27-12-2011, 09:07 PM
Check out the attachment
05-09-2012, 04:53 PM
Adaptive Fault-Tolerant QoS Control Algorithms for Maximizing System Lifetime of Query-Based Wireless Sensor Networks
Adaptive Fault.pdf (Size: 1.57 MB / Downloads: 54) Abstract Data sensing and retrieval in wireless sensor systems have a widespread application in areas such as security and surveillance monitoring, and command and control in battlefields. In query-based wireless sensor systems, a user would issue a query and expect a response to be returned within the deadline. While the use of fault tolerance mechanisms through redundancy improves query reliability in the presence of unreliable wireless communication and sensor faults, it could cause the energy of the system to be quickly depleted. Therefore, there is an inherent trade-off between query reliability versus energy consumption in query-based wireless sensor systems. In this paper, we develop adaptive fault-tolerant quality of service (QoS) control algorithms based on hop-by-hop data delivery utilizing “source” and “path” redundancy, with the goal to satisfy application QoS requirements while prolonging the lifetime of the sensor system. We develop a mathematical model for the lifetime of the sensor system as a function of system parameters including the “source” and “path” redundancy levels utilized. We discover that there exists optimal “source” and “path” redundancy under which the lifetime of the system is maximized while satisfying application QoS requirements. Numerical data are presented and validated through extensive simulation, with physical interpretations given, to demonstrate the feasibility of our algorithm design. INTRODUCTION OVER the last few years, we have seen a rapid increase in the number of applications for wireless sensor networks (WSNs). WSNs can be deployed in battlefield applications, and a variety of vehicle health management and condition-based maintenance applications on industrial, military, and space platforms. For military users, a primary focus has been area monitoring for security and surveillance applications. A WSN can be either source-driven or query-based depending on the data flow. In source-driven WSNs, sensors initiate data transmission for observed events to interested users, including possibly reporting sensor readings periodically. An important research issue in sourcedriven WSNs is to satisfy QoS requirements of event-to-sink data transport while conserving energy of WSNs. In querybased WSNs, queries and data are forwarded to interested entities only. In query-based WSNs, a user would issue a query with QoS requirements in terms of reliability and timeliness. RELATED WORK Existing research efforts related to applying redundancy to satisfy QoS requirements in query-based WSNsfall into three categories: traditional end-to-end QoS, reliability assurance, and application-specific QoS [4]. Traditional end-to-end QoS solutions are based on the concept of end-to-end QoS requirements. The problem is that it may not be feasible to implement end-to-end QoS in WSNs due to the complexity and high cost of the protocols for resource-constrained sensors. An example is Sequential Assignment Routing (SAR) [5] that utilizes path redundancy from a source node to the sink node. Each sensor uses a SAR algorithm for path selection. It takes into account the energy and QoS factors on each path, and the priority level of a packet. For each packet routed through the network, a weighted QoS metric is computed as the product of the additive QoS metric and a weight coefficient associated with the priority level of that packet. The objective of the SAR algorithm is to minimize the average weighted QoS metric throughout the lifetime of the network. The algorithm does not consider the reliability issue. Energy Consumption Due to Clustering For clustering, the system would consume energy for broadcasting the announcement message and for the cluster-join process. Since p is the probability of becoming a CH, there will be pn SNs that would be broadcasting the announcement message. This announcement message will be received and retransmitted by each SN to the next hop until the TTL of the message reaches the value 0, i.e., the number of hops equals Nh intra. Thus, the energy required for broadcasting is pn½Nh intraðr2ÞðET þ ERÞ. The cluster-join process will require an SN to send a message to the CH informing that it will join the cluster and the CH to send an acknowledgement to the SN. Since there are pn CHs and ðn pnÞ SNs in the system, the energy for this is nðET þ ER). Let the size of the message exchange be nl. ER and ET will be calculated from (1) and (2) with nl in place of nb. Let Niteration be the number of iterations required to execute the clustering algorithm. EVALUATION In this section, we present numeric data to demonstrate the tradeoff between Rq and Eq and that there exists an optimal (mp, ms) set that would maximize the MTTF of the sensor system while satisfying (24). Table 1 lists the parameters used along with their default parameters. Our WSN consists of 1,000 sensor nodes distributed according to a Poisson process with density in a square area of 400 m by 400 m. Each SN has a transmission radio range of 40 m. The initial bandwidth of the wireless channel is 200 Kb/s. Each SN has an initial energy of 10 J. The energy parameters used by the radio module are adopted from [1], [2]. The energy cost to run the transmitter/receiver radio circuitry per bit processed (Eelec) is chosen to be 50 nJ/bit. The energy used by the transmit amplifier to achieve an acceptable signal to noise ratio ("amp) is chosen to be 10 pJ=bit=m2.
25-09-2012, 12:04 PM
which type sensor is used for this project but how to start the project with c# codings please tell me about this
|
|