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An accurate detection of spectrum opportunities is a key factor in governing the efficient spectrum usage in a cognitive radio (CR) system. Energy detection based spectrum sensing has been widely used due to its ease of implementation with lower computational complexity; however, its robustness and performance are highly affected by the noise uncertainty. In the present work, a real time hardware...
For the upcoming IoT (Internet of things) era, plethora of data from a variety of sensors needs to be processed on a real time basis for improving system responsiveness. Due to the increasing modality of sensors, data streaming analytics to deal with high dimensional data becomes a critical ability. In addition, concept drift also needs to be addressed since an IoT-enabled environment is dynamic in...
The advancement of smartphones with various type of sensors enabled us to harness diverse information with crowd sensing mobile application. However, traditional approaches have suffered drawbacks such as high battery consumption as a trade off to obtain high accuracy data using high sampling rate. To mitigate the battery consumption, we proposed low sampling point of interest (POI) extraction framework,...
Energy consumption and lifetime of WSN are the most important research challenges to be resolved. For load balancing and efficient data collection in the network, clustering is used. Sensors in each cluster send the data to their corresponding cluster heads. The cluster head performs data aggregation and transmission of the aggregated data to the base station. Farther sensor nodes data are aggregated...
Energy efficiency has become a main challenge in Wireless Sensor Networks (WSNs) and their applications. Localization is one of the indispensable stages in WSN. Localization generally refers to the process of locating the position of one or more node(s) in a network. This paper develops and evaluates an improved energy aware localization algorithm in WSNs. Clustering techniques have been intensively...
This research arises from the need of equality in real life problems. Clustering algorithms are being used in many applications where equality is an interest, such as districting (either zonal or political) and industry (distribution companies). One of the well known clustering algorithms is Fuzzy clustering. We add an equality constraint to the existing model. We call the new optimization problem...
This paper proposes a new model to efficiently control cluster-heads using heterogeneous sensors in real-time. It also proposes a generic software framework to feasibly and efficiently meet the needs of the users and applications (e.g., reliability, energy efficiency). The proposed model and its method have been implemented and evaluated in Matlab, comparing its performance with known protocols for...
As it is the fact that sensors deployed in the field are not accessible after deployment hence lifetime of the network is directly dependent on residual energy the sensors have. Conservation and efficient utilization of energy are very crucial in a sensor network. Clustering is one of the best-accepted strategies to efficiently utilize energy. Various approaches are proposed in the literature for...
In past few years the use of Wireless Sensor Networks (WSNs) are increasing tremendously in different applications such as disaster management, security surveillance, border protection, combat field reconnaissance etc. Sensors are expected to deploy remotely in huge numbers and coordinate with each other where human attendant is not practically feasible. These tiny sensor nodes are operated by battery...
This research expands the scope of wireless sensor network (WSN) optimization from single objective to multi objective optimization. It introduces a WSN's energy-aware and coverage preserve hierarchal clustering and routing model based on multi-objective bat swarm optimization algorithm. Two objectives are taken into consideration; coverage and nodes residual energies. The proposed model optimizes...
Crowd sensing is an approach to collect many samples of a phenomena of interest by distributing the sampling across a large number of individuals. While any one individual may not provide sufficient samples, aggregating samples across many individuals may provide high-quality and high-coverage measurements of a phenomena. In this work, we propose an incentive assignment mechanism for crowd sensing...
One of the major components of Agent Based Crowd Simulation is motion planning. There have been various motion planning algorithms developed and they've become increasingly better and more efficient at calculating the most optimal path. We believe that this optimality is coming at the price of realism. Certain factors like social norms, limitations to human computation capabilities, etc. prevent humans...
Wireless sensor networks have become one of the most tempting networking technologies since it can be deployed without the need of a communication infrastructure. In general, there are some major concerns with this technology. That is, sensor node should have a long lasting system lifetime. And the system should keep the livability of nodes in a received level during the using process. In such systems...
Target tracking plays a critical role in the applications of wireless sensor networks. In this paper, we propose a target tracking algorithm based on Bayesian estimation, the key steps involved in the algorithm include target detection based on a probabilistic model, preliminary localization using the two-stage target locating algorithm, further prediction adopting Bayesian estimation. Simulation...
Many recent applications deal with continues flows of data (data streams). One important area of applications that is based on data streams is the area of Wireless Sensor Networks (WSNs) applications. Since sensors have limited lifetime, the need for developing algorithms for aggregating sensors' data forms an important concern in the area of WSNs. We present W-LEACH, a data-stream aggregation algorithm...
Wireless sensor networks are emerged as a new technology in different applications to get information from environment in recent years. On of the most important challenges in this type of networks is energy shortage of sensors. Where as energy restriction, it should be mentioned a fundamental solution to providence energy consumption. The most suitable solution is clustering. In this paper the clustering...
Industrial processes are characterized to be in open environments, with high uncertainty, unpredictability and nonlinear behavior. They have to be monitored and measured rigorously due to their behavior having a direct and serious impact on product quality, safety, productivity, pollution and finance. However, industrial processes have enormous volumes of complex and high dimensional data available,...
Wireless sensor networks are widely used for gathering data in an autonomous fashion. Since sensors are power constrained devices, it is quite important for them to minimize the energy consumption. In this paper we propose an energy efficient clustering scheme for self-organizing distributed wireless sensor networks. The proposed scheme self-selects the cluster head by a novel probability function...
The computational complexity of multi-dimension assignment algorithm, which can be used to solve multi-sensor multi-target location and tracking problem based on time difference of arrival (TDOA) measurements, will increase exponentially with the scale of assignment problem. By the fact that multiple emitters usually exist separately in the surveillance space, the clustering technique is used to partition...
A large Ad Hoc network can be represented as several sets of clusters. Each cluster contains one or more nodes and has its clusterhead (or caryomme) chosen following an election based on an appropriate criterion. The clustering in wireless networking adds scalability, reduces the computation complexity of routing protocols, allows data aggregation and then enhances the network performance. Several...
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