95 resultados para routing in wireless sensor networks.
Resumo:
We address the problem of passive eavesdroppers in multi-hop wireless networks using the technique of friendly jamming. The network is assumed to employ Decode and Forward (DF) relaying. Assuming the availability of perfect channel state information (CSI) of legitimate nodes and eavesdroppers, we consider a scheduling and power allocation (PA) problem for a multiple-source multiple-sink scenario so that eavesdroppers are jammed, and source-destination throughput targets are met while minimizing the overall transmitted power. We propose activation sets (AS-es) for scheduling, and formulate an optimization problem for PA. Several methods for finding AS-es are discussed and compared. We present an approximate linear program for the original nonlinear, non-convex PA optimization problem, and argue that under certain conditions, both the formulations produce identical results. In the absence of eavesdroppers' CSI, we utilize the notion of Vulnerability Region (VR), and formulate an optimization problem with the objective of minimizing the VR. Our results show that the proposed solution can achieve power-efficient operation while defeating eavesdroppers and achieving desired source-destination throughputs simultaneously. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
Mobile Ad hoc Networks (MANETs) are self-organized, infrastructureless, decentralized wireless networks consist of a group of heterogeneous mobile devices. Due to the inherent characteristics of MANE -Ts, such as frequent change of topology, nodes mobility, resource scarcity, lack of central control, etc., makes QoS routing is the hardest task. QoS routing is the task of routing data packets from source to destination depending upon the QoS resource constraints, such as bandwidth, delay, packet loss rate, cost, etc. In this paper, we proposed a novel scheme of providing QoS routing in MANETs by using Emergent Intelligence (El). The El is a group intelligence, which is derived from the periodical interaction among a group of agents and nodes. We logically divide MANET into clusters by centrally located static agent, and in each cluster a mobile agent is deployed. The mobile agent interacts with the nodes, neighboring mobile agents and static agent for collection of QoS resource information, negotiations, finding secure and reliable nodes and finding an optimal QoS path from source to destination. Simulation and analytical results show that the effectiveness of the scheme. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.ore/licenscs/by-nc-nd/4.0/). Peer-review under responsibility of the Conference Program Chairs
Resumo:
We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.
Resumo:
The differential encoding/decoding setup introduced by Kiran et at, Oggier et al and Jing et al for wireless relay networks that use codebooks consisting of unitary matrices is extended to allow codebooks consisting of scaled unitary matrices. For such codebooks to be used in the Jing-Hassibi protocol for cooperative diversity, the conditions that need to be satisfied by the relay matrices and the codebook are identified. A class of previously known rate one, full diversity, four-group encodable and four-group decodable Differential Space-Time Codes (DSTCs) is proposed for use as Distributed DSTCs (DDSTCs) in the proposed set up. To the best of our knowledge, this is the first known low decoding complexity DDSTC scheme for cooperative wireless networks.
Resumo:
We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology.
Resumo:
This paper considers the problem of spectrum sensing, i.e., the detection of whether or not a primary user is transmitting data by a cognitive radio. The Bayesian framework is adopted, with the performance measure being the probability of detection error. A decentralized setup, where N sensors use M observations each to arrive at individual decisions that are combined at a fusion center to form the overall decision is considered. The unknown fading channel between the primary sensor and the cognitive radios makes the individual decision rule computationally complex, hence, a generalized likelihood ratio test (GLRT)-based approach is adopted. Analysis of the probabilities of false alarm and miss detection of the proposed method reveals that the error exponent with respect to M is zero. Also, the fusion of N individual decisions offers a diversity advantage, similar to diversity reception in communication systems, and a tight bound on the error exponent is presented. Through an analysis in the low power regime, the number of observations needed as a function of received power, to achieve a given probability of error is determined. Monte-Carlo simulations confirm the accuracy of the analysis.
