Cut Detection and Recovery in Wireless Sensor Networks

In WSN(wireless sensor network) will get partition into multiple number connected elements due to the failure of a number of its nodes, that is termed has cut. We tend to contemplate the drop back of detective work cut by the remaining nodes of a wireless sensor network. We tend to propose associate degree algorithmic rule that enables. Each node to notice once the property to a specially selected node has been lost. One or a lot of nodes that are connected to the special node when the cut. The rule of algorithmic is distributed and not synchronized: Each node has to communicate with solely those nodes that are among its communication limit. The algorithmic rule relies on the repetitious computation of a untrue electrical pulse of nodes. The meeting time of the underlying repetitious theme is freelance of the dimensions and structure of the network. We tend to demonstrate the effectiveness of the planned algorithmic rule through simulations and real implementation

Towards Spatial Queries over Phenomena in Sensor Networks

Today, technology developments enable inexpensive production and deployment of tiny sensing and computing nodes. Networked through wireless radio, such senor nodes form a new platform, wireless sensor networks, which provide novel ability to monitor spatiotemporally continuous phenomena. By treating a wireless sensor network as a database system, users can pose SQL-based queries over phenomena without needing to program detailed sensor node operations. DBMS-internally, intelligent and energyefficient data collection and processing algorithms have to be implemented to support spatial query processing over sensor networks. This dissertation proposes spatial query support for two views of continuous phenomena: field-based and object-based. A field-based view of continuous phenomena depicts them as a value distribution over a geographical area. However, due to the discrete and comparatively sparse distribution of sensor nodes, estimation methods are necessary to generate a field-based query result, and it has to be computed collaboratively ‘in-the-network’ due to energy constraints. This dissertation proposes SWOP, an in-network algorithm using Gaussian Kernel estimation. The key contribution is the use of a small number of Hermite coefficients to approximate the Gaussian Kernel function for sub-clustered sensor nodes, and processes the estimation result efficiently. An object-based view of continuous phenomena is interested in aspects such as the boundary of an ‘interesting region’ (e.g. toxic plume). This dissertation presents NED, which provides object boundary detection in sensor networks. NED encodes partial event estimation results based on confidence levels into optimized, variable length messages exchanged locally among neighboring sensor nodes to save communication cost. Therefore, sensor nodes detect objects and boundaries based on moving averages to eliminate noise effects and enhance detection quality. Furthermore, the dissertation proposes the SNAKE-based approach, which uses deformable curves to track the spatiotemporal changes of such objects incrementally in sensor networks. In the proposed algorithm, only neighboring nodes exchange messages to maintain the curve structures. Based on in-network tracking of deformable curves, other types of spatial and spatiotemporal properties of objects, such as area, can be provided by the sensor network. The experimental results proved that our approaches are resource friendly within the constrained sensor networks, while providing high quality query results

Mesh-Mon: a Monitoring and Management System for Wireless Mesh Networks

A mesh network is a network of wireless routers that employ multi-hop routing and can be used to provide network access for mobile clients. Mobile mesh networks can be deployed rapidly to provide an alternate communication infrastructure for emergency response operations in areas with limited or damaged infrastructure. In this dissertation, we present Dart-Mesh: a Linux-based layer-3 dual-radio two-tiered mesh network that provides complete 802.11b coverage in the Sudikoff Lab for Computer Science at Dartmouth College. We faced several challenges in building, testing, monitoring and managing this network. These challenges motivated us to design and implement Mesh-Mon, a network monitoring system to aid system administrators in the management of a mobile mesh network. Mesh-Mon is a scalable, distributed and decentralized management system in which mesh nodes cooperate in a proactive manner to help detect, diagnose and resolve network problems automatically. Mesh-Mon is independent of the routing protocol used by the mesh routing layer and can function even if the routing protocol fails. We demonstrate this feature by running Mesh-Mon on two versions of Dart-Mesh, one running on AODV (a reactive mesh routing protocol) and the second running on OLSR (a proactive mesh routing protocol) in separate experiments. Mobility can cause links to break, leading to disconnected partitions. We identify critical nodes in the network, whose failure may cause a partition. We introduce two new metrics based on social-network analysis: the Localized Bridging Centrality (LBC) metric and the Localized Load-aware Bridging Centrality (LLBC) metric, that can identify critical nodes efficiently and in a fully distributed manner. We run a monitoring component on client nodes, called Mesh-Mon-Ami, which also assists Mesh-Mon nodes in the dissemination of management information between physically disconnected partitions, by acting as carriers for management data. We conclude, from our experimental evaluation on our 16-node Dart-Mesh testbed, that our system solves several management challenges in a scalable manner, and is a useful and effective tool for monitoring and managing real-world mesh networks

