Signal processing techniques for synchronization of wireless sensor networks

Plenary PaperClock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated. © 2010 SPIE.published_or_final_versio

Secure Routing in Wireless Mesh Networks

Wireless mesh networks (WMNs) have emerged as a promising concept to meet the challenges in next-generation networks such as providing flexible, adaptive, and reconfigurable architecture while offering cost-effective solutions to the service providers. Unlike traditional Wi-Fi networks, with each access point (AP) connected to the wired network, in WMNs only a subset of the APs are required to be connected to the wired network. The APs that are connected to the wired network are called the Internet gateways (IGWs), while the APs that do not have wired connections are called the mesh routers (MRs). The MRs are connected to the IGWs using multi-hop communication. The IGWs provide access to conventional clients and interconnect ad hoc, sensor, cellular, and other networks to the Internet. However, most of the existing routing protocols for WMNs are extensions of protocols originally designed for mobile ad hoc networks (MANETs) and thus they perform sub-optimally. Moreover, most routing protocols for WMNs are designed without security issues in mind, where the nodes are all assumed to be honest. In practical deployment scenarios, this assumption does not hold. This chapter provides a comprehensive overview of security issues in WMNs and then particularly focuses on secure routing in these networks. First, it identifies security vulnerabilities in the medium access control (MAC) and the network layers. Various possibilities of compromising data confidentiality, data integrity, replay attacks and offline cryptanalysis are also discussed. Then various types of attacks in the MAC and the network layers are discussed. After enumerating the various types of attacks on the MAC and the network layer, the chapter briefly discusses on some of the preventive mechanisms for these attacks.Comment: 44 pages, 17 figures, 5 table

Energy and Link Quality Based Routing for Data Gathering Tree in Wireless Sensor Networks Under TINYOS - 2.X

Energy is one of the most important and scarce resources in Wireless Sensor Networks (WSN). WSN nodes work with the embedded operating system called TinyOS, which addresses the constrains of the WSN nodes such as limited processing power, memory, energy, etc and it uses the collection Tree Protocol (CTP) to collect the data from the sensor nodes. It uses either the four-bit link estimation or Link Estimation Exchange Protocol (LEEP) to predict the bi directional quality of the wireless link between the nodes and the next hop candidate is based on the estimated link quality. The residual energy of the node is an important key factor, which plays a vital role in the lifetime of the network and hence this has to taken as one of the metric in the parent selection. In this work, we consider the remaining energy of the node as one of the metric to decide the parent in addition to the link quality metrics. The proposed protocol was compared with CTP protocol in terms of number of packets forwarded by each node and packet reception ratio (PRR) of the network. This work was simulated in TOSSIM simulator and the same was tested in Crossbow IRIS radio test bed. The results show that our algorithm performs better than CTP in terms of load distribution and hence the increased lifetimeComment: 14 Pages, IJWM