You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: An Overview of Moving Object Trajectory Compression Algorithms 
Chapter Title:  Priority Queue Based Trajectory Compression. 
1. Abstract of Cited Paper (BIB001):  GPS-equipped mobile devices such as smart phones and in-car navigation units are collecting enormous amounts of spatial and temporal information that traces a moving object's path. The exponential increase in the amount of such trajectory data has caused three major problems. First, transmission of large amounts of data is expensive and time-consuming. Second, queries on large amounts of trajectory data require computationally expensive operations to extract useful patterns and information. Third, GPS trajectories often contain large amounts of redundant data that waste storage and cause increased disk I/O time. These issues can be addressed by algorithms that reduce the size of trajectory data. A key requirement for these algorithms is to minimize the loss of information essential to location-based applications. This paper presents a new compression method called SQUISH-E (Spatial QUalIty Simplification Heuristic - Extended) that provides improved run-time performance and usability. A comprehensive comparison of SQUISH-E with other algorithms is carried out through an empirical study across three types of real-world datasets and a variety of error metrics.

Literature Review:
Priority queue based trajectory compression selects the best subset of trajectory points and permanently removes redundant and inessential trajectory points from original trajectory by utilizing local optimization strategies, until some halting condition is met. The Spatial QUalIty Simplification Heuristic (SQUISH) method based on the priority queue data structure proposed by Muckell et al. BIB001 prioritizes the most important points in a trajectory stream. It uses local optimization to select the best subset of points and permanently removes redundant or insignificant points from the original GPS trajectory. Three years later, Muckell et al. BIB002 presented a new version of SQUISH, called SQUISH-E (Spatial QUalIty Simplification Heuristic-Extended) which has the flexibility of tuning compression with respect to compression ratio and error. Priority queue based trajectory compression is not only an online trajectory compression algorithm but also a trajectory compression algorithm that requires presetting the memory buffer. Hence, it can be well applied to real-time applications and small memory devices. It is suitable for all kinds of trajectories, but the compression effect and matching effect may be a little worse than the other compression methods.