A maximum-votes and load-balance clustering algorithm(VLCA) for wireless sensor network was proposedThe algorithm is completely distributed,and independent of network size and topologySimulation results show that the VLCA can reduce the number of clusters by 20%-50% and prolong the lifetime of a sensor network

Energy-efficient clustering algorithm for wireless sensor networks

Cognitive radio is a promising technique for efficient utilization of idle authorized spectrum since it is able to sense the spectrum and reuse the frequency when the primary user is absent. In order to overcome the fading, shadowing or hidden terminals in independent detection, cooperative detection is presented. The performance of cooperative sensing is studied in this paper. To enhance the sensing ability, some weighted-cooperative spectrum sensing techniques have been proposed. In this paper, different from the previous studies, we propose a novel weighted-clustering cooperative spectrum sensing algorithm based on distances for cognitive radio network. We firstly classify the secondary users into a few clusters according to several existent methods, and then use cluster-head to collect the observation results come from different secondary users in the same cluster and make a cluster-decision. Considering the different distances between the clusters and the fusion center, different weightings are used to weight the cluster- decisions before combining. The simulation results show that our proposed method improve the probability of detection and reduce the probability of error.

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Cooperative Spectrum Sensing and Weighted- Clustering Algorithm for Cognitive Radio Network

Wireless sensor nodes become more and more attractive for a broad variety of application scenarios. Wireless Sensor Networks WSNs can be easily deployed and they require by design low maintenance effort. But running installations are still rare, because real world requirements and environmental conditions are even today a big challenge. Especially in multi-hop networks a minimum lifetime of several years cannot be achieved globally. In this paper, the authors present a Distributed Low Duty Cycle DLDC based Multi-Hop Routing MHR protocol for Wireless Sensor Networks guaranteeing a minimum network lifetime. The authors introduce a forecast scheme to calculate the expected life of a node with a minimal effort. The authors are convinced that by using a forecast scheme the network topology and the used protocols can be easily optimized before deploying the network. The authors evaluated their forecast scheme by measuring real sensor node parameters and simulating an example network in the Castalia simulation framework. The authors demonstrated that by using the proposed scheme an energy consumption forecast with a deviation of less than three per cent can be achieved.

A Lifetime Forecast Scheme for a Distributed Low Duty Cycle Multi-Hop Routing in Wireless Sensor Networks

Wireless sensor networks become more and more attractive for a broad variety of application scenarios. Wireless Sensor Network (WSN)s are cheap and can be easily deployed as well as that they require by design low maintenance effort. But running installations are still rare, because real world requirements and environmental conditions are even today a big challenge. Especially in multi-hop networks a minimum lifetime of several years can not be achieved globally. In this paper, we present a Fair Energy Trade Multi-Hop Routing (FET-MHR) protocol for Wireless Sensor Networks guaranteeing a minimum network lifetime. We introduce a routing metric that implements a fair energy trade among all nodes. Nodes with low energy resources and links with a bad quality index are avoided. By that we take into account the energy spent for sending in the past (low battery) as well as energy needed for sending in the future (bad link quality). Considering both aspects when selecting routing paths including their metrics helps increasing the node's lifetime significantly. We evaluated our protocol in simulations and compared it with various existing routing metrics. We demonstrate that our protocol can achieve better lifetimes for sparse and for dense network setups.

A fair energy trade multi-hop routing in wireless sensor networks

Networks-on-Chips (NoCs) consume the large fraction of the whole system energy budget. Three-dimensional NoCs overcome the communication demands as a viable architecture in many-core systems, outperform 2D NoCs in terms of area, latency, performance and scalability, however, 3D NoCs consume high power even more than 2D NoCs. Using the voltage scaling technique in routers and links can significantly improve energy saving. Unfortunately, voltage level reduction compromises the latency and the communication reliability. As emerging applications can tolerate inaccuracy in the output and due to the latency reduction in 3D NoCs, Dynamic Voltage Scaling (DVS) technique is applied to the links and routers of 3D NoC in facing with error tolerance communications. Therefore, energy efficiency and the performance are significantly improved in 3D NoC while outputs are within an acceptable variance. Simulation results indicate that the described method improves on average the energy efficiency 27% across different PARSEC benchmarks.

Energy Optimization in 3D Networks-on-Chip through Dynamic Voltage Scaling technique

The wireless sensor network is an autonomous collection of sensors which makes a simple, high speed and inexpensive network. These kinds of network are able to monitor a parameter where the coverage is impossible via wired networks. Since, the sensors in wireless networks are equipped with batteries, these networks are energy constrained and clustering approaches play an important role in energy efficiency and prolonging network's lifetime. In this paper, an energy efficient algorithm is presented for wireless sensor networks. EECMT (Energy Efficient Clustering with Multi-hop Transmission) employs the wireless sensor network's characteristics. In addition to energy consumption, load balancing and network's scalability have been taken into account. Simulation results illustrate that network's lifetime has been optimized to 86% in clustered sensor networks.

Energy Efficient Clustering Algorithm with Multi-hop Transmission

Wireless sensor networks are simple, high speed and inexpensive networks that include large number of sensors. These networks are able to monitor a parameter where the coverage is impossible via wired networks. Since clustering improves energy consumption, clustering algorithms aim at this improvement. In this paper, an energy efficient algorithm entitled EECDP (Energy Efficient Clustering with Direct Paths) is presented for wireless sensor networks. EECDP employs the wireless sensor network's characteristics. Simulation results illustrate that network's lifetime has been optimized to 18.5% in clustered sensor networks.

Mona Shemshaki

Papers

Energy Efficient Clustering Algorithm with Multi-hop Transmission

Energy Efficient Clustering Algorithm with Direct Path Supports