Energy-Efficient Load Balancing Ant Based Routing Algorithm for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are a type of self-organizing networks with limited energy supply and communication ability. One of the most crucial issues in WSNs is to use an energy-efficient routing protocol to prolong the network lifetime. We therefore propose the novel Energy-Efficient Load Balancing Ant-based Routing Algorithm (EBAR) for WSNs. EBAR adopts a pseudo-random route discovery algorithm and an improved pheromone trail update scheme to balance the energy consumption of the sensor nodes. It uses an efficient heuristic update algorithm based on a greedy expected energy cost metric to optimize the route establishment. Finally, in order to reduce the energy consumption caused by the control overhead, EBAR utilizes an energy-based opportunistic broadcast scheme. We simulate WSNs in different application scenarios to evaluate EBAR with respect to performance metrics such as energy consumption, energy efficiency, and predicted network lifetime. The results of this comprehensive study show that EBAR provides a significant improvement in comparison to the state-of-the-art approaches EEABR, SensorAnt, and IACO

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

From carbon nanotubes and silicate layers to graphene platelets for polymer nanocomposites

In spite of extensive studies conducted on carbon nanotubes and silicate layers for their polymer-based nanocomposites, the rise of graphene now provides a more promising candidate due to its exceptionally high mechanical performance and electrical and thermal conductivities. The present study developed a facile approach to fabricate epoxy–graphene nanocomposites by thermally expanding a commercial product followed by ultrasonication and solution-compounding with epoxy, and investigated their morphologies, mechanical properties, electrical conductivity and thermal mechanical behaviour. Graphene platelets (GnPs) of 3.5

Improved Fair-Zone technique using Mobility Prediction in WSN

The self-organizational ability of ad-hoc Wireless Sensor Networks (WSNs) has led them to be the most popular choice in ubiquitous computing. Clustering sensor nodes organizing them hierarchically have proven to be an effective method to provide better data aggregation and scalability for the sensor network while conserving limited energy. It has some limitation in energy and mobility of nodes. In this paper we propose a mobility prediction technique which tries overcoming above mentioned problems and improves the life time of the network. The technique used here is Exponential Moving Average for online updates of nodal contact probability in cluster based network.Comment: 10 pages, 7 figures, Published in International Journal Of Advanced Smart Sensor Network Systems (IJASSN

Energy distribution control in wireless sensor networks through range optimization

A major objective in wireless sensor networks is to find optimum routing strategies for energy efficient use of nodes. Routing decision and transmission power selection are intrinsically connected since the transmission power of a node is adjusted depending on the location of the next hop. In this paper, we propose a location-based routing framework to control the energy distribution in a network where transmission ranges, hence powers, of nodes are determined based on their locations. We show that the proposed framework is sufficiently general to investigate the minimum-energy and maximum-lifetime routing problems. It is shown that via the location based strategy the network lifetime can be improved by 70% and the total energy consumption can be decreased to three-fourths to one-third of the constant transmission range strategy depending on the propagation medium and the size of the network

On Modeling Geometric Joint Sink Mobility with Delay-Tolerant Cluster-less Wireless Sensor Networks

Moving Sink (MS) in Wireless Sensor Networks (WSNs) has appeared as a blessing because it collects data directly from the nodes where the concept of relay nodes is becomes obsolete. There are, however, a few challenges to be taken care of, like data delay tolerance and trajectory of MS which is NP-hard. In our proposed scheme, we divide the square field in small squares. Middle point of the partitioned area is the sojourn location of the sink, and nodes around MS are in its transmission range, which send directly the sensed data in a delay-tolerant fashion. Two sinks are moving simultaneously; one inside and having four sojourn locations and other in outer trajectory having twelve sojourn locations. Introduction of the joint mobility enhances network life and ultimately throughput. As the MS comes under the NP-hard problem, we convert it into a geometric problem and define it as, Geometric Sink Movement (GSM). A set of linear programming equations has also been given in support of GSM which prolongs network life time