In recent years, fractal is widely used everywhere and escape time algorithm (ETA) became the most useful fractal creating method. However, ETA performs not so well because it needs huge computations. So, in this pape...
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In recent years, fractal is widely used everywhere and escape time algorithm (ETA) became the most useful fractal creating method. However, ETA performs not so well because it needs huge computations. So, in this paper, we first present an improved fractal creating algorithm by symmetrical radius of k-M set. Meanwhile, we use distributed cooperative method to improve classic ETA into parallel system, which is called distributed cooperative ETA (DCETA). Secondly, we present the proof of fractal property in k-M set f(c) (z) = z(k) + c with exponent k (k < 0), which concludes its threshold and symmetrical property. Finally, computational result shows correctness of the novel DCETA, which shows better computational effectiveness and lower waste.
WVSN is a collective network of motes containing visual sensors. The nodes in the network are capable of acquiring, compressing, and transmitting successive images to the sink. To increase the lifetime of such network...
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WVSN is a collective network of motes containing visual sensors. The nodes in the network are capable of acquiring, compressing, and transmitting successive images to the sink. To increase the lifetime of such network, it is essential to reduce the amount of dataflow across the network without losing the integrity. This paper proposes a CS-based image transmission system to reduce the number of measurements required to represent the image. It utilizes a two-measurement matrix-based CS. TMM with CS leads to 2.8% to 6.7% and 0.67% to 7.9% reduction in the number of measurements compared to one MM-based CS while using DCT and binary DCT, respectively. Similarly, TMM with NUS CS leads to 5% to 40% ( DCT) and 1.4% to 20% ( binDCT) reduction in the number of measurements than one-measurement matrix-based NUS CS. An Enhanced Orthogonal Matching Pursuit algorithmis also proposed, which produces nearly 2% to 26% better recovery rate with the same number of measurements than the conventional OMP algorithm. Reduced measurements and better recovery rate achieved will enhance the lifetime of the WVSN, with considerable image quality. Rate distortion analysis of the proposed methodology is also done.
Recently underwater acoustic sensor networks (UASNs) have drawn much attention because of their great value in many underwater applications where human operation is hard to carry out. In this paper, we introduce and c...
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Recently underwater acoustic sensor networks (UASNs) have drawn much attention because of their great value in many underwater applications where human operation is hard to carry out. In this paper, we introduce and compare the performance of four localization algorithms in UASNs, namely, distance vector-hop (DV-hop), a new localization algorithm for underwater acoustic sensor networks (NLA), large-scale hierarchical localization (LSHL), and localization scheme for large scale underwater networks (LSLS). The four algorithms are all suitable for large-scale UASNs. We compare the localization algorithms in terms of localization coverage, localization error, and average energy consumption. Besides, we analyze the impacts of the ranging error and the number of anchor nodes on the performance of the localization algorithms. Simulations show that LSHL and LSLS perform much better than DV-hop and NLA in localization coverage, localization error, and average energy consumption. The performance of NLA is similar to that of the DV-hop. The advantage of DV-hop and NLA is that the localization results do not rely on the number of anchor nodes;that is, only a small number of anchor nodes are needed for localization.
This paper presents a lightweight data compression method for wireless sensor networks monitoring environmental parameters with low resolution sensors. Instead of attempting to devise novel ad hoc algorithms, we show ...
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This paper presents a lightweight data compression method for wireless sensor networks monitoring environmental parameters with low resolution sensors. Instead of attempting to devise novel ad hoc algorithms, we show that, given general knowledge of the parameters that must be monitored, it is possible to efficiently employ conventional Huffman coding to represent the same parameter when measured at different locations and time periods. When the data collected by the sensor nodes consists of integer measurements, the Huffman dictionary computed using statistics inferred from public datasets often approaches the entropy of the data. Results using temperature and relative humidity measurements show that even when the proposed method does not approach the theoretical limit, it outperforms popular compression mechanisms designed specifically for wireless sensor networks.
In vehicular ad hoc networks (VANETs), message dissemination to one or more vehicles is very challenging, due to frequent network disconnections and uncertain locations of the destination vehicles. Deploying roadside ...
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In vehicular ad hoc networks (VANETs), message dissemination to one or more vehicles is very challenging, due to frequent network disconnections and uncertain locations of the destination vehicles. Deploying roadside units (RSUs) is a possible solution to overcome the challenges, but it often requires a large amount of investment. In this paper, we propose the idea of Parking Backbone, which does not need any RSUs but leverages a virtual overlay network formed by outside parked vehicles to track vehicles and to disseminate messages between moving vehicles. Our scheme consists of three parts. At first, to each road, parked vehicles both at roadside and off street are grouped into a cluster as far as possible. An urban overlay network is established based on this type of clusters for data transmission. Secondly, to a specific vehicle, a daily mobility model is established, to determine its location through a corresponding location prediction algorithm. Finally, a novel message delivery scheme is designed to efficiently transmit messages to destination vehicles through the proposed virtual overlay network. Thanks to the extensive and stable outside parking in cities, once grouped into the overlay structure, data transmission can be easily achieved over the Parking Backbone. Extensive simulation results prove that our scheme achieves high performance in message dissemination.
