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In this paper, we discuss the design of a new Medium Access Control (MAC) protocol, SRI-MAC (Synchronous Receiver Initiated MAC), for wireless sensor networks whose goal is to extend the lifetime of the network by avoiding major energy waste causes, such as collisions, overhearing and idle listening.  相似文献   
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Energy efficiency and Quality of Service (QoS) providing are known to be critical design concerns in routing protocols for Wireless Sensor Networks (WSNs). Recent studies, demonstrate that Opportunistic Routing (OR) can greatly improve the performance of WSNs by exploiting the broadcast nature of the wireless medium. In this paper, we propose a new QoS aware and Energy efficient Opportunistic Routing protocol (QEOR) to efficiently routing data under QoS and energy constraints for WSNs. QEOR uses a new multi-metric QoS based candidate selection method in order to accurately select and prioritise the candidate forwarders. The selection is focused on a QoS function that takes into consideration the reliabilty of buffers and links, while the prioritisation is established according to transmission delays. To achieve an obvious improvement on the energy consumption, QEOR uses an energy efficient coordination method and an implicit ACKnowledgement scheme for collision and redundancy avoidance. Simulation results show that QEOR provides best performances as compared to other OR protocols.  相似文献   
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The energy consumption is a key design criterion for the routing protocols in wireless sensor networks (WSN). Some of the conventional single path routing schemes may not be optimal to maximize the network lifetime and connectivity. Thus, multipath routing schemes is an optimal alternative to extend the lifetime of WSN. Multipath routing schemes distribute the traffic across multiple paths instead of routing all the traffic along a single path. In this paper, we propose a multipath Energy-Efficient data Routing Protocol for wireless sensor networks (EERP). The latter keeps a set of good paths and chooses one based on the node state and the cost function of this path. In EERP, each node has a number of neighbours through which it can route packets to the base station. A node bases its routing decision on two metrics: state and cost function. It searches its Neighbours Information Table for all its neighbours concerned with minimum cost function. Simulation results show that our EERP protocol minimizes and balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime.  相似文献   
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In Wireless Sensor Networks, node localization is one of the most important system parameters. Determining the exact position of nodes in these networks is one of vital and tedious tasks. This paper presents a review of the most localization methods which optimize the localization error. It provides a new taxonomy of techniques used in this field, including Mobile Anchor, Machine Learning, Matematical Models and Meta-heuristics. In this later, we survey its different algorithms such as Genetic Algorithm, Particle Swarm optimization, Ant Colony Optimization, BAT optimization algorithm, Firefly Optimization Algorithm, Flower Pollination Algorithm, Grey Wolf Optimization algorithm, Artificial Bees Colony Optimization Algorithm, Fish Swarm Optimization Algorithm and others. Further, the comparison between these metaheuristics algorithms based localization optimization is done. Finally, a comprehensive discussion of the performance parameters such as accuracy, convergence rate, energy consumption and the number of localized nodes is given.

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