Improved energy aware cluster based data routing scheme for WSN

Wireless sensor network (WSN) consists of several tiny devices that are dispersed randomly for gathering network field. Clustering mechanism divides the WSN into different sub-regions called clusters. Individual cluster is consisting of cluster head (CH) and member nodes. The main research challenges behind clustering mechanism are to optimize network overheads with efficient data delivery. Sensor nodes are operated by batteries and practically it is not feasible to replace them during sensing the environment so energy should be effectively utilized among sensors for improving overall network performance. This research paper presents an improved energy aware cluster based data routing (i-ECBR) scheme, by dividing the network regions into uniform sized square partitions and localized CH election mechanism. In addition, consistent end-to-end data routing is performed for improving data dissemination. Simulation results illustrate that our proposed scheme outperforms than existing work in terms of different performance metrics

Improved Energy Aware Cluster based Data Routing Scheme for WSN

Wireless sensor network (WSN) consists of several tiny devices that are dispersed randomly for gathering network field. Clustering mechanism divides the WSN into different sub-regions called clusters. Individual cluster is consisting of cluster head (CH) and member nodes. The main research challenges behind clustering mechanism are to optimize network overheads with efficient data delivery. Sensor nodes are operated by batteries and practically it is not feasible to replace them during sensing the environment so energy should be effectively utilized among sensors for improving overall network performance. This research paper presents an improved energy aware cluster based data routing (i-ECBR) scheme, by dividing the network regions into uniform sized square partitions and localized CH election mechanism. In addition, consistent end-to-end data routing is performed for improving data dissemination. Simulation results illustrate that our proposed scheme outperforms than existing work in terms of different performance metrics

Energy-Efficient Multi-Level and Distance-Aware Clustering Mechanism for WSNs

[EN] Most sensor networks are deployed at hostile environments to sense and gather specific information. As sensor nodes have battery constraints, therefore, the research community is trying to propose energyefficient solutions for wireless sensor networks (WSNs) to prolong the lifetime of the network. In this paper, we propose an energy-efficient multi-level and distance-aware clustering (EEMDC) mechanism for WSNs. In this mechanism, the area of the network is divided into three logical layers, which depends upon the hop-count-based distance from the base station. The simulation outcomes show that EEMDC is more energy efficient than other existing conventional approaches.This work has been partially supported by the 'Ministerio de Ciencia e Innovacion', through the 'Plan Nacional de I+D+i 2008-2011' in the 'Subprograma de Proyectos de Investigacion Fundamental', project TEC2011-27516, and by the Polytechnic University of Valencia, through the PAID-15-11 multidisciplinary projectsMehmood, A.; Khan, S.; Shams, B.; Lloret, J. (2015). Energy-Efficient Multi-Level and Distance-Aware Clustering Mechanism for WSNs. International Journal of Communication Systems. 28(5):972-989. https://doi.org/10.1002/dac.2720S972989285Sendra, S., Lloret, J., Garcia, M., & Toledo, J. F. (2011). Power Saving and Energy Optimization Techniques for Wireless Sensor Neworks (Invited Paper). 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Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Analyzing Energy-efficiency and Route-selection of Multi-level Hierarchal Routing Protocols in WSNs

The advent and development in the field of Wireless Sensor Networks (WSNs) in recent years has seen the growth of extremely small and low-cost sensors that possess sensing, signal processing and wireless communication capabilities. These sensors can be expended at a much lower cost and are capable of detecting conditions such as temperature, sound, security or any other system. A good protocol design should be able to scale well both in energy heterogeneous and homogeneous environment, meet the demands of different application scenarios and guarantee reliability. On this basis, we have compared six different protocols of different scenarios which are presenting their own schemes of energy minimizing, clustering and route selection in order to have more effective communication. This research is motivated to have an insight that which of the under consideration protocols suit well in which application and can be a guide-line for the design of a more robust and efficient protocol. MATLAB simulations are performed to analyze and compare the performance of LEACH, multi-level hierarchal LEACH and multihop LEACH.Comment: NGWMN with 7th IEEE Inter- national Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2012), Victoria, Canada, 201

M-GEAR: Gateway-Based Energy-Aware Multi-Hop Routing Protocol for WSNs

In this research work, we advise gateway based energy-efficient routing protocol (M-GEAR) for Wireless Sensor Networks (WSNs). We divide the sensor nodes into four logical regions on the basis of their location in the sensing field. We install Base Station (BS) out of the sensing area and a gateway node at the centre of the sensing area. If the distance of a sensor node from BS or gateway is less than predefined distance threshold, the node uses direct communication. We divide the rest of nodes into two equal regions whose distance is beyond the threshold distance. We select cluster heads (CHs)in each region which are independent of the other region. These CHs are selected on the basis of a probability. We compare performance of our protocol with LEACH (Low Energy Adaptive Clustering Hierarchy). Performance analysis and compared statistic results show that our proposed protocol perform well in terms of energy consumption and network lifetime.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc