One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT.

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In this paper, an energy efficient inter cluster coordination protocol developed for the wireless sensor networks has been proposed. By controlling the topology, longevity and the scalability of the network can be increased. Clustering sensor node is an effective topology for the energy constrained networks. So cluster based algorithm has been developed in which different levels of clusters are considered on the basis of received signal strength to recognize the distance of the clusters from the BS (base station) and to determine the number of cluster coordinators to make routes for the CHs to transmit the data. Based on the investigation of existing protocols in which cluster heads send data directly to the base station, it is found that direct transmission by the CHs is not an optimal solution and dissipates a lot of energy, so in this paper a novel EEICCP (Energy efficient inter cluster coordination) protocol has been proposed which evenly distributes the energy load among the sensor nodes and use the multi hop approach for the CHs. Analytical model of new protocol is projected and the algorithm is implemented in MATLAB. Moreover, EEICCP has shown remarkable improvement over already existing LEACH and HCR protocols in terms of reliability and stability. Our work has also been validated through the simulation results.

Detection of Earth surface changes are essential to monitor regional climatic, snow avalanche hazard analysis and energy balance studies that occur due to air temperature irregularities. Geographic Information System (GIS) enables such research activities to be carried out through change detection analysis. From this viewpoint, different change detection algorithms have been developed for land-use land-cover (LULC) region. Among the different change detection algorithms, change vector analysis (CVA) has level headed capability of extracting maximum information in terms of overall magnitude of change and the direction of change between multispectral bands from multi-temporal satellite data sets. Since past two-three decades, many effective CVA based change detection techniques e.g., improved change vector analysis (ICVA), modified change vector analysis (MCVA) and change vector analysis posterior-probability space (CVAPS), have been developed to overcome the difficulty that exists in traditional change vector analysis (CVA). Moreover, many integrated techniques such as cross correlogram spectral matching (CCSM) based CVA. CVA uses enhanced principal component analysis (PCA) and inverse triangular (IT) function, hyper-spherical direction cosine (HSDC), and median CVA (m-CVA), as an effective LULC change detection tools. This paper comprises a comparative analysis on CVA based change detection techniques such as CVA, MCVA, ICVA and CVAPS. This paper also summarizes the necessary integrated CVA techniques along with their characteristics, features and shortcomings. Based on experiment outcomes, it has been evaluated that CVAPS technique has greater potential than other CVA techniques to evaluate the overall transformed information over three different MODerate resolution Imaging Spectroradiometer (MODIS) satellite data sets of different regions. Results of this study are expected to be potentially useful for more accurate analysis of LULC changes which will, in turn, improve the utilization of CVA based change detection techniques for such applications. * For correspondence 1311 1312 Sartajvir Singh and Rajneesh TalwarKeywords. Change vector analysis (CVA); improved change vector analysis (ICVA); modified change vector analysis (MCVA); change vector analysis posteriorprobability space (CVAPS).