897 resultados para Flip and Saddle-node Bifurcation
Resumo:
We consider the problem of secure communication in mobile Wireless Sensor Networks (WSNs). Achieving security in WSNs requires robust encryption and authentication standards among the sensor nodes. Severe resources constraints in typical Wireless Sensor nodes hinder them in achieving key agreements. It is proved from past studies that many notable key management schemes do not work well in sensor networks due to their limited capacities. The idea of key predistribution is not feasible considering the fact that the network could scale to millions. We prove a novel algorithm that provides robust and secure communication channel in WSNs. Our Double Encryption with Validation Time (DEV) using Key Management Protocol algorithm works on the basis of timed sessions within which a secure secret key remains valid. A mobile node is used to bootstrap and exchange secure keys among communicating pairs of nodes. Analysis and simulation results show that the performance of the DEV using Key Management Protocol Algorithm is better than the SEV scheme and other related work.
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Network life time maximization is becoming an important design goal in wireless sensor networks. Energy harvesting has recently become a preferred choice for achieving this goal as it provides near perpetual operation. We study such a sensor node with an energy harvesting source and compare various architectures by which the harvested energy is used. We find its Shannon capacity when it is transmitting its observations over a fading AWGN channel with perfect/no channel state information provided at the transmitter. We obtain an achievable rate when there are inefficiencies in energy storage and the capacity when energy is spent in activities other than transmission.
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Opportunistic selection is a practically appealing technique that is used in multi-node wireless systems to maximize throughput, implement proportional fairness, etc. However, selection is challenging since the information about a node's channel gains is often available only locally at each node and not centrally. We propose a novel multiple access-based distributed selection scheme that generalizes the best features of the timer scheme, which requires minimal feedback but does not always guarantee successful selection, and the fast splitting scheme, which requires more feedback but guarantees successful selection. The proposed scheme's design explicitly accounts for feedback time overheads unlike the conventional splitting scheme and guarantees selection of the user with the highest metric unlike the timer scheme. We analyze and minimize the average time including feedback required by the scheme to select. With feedback overheads, the proposed scheme is scalable and considerably faster than several schemes proposed in the literature. Furthermore, the gains increase as the feedback overhead increases.
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In this paper, we study duty cycling and power management in a network of energy harvesting sensor (EHS) nodes. We consider a one-hop network, where K EHS nodes send data to a destination over a wireless fading channel. The goal is to find the optimum duty cycling and power scheduling across the nodes that maximizes the average sum data rate, subject to energy neutrality at each node. We adopt a two-stage approach to simplify the problem. In the inner stage, we solve the problem of optimal duty cycling of the nodes, subject to the short-term power constraint set by the outer stage. The outer stage sets the short-term power constraints on the inner stage to maximize the long-term expected sum data rate, subject to long-term energy neutrality at each node. Albeit suboptimal, our solutions turn out to have a surprisingly simple form: the duty cycle allotted to each node by the inner stage is simply the fractional allotted power of that node relative to the total allotted power. The sum power allotted is a clipped version of the sum harvested power across all the nodes. The average sum throughput thus ultimately depends only on the sum harvested power and its statistics. We illustrate the performance improvement offered by the proposed solution compared to other naive schemes via Monte-Carlo simulations.
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Energy harvesting sensor networks provide near perpetual operation and reduce carbon emissions thereby supporting `green communication'. We study such a sensor node powered with an energy harvesting source. We obtain energy management policies that are throughput optimal. We also obtain delay-optimal policies. Next we obtain the Shannon capacity of such a system. Further we combine the information theoretic and queuing theoretic approaches to obtain the Shannon capacity of an energy harvesting sensor node with a data queue. Then we generalize these results to models with fading and energy consumption in activities other than transmission.
Resumo:
Erasure codes are an efficient means of storing data across a network in comparison to data replication, as they tend to reduce the amount of data stored in the network and offer increased resilience in the presence of node failures. The codes perform poorly though, when repair of a failed node is called for, as they typically require the entire file to be downloaded to repair a failed node. A new class of erasure codes, termed as regenerating codes were recently introduced, that do much better in this respect. However, given the variety of efficient erasure codes available in the literature, there is considerable interest in the construction of coding schemes that would enable traditional erasure codes to be used, while retaining the feature that only a fraction of the data need be downloaded for node repair. In this paper, we present a simple, yet powerful, framework that does precisely this. Under this framework, the nodes are partitioned into two types and encoded using two codes in a manner that reduces the problem of node-repair to that of erasure-decoding of the constituent codes. Depending upon the choice of the two codes, the framework can be used to avail one or more of the following advantages: simultaneous minimization of storage space and repair-bandwidth, low complexity of operation, fewer disk reads at helper nodes during repair, and error detection and correction.
Resumo:
Erasure codes are an efficient means of storing data across a network in comparison to data replication, as they tend to reduce the amount of data stored in the network and offer increased resilience in the presence of node failures. The codes perform poorly though, when repair of a failed node is called for, as they typically require the entire file to be downloaded to repair a failed node. A new class of erasure codes, termed as regenerating codes were recently introduced, that do much better in this respect. However, given the variety of efficient erasure codes available in the literature, there is considerable interest in the construction of coding schemes that would enable traditional erasure codes to be used, while retaining the feature that only a fraction of the data need be downloaded for node repair. In this paper, we present a simple, yet powerful, framework that does precisely this. Under this framework, the nodes are partitioned into two types and encoded using two codes in a manner that reduces the problem of node-repair to that of erasure-decoding of the constituent codes. Depending upon the choice of the two codes, the framework can be used to avail one or more of the following advantages: simultaneous minimization of storage space and repair-bandwidth, low complexity of operation, fewer disk reads at helper nodes during repair, and error detection and correction.
