Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation

Sensor networks potentially feature large numbers of nodes that can sense their environment over time, communicate with each other over a wireless network, and process information. They differ from data networks in that the network as a whole may be designed for a specific application. We study the theoretical foundations of such large scale sensor networks, addressing four fundamental issues- connectivity, capacity, clocks and function computation. To begin with, a sensor network must be connected so that information can indeed be exchanged between nodes. The connectivity graph of an ad-hoc network is modeled as a random graph and the critical range for asymptotic connectivity is determined, as well as the critical number of neighbors that a node needs to connect to. Next, given connectivity, we address the issue of how much data can be transported over the sensor network. We present fundamental bounds on capacity under several models, as well as architectural implications for how wireless communication should be organized. Temporal information is important both for the applications of sensor networks as well as their operation.We present fundamental bounds on the synchronizability of clocks in networks, and also present and analyze algorithms for clock synchronization. Finally we turn to the issue of gathering relevant information, that sensor networks are designed to do. One needs to study optimal strategies for in-network aggregation of data, in order to reliably compute a composite function of sensor measurements, as well as the complexity of doing so. We address the issue of how such computation can be performed efficiently in a sensor network and the algorithms for doing so, for some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE

Kriptografi Dan Skema Keamanan Untuk Jaringan Sensor Nirkawat

This paper attempts to explore the security issues in sensor network that include constraints in sensor networks security, the requirements of secure sensor networks, attack classification and its counter measures and security mechanisms at wirelesssensor network (WSN) such as cryptography and key management. Popularity of wireless sensor network is increasing because of its potential to provide low-cost solution for a variety of real-world problem. As a special form of ad-hoc networks, sensor networks has many limitations that lead to vulnerabilities in security issues. Currently, there are many researches in the field of sensor network security. Our analysis shows that symmetric key cryptography systems are more favorable to provide WSN security services because of its computation and energy cost. Moreover, distributed combine with pre-distributed key management is important to overcome security threats and centralize threats detection is more favorable to reduce energy and computation cost of sensor nodes

Towards a Queueing-Based Framework for In-Network Function Computation

We seek to develop network algorithms for function computation in sensor networks. Specifically, we want dynamic joint aggregation, routing, and scheduling algorithms that have analytically provable performance benefits due to in-network computation as compared to simple data forwarding. To this end, we define a class of functions, the Fully-Multiplexible functions, which includes several functions such as parity, MAX, and k th -order statistics. For such functions we exactly characterize the maximum achievable refresh rate of the network in terms of an underlying graph primitive, the min-mincut. In acyclic wireline networks, we show that the maximum refresh rate is achievable by a simple algorithm that is dynamic, distributed, and only dependent on local information. In the case of wireless networks, we provide a MaxWeight-like algorithm with dynamic flow splitting, which is shown to be throughput-optimal

Decentralized event-triggered control over wireless sensor/actuator networks

In recent years we have witnessed a move of the major industrial automation providers into the wireless domain. While most of these companies already offer wireless products for measurement and monitoring purposes, the ultimate goal is to be able to close feedback loops over wireless networks interconnecting sensors, computation devices, and actuators. In this paper we present a decentralized event-triggered implementation, over sensor/actuator networks, of centralized nonlinear controllers. Event-triggered control has been recently proposed as an alternative to the more traditional periodic execution of control tasks. In a typical event-triggered implementation, the control signals are kept constant until the violation of a condition on the state of the plant triggers the re-computation of the control signals. The possibility of reducing the number of re-computations, and thus of transmissions, while guaranteeing desired levels of performance makes event-triggered control very appealing in the context of sensor/actuator networks. In these systems the communication network is a shared resource and event-triggered implementations of control laws offer a flexible way to reduce network utilization. Moreover reducing the number of times that a feedback control law is executed implies a reduction in transmissions and thus a reduction in energy expenditures of battery powered wireless sensor nodes.Comment: 13 pages, 3 figures, journal submissio

Dataflow-Oriented Provenance System for Multifusion Wireless Sensor Networks

We present a dataflow-oriented provenance system for data fusion sensor networks. This model works best with net- works sensing dynamic objects and although our system is generic, we model it on a proximity binary sensor network. We introduce a network-level fault-tolerance mechanism by using the cognitive strength of provenance models. Our provenance model reduce the limitations of a sensor’s capability and decrease the error-prone nature of wireless sen- sor networks. In addition provenance data is used in order to efficiently build the dynamic data fusion scenario and to adjust the network such as turning of some sensors. In a fault-tolerant, self-adjusting sensor network, sensor data produce more accurate results and with the improvements, tasks such as target localization is more precisely done. One other aspect of our network is that by having computation nodes spread to the network, the computation is done in a distributed manner and as nodes make decisions based on the provenance and fusion data available, the network has a distributed intelligence. Keywords: Multifusion, Wireless Sensor Networks, Open Provenance Mode

Performance Evaluation of Mannasim Framework for Wireless Sensor Network in Network Simulator 2

Optimizing sensor networks involves addressing a wide range of issues steaming from limited energy reserves, computation power, communication capabilities, and self-managing sensor nodes. The high cost and difficulties in deploying wireless sensor networks are the main challenges that motivate investigating the performance of a sensor network in a simulated environment. The Network Simulator 2 (ns-2) is one of the flexible tools available for network engineers to study how various protocols perform under different configurations and topologies. ns-2 lacks of modules for studying the sensor networks. However, many researchers have developed several modules for ns-2, which help exploring wireless sensor network before real deployment. This project concerns the reliability of Mannasim module for studying the performance of wireless sensor networks in ns-2. This project supports the analysis of different sensor network configurations under the demands of specific sensor applications. The project showed that Mannasim module reliable and it is able to meet the requirements of different layers that are involved in sensor networks