A combined algorithm is required to select an optimal impediments like obstructions, line of sight constraints etc, set of sensors, satisfying the conditions of coverage and multiple sensor nodes are essential in several cases. For either connectivity. Since topological changes have significant impact on energy or communication, the environment to be observed the coverage quality, there is a need for dynamic coverage does not possess an offered infrastructure in the majority maintenance algorithms. In this paper, an energy efficient cases. Staying alive on minute, finite sources of energy and distributed connected coverage (EEDCC) algorithm and a set of communicating through a wireless communication channel [2] dynamic coverage maintenance (DCM) algorithms have been become essential for sensor nodes.proposed. EEDCC aims to reduce the energy consumption with a lower communication overhead. The DCM algorithms aid in the Distributed processing capability would be an additional tracking of changes in network topology thereby addressing the necessity for sensor networks. As communication is a issues related to dynamic coverage and loss recovery. These foremost consumer of energy, this is essential. The sensors algorithms would assist in the adaptive maintenance of the may need to communicate over long distances in case of a coverage either by migrating sensor node or by updating the centralized algorithm, which may lead to further energy radii accordingly. Simulations results show that the EEDCCdepletion.DCM algorithms attain significant reduction of energy, with strong connectivity and coverage. For this reason, so as to diminish the whole amount of bits broadcasted, it would be an excellent thought to process in the Keywords-Sensor; Coverage; Energy; Recovery; Connectivity. neighborhood as much information as achievable.
WiMAX networks are deployed for commercial use because of its nature high bandwidth. This requirement invokes the application level changes in QoS provisioning techniques. The objective of the broadband wireless technologies is to ensure the end to end Quality of Service (QoS) for the service classes. WiMAX is a revolution in wireless networks, which could support real time multimedia services. In order to provide QoS support and efficient usage of system resources an intelligent scheduling algorithm is needed. The design of the detailed scheduling algorithm is a major focus for researchers and service providers. In this study, a channel aware cross-layer scheduling algorithm for WiMAX networks has been proposed. This scheme employs the Signal to Noise Ratio (SNR) value, which allocates the bandwidth based on the information about the quality of the channel and the service requirements of each connection. The proposed algorithm is described in detail and evaluated, through a series of simulations. The QoS parameters of throughput, bandwidth efficiency and transmission efficiency have been measured in simulation.
In Wireless Sensor Networks (WSN), sensor node deployment is essential for maximizing the coverage and detection probabilities. But the existing optimization solution suffers from limited energy storage, node death, increased network traffic etc. To solve these issues, we propose a fuzzy based optimization model for power management in wireless sensor networks. The objectives considered in the paper include maximizing network coverage, connectivity, network lifetime and minimizing traffic load. A fuzzy rules table is constructed with the input parameters such as node degree, link quality, residual energy and traffic rate. Depending upon the outcome of the fuzzy logic, the nodes are categorized into good, normal and bad. After the initial deployment of good nodes, the SLEEP and WAKEUP Procedure is applied to maximize the lifetime of wireless sensor networks. By putting nodes to sleep when there are no events, the energy consumption of the sensor nodes can be significantly reduced. In SLEEP and WAKEUP Procedure, asynchronous type is used; it allows each node in the wireless sensor network to set its own SLEEP and WAKEUP schedule independently in order to save energy. Simulation result shows that the proposed Procedure provides maximization of the lifetime of Wireless Sensor Network (WSN). INTRODUCTIONWireless sensor networks (WSN) helps in sensing or monitoring physical or environment conditions since the network has distributed autonomous nodes. Sensor nodes consist of one or more sensors, a radio transceiver, a microcontroller and an energy source. Currently WSN has fascinated more number of research interests which is due to potential applications in many areas ranging from environmental observation, natural habitat monitoring, medical, industry and military applications. Searching and developing potentials are essential for formation of multiple mobile sensor nodes in the sensor network. The entire monitoring environment needs to be covered by the mobile sensor nodes using the searching potentials of the sensor network. For the region where concentrated monitoring is essential the sensor nodes are joined using the developing potentials of the sensor network. A novel deployment strategy is required to maximize both the potentials of the sensor networks. Depending upon the coverage of each point in the sensing field, the sensors provide better QoS.[1]The maximum network coverage needs to be achieved by effectively deploying the sensors in an appropriate manner. Energy efficient protocols are aimed at minimizing the energy consumption during network activities. However, a large amount of energy is consumed by node components (CPU, radio, etc.) even if they are idle. Energy or power management schemes are thus used for switching off node components that are not temporarily needed. Several energy conservation schemes have been proposed. They are mainly aimed at minimizing the energy consumption of the communication subsystem.[2]There are two main approaches to energy conservation in-network processing and p...
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