Do you want to publish a course? Click here

Node Isolation Probability of Wireless Adhoc Networks in Nagakami Fading Channel

120   0   0.0 ( 0 )
 Publication date 2010
and research's language is English




Ask ChatGPT about the research

This paper investigates the issue of connectivity of a wireless adhoc network in the presence of channel impairments. We derive analytical expressions for the node isolation probability in an adhoc network in the presence of Nakagami-m fading with superimposed lognormal shadowing. The node isolation probability is the probability that a randomly chosen node is not able to communicate with none of the other nodes in the network. An extensive investigation into the impact of path loss exponent, lognormal shadowing, Nakagami fading severity index, node density, and diversity order on the node isolation probability is conducted. The presented results are beneficial for the practical design of ad hoc networks.



rate research

Read More

We propose a new class of algorithms for randomly scheduling network transmissions. The idea is to use (discrete) determinantal point processes (subsets) to randomly assign medium access to various {em repulsive} subsets of potential transmitters. This approach can be seen as a natural extension of (spatial) Aloha, which schedules transmissions independently. Under a general path loss model and Rayleigh fading, we show that, similarly to Aloha, they are also subject to elegant analysis of the coverage probabilities and transmission attempts (also known as local delay). This is mainly due to the explicit, determinantal form of the conditional (Palm) distribution and closed-form expressions for the Laplace functional of determinantal processes. Interestingly, the derived performance characteristics of the network are amenable to various optimizations of the scheduling parameters, which are determinantal kernels, allowing the use of techniques developed for statistical learning with determinantal processes. Well-established sampling algorithms for determinantal processes can be used to cope with implementation issues, which is is beyond the scope of this paper, but it creates paths for further research.
Multi-channel wireless networks are increasingly being employed as infrastructure networks, e.g. in metro areas. Nodes in these networks frequently employ directional antennas to improve spatial throughput. In such networks, given a source and destination, it is of interest to compute an optimal path and channel assignment on every link in the path such that the path bandwidth is the same as that of the link bandwidth and such a path satisfies the constraint that no two consecutive links on the path are assigned the same channel, referred to as Channel Discontinuity Constraint (CDC). CDC-paths are also quite useful for TDMA system, where preferably every consecutive links along a path are assigned different time slots. This paper contains several contributions. We first present an $O(N^{2})$ distributed algorithm for discovering the shortest CDC-path between given source and destination. This improves the running time of the $O(N^{3})$ centralized algorithm of Ahuja et al. for finding the minimum-weight CDC-path. Our second result is a generalized $t$-spanner for CDC-path; For any $theta>0$ we show how to construct a sub-network containing only $O(frac{N}{theta})$ edges, such that that length of shortest CDC-paths between arbitrary sources and destinations increases by only a factor of at most $(1-2sin{tfrac{theta}{2}})^{-2}$. We propose a novel algorithm to compute the spanner in a distributed manner using only $O(nlog{n})$ messages. An important conclusion of this scheme is in the case of directional antennas are used. In this case, it is enough to consider only the two closest nodes in each cone.
An efficient and fair node scheduling is a big challenge in multihop wireless networks. In this work, we propose a distributed node scheduling algorithm, called Local Voting. The idea comes from the finding that the shortest delivery time or delay is obtained when the load is equalized throughout the network. Simulation results demonstrate that Local Voting achieves better performance in terms of average delay, maximum delay, and fairness compared to several representative scheduling algorithms from the literature. Despite being distributed, Local Voting has a very close performance to a centralized algorithm that is considered to have the optimal performance.
With the tremendous advances of the wireless devices technology, securing wireless sensor networks became more and more a vital but also a challenging task. In this paper we propose an integrated strategy that is meant to discover malicious nodes within a sensor network and to expel them from the network using a node self-destruction procedure. Basically, we will compare every sensor reading with its estimated values provided by two predictors: an autoregressive predictor [1] that uses past values provided by the sensor under investigation and a neural predictor that uses past values provided by adjacent nodes. In case the absolute difference between the measured and the estimated values are greater then a chosen threshold, the sensor node becomes suspicious and a decision block is activated. If this block decides that the node is malicious, a self-destruction procedure will be started.
126 - Huy Nguyen , Gabriel Scalosub , 2013
Passive monitoring utilizing distributed wireless sniffers is an effective technique to monitor activities in wireless infrastructure networks for fault diagnosis, resource management and critical path analysis. In this paper, we introduce a quality of monitoring (QoM) metric defined by the expected number of active users monitored, and investigate the problem of maximizing QoM by judiciously assigning sniffers to channels based on the knowledge of user activities in a multi-channel wireless network. Two types of capture models are considered. The user-centric model assumes frame-level capturing capability of sniffers such that the activities of different users can be distinguished while the sniffer-centric model only utilizes the binary channel information (active or not) at a sniffer. For the user-centric model, we show that the implied optimization problem is NP-hard, but a constant approximation ratio can be attained via polynomial complexity algorithms. For the sniffer-centric model, we devise stochastic inference schemes to transform the problem into the user-centric domain, where we are able to apply our polynomial approximation algorithms. The effectiveness of our proposed schemes and algorithms is further evaluated using both synthetic data as well as real-world traces from an operational WLAN.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا