An Application of Path Sharing To Routing For Mobile Sinks In Wireless Sensor Networks

Power Conservation is one of the most important challenges in wireless sensor networks. In this paper, we present a minimum-energy routing algorithm. Our main goal is to reduce power consumed and prolong the lifespan of the network. The rotocol, named CODEXT: Coordinationbased Data dissemination for Sensor Networks eXTension, addresses the sensor networks consisting of mobile sinks. CODEXT which is an improvement over CODE protocol Coordination-based Data dissemination for sensor networks considers energy conservation not only in communication but also in idle-to-sleep state. Better informed routing decisions can often be made by sharing information among neighbouring nodes. To this end, we describe the CODEXT protocol, a generic outline for Wireless Sensor Network (WSN) protocols that focuses on locally sharing feedback with little or no overhead. This paper describes one instantiation of it, CODEXT protocol for optimizing routing to multiple sinks through reinforcement learning. Such a routing situation arises in WSNs with multiple, possibly mobile sinks, such as WSNs with actuators deployed in parallel to sensors. This protocol is based on GAF protocol and grid structure to reduce energy consumed. Our simulation results show that CODEXT gain energy efficiency and prolong the network lifetime. Keywords: Source, Sink, Coordination-based Data dissemination protocol, WSN

Improved Bounds on Information Dissemination by Manhattan Random Waypoint Model

With the popularity of portable wireless devices it is important to model and predict how information or contagions spread by natural human mobility -- for understanding the spreading of deadly infectious diseases and for improving delay tolerant communication schemes. Formally, we model this problem by considering $M$ moving agents, where each agent initially carries a \emph{distinct} bit of information. When two agents are at the same location or in close proximity to one another, they share all their information with each other. We would like to know the time it takes until all bits of information reach all agents, called the \textit{flood time}, and how it depends on the way agents move, the size and shape of the network and the number of agents moving in the network. We provide rigorous analysis for the \MRWP model (which takes paths with minimum number of turns), a convenient model used previously to analyze mobile agents, and find that with high probability the flood time is bounded by $O\big(N\log M\lceil(N/M) \log(NM)\rceil\big)$, where $M$ agents move on an $N\times N$ grid. In addition to extensive simulations, we use a data set of taxi trajectories to show that our method can successfully predict flood times in both experimental settings and the real world.Comment: 10 pages, ACM SIGSPATIAL 2018, Seattle, U

A component-based middleware framework for configurable and reconfigurable Grid computing

Significant progress has been made in the design and development of Grid middleware which, in its present form, is founded on Web services technologies. However, we argue that present-day Grid middleware is severely limited in supporting projected next-generation applications which will involve pervasive and heterogeneous networked infrastructures, and advanced services such as collaborative distributed visualization. In this paper we discuss a new Grid middleware framework that features (i) support for advanced network services based on the novel concept of pluggable overlay networks, (ii) an architectural framework for constructing bespoke Grid middleware platforms in terms of 'middleware domains' such as extensible interaction types and resource discovery. We believe that such features will become increasingly essential with the emergence of next-generation e-Science applications. Copyright (c) 2005 John Wiley & Sons, Ltd

Sink-Independent Model in Wireless Sensor Networks

Wireless sensor networks generally support users that send queries and receive data via the sinks. The user and the sinks are mostly connected to each other by infrastructure networks. The users, however, should receive the data from the sinks through multi-hop communications between disseminating sensor nodes if such users move into the sensor networks without infrastructure networks. To support mobile users, previous work has studied various user mobility models. Nevertheless, such approaches are not compatible with the existing routing algorithms, and it is difficult for the mobile users to gather data efficiently due to their mobility. To improve the shortcomings, we propose a view of mobility for wireless sensor networks and propose a model to support a user mobility that is independent of sinks

Geographic Gossip: Efficient Averaging for Sensor Networks

Gossip algorithms for distributed computation are attractive due to their simplicity, distributed nature, and robustness in noisy and uncertain environments. However, using standard gossip algorithms can lead to a significant waste in energy by repeatedly recirculating redundant information. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is related to the slow mixing times of random walks on the communication graph. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing geographic routing combined with a simple resampling method, we demonstrate substantial gains over previously proposed gossip protocols. For regular graphs such as the ring or grid, our algorithm improves standard gossip by factors of $n$ and $\sqrt{n}$ respectively. For the more challenging case of random geometric graphs, our algorithm computes the true average to accuracy $\epsilon$ using $O(\frac{n^{1.5}}{\sqrt{\log n}} \log \epsilon^{-1})$ radio transmissions, which yields a $\sqrt{\frac{n}{\log n}}$ factor improvement over standard gossip algorithms. We illustrate these theoretical results with experimental comparisons between our algorithm and standard methods as applied to various classes of random fields.Comment: To appear, IEEE Transactions on Signal Processin