Resumo:
A wireless Energy Harvesting Sensor (EHS) needs to send data packets arriving in its queue over a fading channel at maximum possible throughput while ensuring acceptable packet delays. At the same time, it needs to ensure that energy neutrality is satisfied, i.e., the average energy drawn from a battery should equal the amount of energy deposited in it minus the energy lost due to the inefficiency of the battery. In this work, a framework is developed under which a system designer can optimize the performance of the EHS node using power control based on the current channel state information, when the EHS node employs a single modulation and coding scheme and the channel is Rayleigh fading. Optimal system parameters for throughput optimal, delay optimal and delay-constrained throughput optimal policies that ensure energy neutrality are derived. It is seen that a throughput optimal (maximal) policy is packet delay-unbounded and an average delay optimal (minimal) policy achieves negligibly small throughput. Finally, the influence of the harvested energy profile on the performance of the EHS is illustrated through the example of solar energy harvesting.
Resumo:
We study the trade-off between delivery delay and energy consumption in delay tolerant mobile wireless networks that use two-hop relaying. The source may not have perfect knowledge of the delivery status at every instant. We formulate the problem as a stochastic control problem with partial information, and study structural properties of the optimal policy. We also propose a simple suboptimal policy. We then compare the performance of the suboptimal policy against that of the optimal control with perfect information. These are bounds on the performance of the proposed policy with partial information. Several other related open loop policies are also compared with these bounds.
Resumo:
We propose partial and full link reversal algorithms to bypass voids during geographic routing over duty-cycled wireless sensor networks. We propose a distributed approach that is oblivious to one-hop neighbor information. Upon termination of the algorithm, the resulting network is guaranteed to be destination-oriented. Further, to reduce the delays incurred under reactive link reversal, we propose the use of `pseudo-events', a preemptive link reversal strategy, that renders the network destination-oriented before the onset of a real event. A simulation study of the effectiveness of pseudo-events is also provided.
Resumo:
This paper presents the capability of the neural networks as a computational tool for solving constrained optimization problem, arising in routing algorithms for the present day communication networks. The application of neural networks in the optimum routing problem, in case of packet switched computer networks, where the goal is to minimize the average delays in the communication have been addressed. The effectiveness of neural network is shown by the results of simulation of a neural design to solve the shortest path problem. Simulation model of neural network is shown to be utilized in an optimum routing algorithm known as flow deviation algorithm. It is also shown that the model will enable the routing algorithm to be implemented in real time and also to be adaptive to changes in link costs and network topology. (C) 2002 Elsevier Science Ltd. All rights reserved.
Resumo:
An analog minimum-variance unbiased estimator(MVUE) over an asymmetric wireless sensor network is studied.Minimisation of variance is cast into a constrained non-convex optimisation problem. An explicit algorithm that solves the problem is provided. The solution is obtained by decomposing the original problem into a finite number of convex optimisation problems with explicit solutions. These solutions are then juxtaposed together by exploiting further structure in the objective function.
Resumo:
We study the trade-off between delivery delay and energy consumption in a delay tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the packet and the number of destinations that have received the packet. We formulate the problem as a controlled continuous time Markov chain and derive the optimal closed loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ODE (i.e., fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed loop policy.
Resumo:
The key problem tackled in this paper is the development of a stand-alone self-powered sensor to directly sense the spectrum of mechanical vibrations. Such a sensor could be deployed in wide area sensor networks to monitor structural vibrations of large machines (e. g. aircrafts) and initiate corrective action if the structure approaches resonance. In this paper, we study the feasibility of using stretched membranes of polymer piezoelectric polyvinlidene fluoride for low-frequency vibration spectrum sensing. We design and evaluate a low-frequency vibration spectrum sensor that accepts an incoming vibration and directly provides the spectrum of the vibration as the output.
Resumo:
A power scalable receiver architecture is presented for low data rate Wireless Sensor Network (WSN) applications in 130nm RF-CMOS technology. Power scalable receiver is motivated by the ability to leverage lower run-time performance requirement to save power. The proposed receiver is able to switch power settings based on available signal and interference levels while maintaining requisite BER. The Low-IF receiver consists of Variable Noise and Linearity LNA, IQ Mixers, VGA, Variable Order Complex Bandpass Filter and Variable Gain and Bandwidth Amplifier (VGBWA) capable of driving variable sampling rate ADC. Various blocks have independent power scaling controls depending on their noise, gain and interference rejection (IR) requirements. The receiver is designed for constant envelope QPSK-type modulation with 2.4GHz RF input, 3MHz IF and 2MHz bandwidth. The chip operates at 1V Vdd with current scalable from 4.5mA to 1.3mA and chip area of 0.65mm2.