Walkabout : an asynchronous messaging architecture for mobile devices

Modern mobile devices are prolific producers and consumers of digital data, and wireless networking capabilities enable them to transfer their data over the Internet while moving. Applications running on these devices may perform transfers to upload data for backup or distribution, or to download new content on demand. Unfortunately, the limited connectivity that mobile devices experience can make these transfers slow and impractical as the amount of data increases. This thesis argues that asynchronous messaging supported by local proxies can improve the transfer capabilities of mobile devices, making it practical for them to participate in large Internet transfers. The design of the Walkabout architecture follows this approach: proxies form store-and-forward overlay networks to deliver messages asynchronously across the Internet on behalf of devices. A mobile device uploads a message to a local proxy at rapid speed, and the overlay delivers it to one or more destination devices, caching the message until each one is able to retrieve it from a local proxy. A device is able to partially upload or download a message whenever it has network connectivity, and can resume this transfer at any proxy if interrupted through disconnection. Simulation results show that Walkabout provides better throughput for mobile devices than is possible under existing methods, for a range of movement patterns. Upload and end-to-end to transfer speeds are always high when the device sending the message is mobile. In the basic Walkabout model, a message sent to a mobile device that is repeatedly moving between a small selection of connection points experiences high download and end-to-end transfer speeds, but these speeds fall as the number of connection points grows. Pre-emptive message delivery extensions improve this situation, making fast end-to-end transfers and device downloads possible under any pattern of movement. This thesis describes the design and evaluation of Walkabout, with both practical implementation and extensive simulation under real-world scenarios

Easing software development for pervasive computing environments

textIn recent years pervasive computing has enjoyed an amazing growth in both research and commercial fields. Not only have the number of available techniques and tools expanded, but the number of actual deployments has been underwhelming. With this growth however, we are also experiencing a divergence of software interfaces, languages, and techniques. This leads to an understandably confusing landscape which needlessly burdens the development of applications. It is our sincere hope that through the use of specialized interfaces, languages, and tools, we can make pervasive computing environments more approachable and efficient to software developers and thereby increase the utility and value of pervasive computing applications. In this dissertation, we present a new method for creating and managing the long-term conversations between peers in pervasive computing environments. The Application Sessions Model formally describes these conversations and specifies techniques for managing them over their lifetimes. In addition to these descriptions, this dissertation presents a prototype implementation of the model and results from its use for realistic scenarios. To address the Application Sessions Model's unique needs for resource discovery in pervasive computing environments, we also present the Evolving Tuples Model. This model is also formally defined in this dissertation and practical examples are used to clarify its features. A prototype for both sensor hardware and software simulation of this model is described along with results characterizing the behavior of the model. The models, prototypes, and evaluations of both models presented here form the basis of a new and interesting line of research into support structures for pervasive computing application development.Electrical and Computer Engineerin

LOCALIZED MOVEMENT CONTROL CONNECTIVITY RESTORATION ALGORITHMS FOR WIRELESS SENSOR AND ACTOR NETWORKS

Wireless Sensor and Actor Networks (WSANs) are gaining an increased interest because of their suitability for mission-critical applications that require autonomous and intelligent interaction with the environment. Hazardous application environments such as forest fire monitoring, disaster management, search and rescue, homeland security, battlefield reconnaissance, etc. make actors susceptible to physical damage. Failure of a critical (i.e. cut-vertex) actor partitions the inter-actor network into disjointed segments while leaving a coverage hole. Maintaining inter-actor connectivity is extremely important in mission-critical applications of WSANs where actors have to quickly plan an optimal coordinated response to detected events. Some proactive approaches pursued in the literature deploy redundant nodes to provide fault tolerance; however, this necessitates a large actor count that leads to higher cost and becomes impractical. On the other hand, the harsh environment strictly prohibits an external intervention to replace a failed node. Meanwhile, reactive approaches might not be suitable for time-sensitive applications. The autonomous and unattended nature of WSANs necessitates a self-healing and agile recovery process that involves existing actors to mend the severed inter-actor connectivity by reconfiguring the topology. Moreover, though the possibility of simultaneous multiple actor failure is rare, it may be precipitated by a hostile environment and disastrous events. With only localized information, recovery from such failures is extremely challenging. Furthermore, some applications may impose application-level constraints while recovering from a node failure. In this dissertation, we address the challenging connectivity restoration problem while maintaining minimal network state information. We have exploited the controlled movement of existing (internal) actors to restore the lost connectivity while minimizing the impact on coverage. We have pursued distributed greedy heuristics. This dissertation presents four novel approaches for recovering from node failure. In the first approach, volunteer actors exploit their partially utilized transmission power and reposition themselves in such a way that the connectivity is restored. The second approach identifies critical actors in advance, designates them preferably as noncritical backup nodes that replace the failed primary if such contingency arises in the future. In the third approach, we design a distributed algorithm that recovers from a special case of multiple simultaneous failures. The fourth approach factors in application-level constraints on the mobility of actors while recovering from node failure and strives to minimize the impact of critical node failure on coverage and connectivity. The performance of proposed approaches is analyzed and validated through extensive simulations. Simulation results confirm the effectiveness of proposed approaches that outperform the best contemporary schemes found in literature