPMULTICAST) solution suitable for low mobility applications in MANET environment has been proposed in [10]. In this paper, we present an improved application layer multicast solution suitable for medium mobility applications in MANET environment. We define multicast groups with low priority and high priority and incorporate a two level service differentiation scheme. We use network layer support to build the overlay topology closer to the actual network topology. We try to maximize Packet Delivery Ratio. Through simulations we show that the control overhead for our algorithm is within acceptable limit and it achieves acceptable Packet Delivery Ratio for medium mobility applications.

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In many applications of wireless ad hoc networks, wireless nodes are owned by rational and intelligent users. In this paper, we call nodes selfish if they are owned by independent users and their only objective is to maximize their individual goals. In such situations, it may not be possible to use the existing protocols for wireless ad hoc networks as these protocols assume that nodes follow the prescribed protocol without deviation. Stimulating cooperation among these nodes is an interesting and challenging problem. Providing incentives and pricing the transactions are well known approaches to stimulate cooperation. In this paper, we present a game theoretic framework for truthful broadcast protocol and strategy proof pricing mechanism called Immediate Predecessor Node Pricing Mechanism (IPNPM). The phrase strategy proof here means that truth revelation of cost is a weakly dominant-strategy (in game theoretic terms) for each node. In order to steer our mechanism-design approach towards practical implementation, we compute the payments to nodes using a distributed algorithm. We also propose a new protocol for broadcast in wireless ad hoc network with selfish nodes based on IPNPM. The features of the proposed broadcast protocol are reliability and a significantly reduced number of packet forwards compared to the number of network nodes, which in turn leads to less system-wide power consumption to broadcast a single packet. Our simulation results show the efficacy of the proposed broadcast protocol.

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The IEEE 802.1le medium access control (MAC) standard provides distributed service differentiation or Quality-of- Service (QoS) by employing a priority system. In 802.1 le networks, network traffic is classified into different priorities or access categories (ACs). Nodes maintain separate queues for each AC and packets at the head-of-line (HOL) of each queue contend for channel access using AC-specific parameters. Such a mechanism allows the provision of differentiated QoS where high priority, performance sensitive traffic such as voice and video applications will enjoy less delay, greater throughput and smaller loss, compared to low priority traffic (e. g. file transfer). The standard implicitly assumes that nodes are honest and will truthfully classify incoming traffic into its appropriate AC. However, in the absence of any additional mechanism, selfish users can gain enhanced performance by selectively classifying low priority traffic as high priority, potentially destroying the QoS capability of the system.

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Two dimensional Optical Orthogonal Codes (OOCs) named Wavelength/Time Multiple-Pulses-per-Row (W/T MPR) codes suitable for use in incoherent fiber-optic code division multiple access (FO-CDMA) networks are reported in [6]. In this paper, we report the construction of W/T MPR codes, using Greedy Algorithm (GA), with distinct 1-D OOCs [1] as the row vectors. We present the W/T MPR codes obtained using the GA. Further, we verify the correlation properties of the generated W/T MPR codes using Matlab.

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We provide a survey of some of our recent results ([9], [13], [4], [6], [7]) on the analytical performance modeling of IEEE 802.11 wireless local area networks (WLANs). We first present extensions of the decoupling approach of Bianchi ([1]) to the saturation analysis of IEEE 802.11e networks with multiple traffic classes. We have found that even when analysing WLANs with unsaturated nodes the following state dependent service model works well: when a certain set of nodes is nonempty, their channel attempt behaviour is obtained from the corresponding fixed point analysis of the saturated system. We will present our experiences in using this approximation to model multimedia traffic over an IEEE 802.11e network using the enhanced DCF channel access (EDCA) mechanism. We have found that we can model TCP controlled file transfers, VoIP packet telephony, and streaming video in the IEEE802.11e setting by this simple approximation.

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This paper addresses the problem of secure path key establishment in wireless sensor networks that uses the random key predistribution technique. Inspired by the recent proxy-based scheme in [1] and [2], we introduce a fiiend-based scheme for establishing pairwise keys securely. We show that the chances of finding friends in a neighbourhood are considerably more than that of finding proxies, leading to lower communication overhead. Further, we prove that the friendbased scheme performs better than the proxy-based scheme in terms of resilience against node capture.

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It is a policy of Solid State Communications’ Executive Editorial Board to organize special issues from time to time on topics of current interests. The present issue focuses on soft condensed matter, a rapidly developing and diverse area of importance not only for the basic science, but also for its potential applications. The ten articles in this issue are intended to give the readers a snapshot of some latest developments in soft condensed matter, mainly from the point of view of basic science. As the special issues are intended for a broad audience, most articles are short reviews that introduce the readers to the relevant topics. Hence this special issue can be especially helpful to readers who might not be specialists in this area but would like to have a quick grasp on some of the interesting research directions.

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Modern wireline and wireless communication devices are multimode and multifunctional communication devices. In order to support multiple standards on a single platform, it is necessary to develop a reconfigurable architecture that can provide the required flexibility and performance. The Channel decoder is one of the most compute intensive and essential elements of any communication system. Most of the standards require a reconfigurable Channel decoder that is capable of performing Viterbi decoding and Turbo decoding. Furthermore, the Channel decoder needs to support different configurations of Viterbi and Turbo decoders. In this paper, we propose a reconfigurable Channel decoder that can be reconfigured for standards such as WCDMA, CDMA2000, IEEE802.11, DAB, DVB and GSM. Different parameters like code rate, constraint length, polynomials and truncation length can be configured to map any of the above mentioned standards. A multiprocessor approach has been followed to provide higher throughput and scalable power consumption in various configurations of the reconfigurable Viterbi decoder and Turbo decoder. We have proposed A Hybrid register exchange approach for multiprocessor architecture to minimize power consumption.

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We present a low-complexity algorithm for intrusion detection in the presence of clutter arising from wind-blown vegetation, using Passive Infra-Red (PIR) sensors in a Wireless Sensor Network (WSN). The algorithm is based on a combination of Haar Transform (HT) and Support-Vector-Machine (SVM) based training and was field tested in a network setting comprising of 15-20 sensing nodes. Also contained in this paper is a closed-form expression for the signal generated by an intruder moving at a constant velocity. It is shown how this expression can be exploited to determine the direction of motion information and the velocity of the intruder from the signals of three well-positioned sensors.

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We propose a method to compute a probably approximately correct (PAC) normalized histogram of observations with a refresh rate of Theta(1) time units per histogram sample on a random geometric graph with noise-free links. The delay in computation is Theta(root n) time units. We further extend our approach to a network with noisy links. While the refresh rate remains Theta(1) time units per sample, the delay increases to Theta(root n log n). The number of transmissions in both cases is Theta(n) per histogram sample. The achieved Theta(1) refresh rate for PAC histogram computation is a significant improvement over the refresh rate of Theta(1/log n) for histogram computation in noiseless networks. We achieve this by operating in the supercritical thermodynamic regime where large pathways for communication build up, but the network may have more than one component. The largest component however will have an arbitrarily large fraction of nodes in order to enable approximate computation of the histogram to the desired level of accuracy. Operation in the supercritical thermodynamic regime also reduces energy consumption. A key step in the proof of our achievability result is the construction of a connected component having bounded degree and any desired fraction of nodes. This construction may also prove useful in other communication settings on the random geometric graph.

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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.