A network-aware framework for energy-efficient data acquisition in wireless sensor networks

Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN

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

A Logically Centralized Approach for Control and Management of Large Computer Networks

Management of large enterprise and Internet Service Provider networks is a complex, error-prone, and costly challenge. It is widely accepted that the key contributors to this complexity are the bundling of control and data forwarding in traditional routers and the use of fully distributed protocols for network control. To address these limitations, the networking research community has been pursuing the vision of simplifying the functional role of a router to its primary task of packet forwarding. This enables centralizing network control at a decision plane where network-wide state can be maintained, and network control can be centrally and consistently enforced. However, scalability and fault-tolerance concerns with physical centralization motivate the need for a more flexible and customizable approach. This dissertation is an attempt at bridging the gap between the extremes of distribution and centralization of network control. We present a logically centralized approach for the design of network decision plane that can be realized by using a set of physically distributed controllers in a network. This approach is aimed at giving network designers the ability to customize the level of control and management centralization according to the scalability, fault-tolerance, and responsiveness requirements of their networks. Our thesis is that logical centralization provides a robust, reliable, and efficient paradigm for management of large networks and we present several contributions to prove this thesis. For network planning, we describe techniques for optimizing the placement of network controllers and provide guidance on the physical design of logically centralized networks. For network operation, algorithms for maintaining dynamic associations between the decision plane and network devices are presented, along with a protocol that allows a set of network controllers to coordinate their decisions, and present a unified interface to the managed network devices. Furthermore, we study the trade-offs in decision plane application design and provide guidance on application state and logic distribution. Finally, we present results of extensive numerical and simulative analysis of the feasibility and performance of our approach. The results show that logical centralization can provide better scalability and fault-tolerance while maintaining performance similarity with traditional distributed approach

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