Abstract
Although the existing time synchronization protocols in wireless sensor networks (WSNs) are efficient for short periods, many applications require long-term synchronization among the nodes, for example, coordinated sleep and wakeup modes, and synchronized sampling. In such applications, experiments have shown that even clock skew correction cannot maintain long-term clock synchronization and a quadratic model of clock variations can better capture the dynamics of the actual clock model involved, hence increasing the resynchronization period and conserving significant energy. This paper derives the maximum likelihood (ML) estimator for all the clock parameters in a two-way timing exchange model with exponential delays. The same estimation procedure can be applied to one-way timing exchange models with little modification.
Highlights
AND RELATED WORKA wireless sensor network (WSN) consists of several small scale miniature devices capable of onboard sensing, computing, and communications
Time synchronization among the nodes in a WSN is important for various applications such as coordinated sleep and wakeup modes, object tracking, data fusion, security, and MAC protocols
Since energy is the scarcest resource in WSNs, a smart technique to conserve energy is to deploy coordinated turning on and off of radios in sensor nodes
Summary
A wireless sensor network (WSN) consists of several small scale miniature devices capable of onboard sensing, computing, and communications. TPSN [2] adjusts the clock offset between the two nodes only, while RBS [3] and FTSP [4] estimate both the clock offset and skew through linear regression These schemes are only useful for short-term applications such as surveillance and object tracking and are unsuitable for efficient duty cycling. EURASIP Journal on Advances in Signal Processing and other applications that require continuous time synchronization such as synchronized sampling because they spend a lot of energy for resynchronization during a long time interval To emphasize this fact, note that the most efficient time synchronization protocol reported far and implemented on real testbed, FTSP, has to resynchronize the nodes in the network every minute to achieve 90 microseconds synchronization error [4]. Since it has been reported in [15] that the energy required to transmit 1 bit over 100 meters (3 Joules) is equivalent to the energy required to execute 3 millions of instructions, a tradeoff between spending reduced communication energy on the cost of more computational energy through estimating the long-term drift as well as the offset and the skew between clocks of two nodes is highly desirable
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