Wireless sensor networks have grown rapidly with the innovation in Information Technology. Sensor nodes are distributed and deployed over the area for gathering requisite information. Sensor nodes possess a negative c...
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Wireless sensor networks have grown rapidly with the innovation in Information Technology. Sensor nodes are distributed and deployed over the area for gathering requisite information. Sensor nodes possess a negative characteristic of limited energy which pulls back the network from exploiting its peak capabilities. Hence, it is necessary to gather and transfer the information in an optimized way which reduces the energy dissipation. Ant Colony Optimization (ACO) is being widely used in optimizing the network routing protocols. Ant Based Routing can play a significant role in the enhancement of network life time. In this paper, Intercluster Ant Colony Optimization algorithm (IC-ACO) has been proposed that relies upon ACO algorithm for routing of data packets in the network and an attempt has been made to minimize the efforts wasted in transferring the redundant data sent by the sensors which lie in the close proximity of each other in a densely deployed network. The IC-ACO algorithm was studied by simulation for various network scenarios. The results depict the lead of IC-ACO as compared to LEACH protocol by indicating higher energy efficiency, prolonged network lifetime, enhanced stability period, and the elevated amount of data packets in a densely deployed wireless sensor network.
Distributed consensus in sensor networks has received great attention in the last few years. Most of the research activity has been devoted to study the sensor interactions that allow the convergence of distributed co...
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Distributed consensus in sensor networks has received great attention in the last few years. Most of the research activity has been devoted to study the sensor interactions that allow the convergence of distributed consensus algorithms toward a globally optimal decision. On the other hand, the problem of designing an appropriate radio interface enabling such interactions has received little attention in the literature. Motivated by the above consideration, in this work an ultrawideband sensor network is considered and a physical layer scheme is designed, which allows the active sensors to achieve consensus in a distributed manner without the need of any admission protocol. We focus on the class of the so-called quantized distributed consensus algorithms in which the local measurements or current states of each sensor belong to a finite set. Particular attention is devoted to address the practical implementation issues as well as to the development of a receiver architecture with the same performance of existing alternatives based on an all-digital implementation but with a much lower sampling frequency on the order of MHz instead of GHz.
The nonexistence of end-to-end path between the sender and the receiver poses great challenges to the successful message transmission in delay tolerant networks. Probabilistic routing provides an efficient scheme to r...
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The nonexistence of end-to-end path between the sender and the receiver poses great challenges to the successful message transmission in delay tolerant networks. Probabilistic routing provides an efficient scheme to route messages, but most existing probabilistic routing protocols do not consider whether a message has enough time-to-live to reach its destination. In this paper, we propose an improved probabilistic routing algorithm that fully takes into account message's time-to-live when predicting the delivery probability. Based on statistical analysis, we compute and update the expected intermeeting times between nodes. And then the probability for a message to be delivered within its time-to-live is computed based on the assumed exponential distribution. We further propose an optimal message schedule policy, by modeling the buffer management problem as 0-1 knapsack, of which the maximum delivery probability sum can be achieved by resorting to the back track technique. Extensive simulations are conducted and the results show that the proposed algorithm can greatly enhance routing performance in terms of message delivery probability, overhead ratio, and average hop count.
In the study of three-dimensional underwater sensor networks, the nodes would produce changes in perception range under the influence of environmental factors and their own hardware. Requesting all nodes completely is...
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In the study of three-dimensional underwater sensor networks, the nodes would produce changes in perception range under the influence of environmental factors and their own hardware. Requesting all nodes completely isomorphic is unrealistic. Ignoring boundary effects usually causes the coverage effect of the actual deployment of networks to not reach the anticipated result. This paper firstly presents an underwater sensing model with normal distributed node sensing radius. Secondly, it gives the relationship between expected deployment quality and the number of nodes in the premise of considering boundary effects. Then, it deduces nodes' redundancy formula based on the sensing model with normal distributed node sensing radius, making node could determine whether itself is a redundant node only based on the number of its neighbour nodes. Furthermore, this paper proposes a redundancy model and boundary effects based coverage-enhancing algorithm for three-dimensional underwater sensor networks (RBCT). Simulation results show that RBCT, compared to similar algorithms, has certain advantages in saving energy and enhancing coverage rate.
Most routing algorithms in delay tolerant networks (DTN) need nodes serving as relays for the source to carry and forward message. Due to the impact of selfishness, nodes have no incentive to stay in the network after...
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Most routing algorithms in delay tolerant networks (DTN) need nodes serving as relays for the source to carry and forward message. Due to the impact of selfishness, nodes have no incentive to stay in the network after getting message (e. g., free riders). To make them be cooperative at specific time, the source has to pay certain reward to them. In addition, the reward may be varying with time. On the other hand, the source can obtain certain benefit if the destination gets message timely. This paper considers the optimal incentive policy to get the best trade-off between the benefit and expenditure of the source for the first time. To cope with this problem, it first proposes a theoretical framework, which can be used to evaluate the trade-off under different incentive policies. Then, based on the framework, it explores the optimal control problem through Pontryagin's maximum principle and proves that the optimal policy conforms to the threshold formin certain cases. Simulations based on both synthetic and real motion traces show the accuracy of the framework. Through extensive numerical results, this paper demonstrates that the optimal policy obtained above is the best.
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