Maintaining Quality of Service for Adaptive Mobile Map Clients

Abstract

Mobile devices must deal with limited and dynamically varying resources, in particular, the network quality of service (QoS). In addition, wireless devices have other constraints such as limited memory, battery power, and physical dimensions. Applications that execute in such environments need to adapt to the dynamic operating conditions in order to preserve an acceptable level of service as close to 100% of the time as possible. Viewing and downloading digital spatial data on mobile devices has become more popular, especially with the availability of <i>location-aware</i> applications that exploit GPS (Global Positioning System) receivers integrated in many of today's mobile devices. Map client applications face many challenges in accessing data across a wireless network. Vector spatial data files tend to be large, and file sizes tend to increase unpredictably depending on the complexity of feature geometry. Due to the limited size of the mobile device display, viewing all the details of the map could cause unreasonable clutter and render the map useless. Even if it is feasible to transmit all the details from a QoS standpoint, this could pose a problem from a usability standpoint. This research effort aims to tackle the issues of QoS and usability on mobile devices through a client-proxy-server model where clients are on mobile devices. The proxy performs two functions. First, it supplies the client with vital data about the status of the system that allows the client to take adaptive decisions aimed at maintaining the QoS. Second, it performs the adaptive actions requested by the client. There are two types of adaptive actions performed by the proxy, activating and deactivating filters. When filters are activated, the amount of data transmitted from the server to the client is reduced. The client may decide to activate one or more filters either to maintain QoS or to limit clutter on the screen and enhance usability. The map client-server application and the proxy were developed in Java (tm), and a number of experiments and real-life scenarios were designed to determine the effectiveness and feasibility of the proposed adaptation model and to evaluate the performance of the proxy.