DISCO: A Distributed Localization Scheme for Mobile Networks

Localization is one of the key operations in mobile networks. Due to the limitations of GPS, many researchers have devised a variety of different range-free and range-based localization schemes. Range-free schemes utilize the connectivity information to localize mobile nodes. However, the use of the connectivity information allows a high degree of freedom in terms of pinpointing the location of mobile nodes, which leads to low localization precision. Range-based schemes can achieve high localization precision because they require the fine-granularity distance information. Nevertheless, they normally result in high computation complexity and do not work well when part of the distance measurements are missing. In this paper, we propose a distributed range-based localization scheme, DISCO, that uses a series of minimization problems that only involve convex optimization to arrive at high localization precision and low computation complexity. In addition, when some distance measurements are not available, DISCO utilizes the partial distance information to achieve satisfactory localization results. Furthermore, DISCO is a distributed algorithm, which means that it scales well. The performance of DISCO is analyzed through simulation experiments. An in-depth analysis of the time complexity of DISCO is also included in this paper.