Resumo:
Mobile ad-hoc network is a wireless ad-hoc network with dynamic network topology. The Dynamicity, due to the random node movement, and scarcity of resources lead to a challenge in monitoring the nodes in a MANET. Monitoring the lack of resources (bandwidth, buffer, and energy), misbehavior, and mobility at node level remains, a challenge. In a MANET the proposed protocol uses both static as well as mobile agents, where the mobile agents migrate to different clusters of the zones respectively, collect the node status information periodically, and provide a high level information to the static agent (which resides at the central node) by analyzing the raw information at the nodes. This, in turn, reduces the network traffic and conserves the workload of the central node, where a static agent is available with high level information and in coordination with other modules. The protocol has been tested in different size MANETs with variable number of nodes and applications. The results shown in the simulation indicates the effectiveness of the protocol.
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Multi-packet reception (MPR) promises significant throughput gains in wireless local area networks (WLANs) by allowing nodes to transmit even in the presence of ongoing transmissions in the medium. However, the medium access control (MAC) layer must now be redesigned to facilitate rather than discourage - these overlapping transmissions. We investigate asynchronous MPR MAC protocols, which successfully accomplish this by controlling the node behavior based on the number of ongoing transmissions in the channel. The protocols use the backoff timer mechanism of the distributed coordination function, which makes them practically appealing. We first highlight a unique problem of acknowledgment delays, which arises in asynchronous MPR, and investigate a solution that modifies the medium access rules to reduce these delays and increase system throughput in the single receiver scenario. We develop a general renewal-theoretic fixed-point analysis that leads to expressions for the saturation throughput, packet dropping probability, and average head-of-line packet delay. We also model and analyze the practical scenario in which nodes may incorrectly estimate the number of ongoing transmissions.
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An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.
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We consider the problem of joint routing, scheduling and power control in a multihop wireless network when the nodes have multiple antennas. We focus on exploiting the multiple degrees-of-freedom available at each transmitter and receiver due to multiple antennas. Specifically we use multiple antennas at each node to form multiple access and broadcast links in the network rather than just point to point links. We show that such a generic transmission model improves the system performance significantly. Since the complexity of the resulting optimization problem is very high, we also develop efficient suboptimal solutions for joint routing, scheduling and power control in this setup.
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Noninvasive or minimally invasive identification of sentinel lymph node (SLN) is essential to reduce the surgical effects of SLN biopsy. Photoacoustic (PA) imaging of SLN in animal models has shown its promise for clinical use in the future. Here, we present a Monte Carlo simulation for light transport in the SLN for various light delivery configurations with a clinical ultrasound probe. Our simulation assumes a realistic tissue layer model and also can handle the transmission/reflectance at SLN-tissue boundary due to the mismatch of refractive index. Various light incidence angles show that for deeply situated SLNs the maximum absorption of light in the SLN is for normal incidence. We also show that if a part of the diffused reflected photons is reflected back into the skin using a reflector, the absorption of light in the SLN can be increased significantly to enhance the PA signal. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)
Resumo:
Energy harvesting sensor (EHS) nodes provide an attractive and green solution to the problem of limited lifetime of wireless sensor networks (WSNs). Unlike a conventional node that uses a non-rechargeable battery and dies once it runs out of energy, an EHS node can harvest energy from the environment and replenish its rechargeable battery. We consider hybrid WSNs that comprise of both EHS and conventional nodes; these arise when legacy WSNs are upgraded or due to EHS deployment cost issues. We compare conventional and hybrid WSNs on the basis of a new and insightful performance metric called k-outage duration, which captures the inability of the nodes to transmit data either due to lack of sufficient battery energy or wireless fading. The metric overcomes the problem of defining lifetime in networks with EHS nodes, which never die but are occasionally unable to transmit due to lack of sufficient battery energy. It also accounts for the effect of wireless channel fading on the ability of the WSN to transmit data. We develop two novel, tight, and computationally simple bounds for evaluating the k-outage duration. Our results show that increasing the number of EHS nodes has a markedly different effect on the k-outage duration than increasing the number of conventional nodes.
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Regenerating codes are a class of codes proposed for providing reliability of data and efficient repair of failed nodes in distributed storage systems. In this paper, we address the fundamental problem of handling errors and erasures at the nodes or links, during the data-reconstruction and node-repair operations. We provide explicit regenerating codes that are resilient to errors and erasures, and show that these codes are optimal with respect to storage and bandwidth requirements. As a special case, we also establish the capacity of a class of distributed storage systems in the presence of malicious adversaries. While our code constructions are based on previously constructed Product-Matrix codes, we also provide necessary and sufficient conditions for introducing resilience in any regenerating code.
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We use information theoretic achievable rate formulas for the multi-relay channel to study the problem of optimal placement of relay nodes along the straight line joining a source node and a destination node. The achievable rate formulas that we utilize are for full-duplex radios at the relays and decode-and-forward relaying. For the single relay case, and individual power constraints at the source node and the relay node, we provide explicit formulas for the optimal relay location and the optimal power allocation to the source-relay channel, for the exponential and the power-law path-loss channel models. For the multiple relay case, we consider exponential path-loss and a total power constraint over the source and the relays, and derive an optimization problem, the solution of which provides the optimal relay locations. Numerical results suggest that at low attenuation the relays are mostly clustered close to the source in order to be able to cooperate among themselves, whereas at high attenuation they are uniformly placed and work as repeaters. We also prove that a constant rate independent of the attenuation in the network can be achieved by placing a large enough number of relay nodes uniformly between the source and the destination, under the exponential path-loss model with total power constraint.