The progress of mobile device technology unfolds a new spectrum of applications that challenges conventional infrastructure models. Most of these devices are perceived by their users as "appliances" rather than computers and accordingly the application management should be done transparently by the underlying system unlike classic applications managed explicitly by the user. Memory management on such devices should consider new types of mobile applications involving code mobility such as mobile agents, active networks and context aware applications. This paper describes a new code management technique, called "code collection " and proposes a specific code collection algorithm, the Adaptive Code Collection Algorithm (ACCAL). Code collection is a mechanism for transparently loading and discarding application components on mobile devices at runtime that is designed to permit very low memory usage and at the same time good performance by focusing memory usage on the hotspots of the application. To achieve these goals, ACCAL uses properties specific to executable code and enhances conventional data management methods such as garbage collection and caching. The results show that fine-grained code collection allows large applications to execute by using significantly less memory while inducing small execution time overhead.

Many parallel and distributed programming models are based on some form of shared objects, which may be represented in various ways (e.g., single-copy, replicated, and partitioned objects). Also, many different operation execution strategies have been designed for each representation. In programming systems that use multiple representations integrated in a single object model, one way to provide multiple execution strategies is to implement each strategy independently from the others. However, this leads to rigid systems and provides little opportunity for code reuse. Instead, we propose a flexible operation execution model that allows the implementation of many different strategies, which can even be changed at runtime. We present the model and a distributed implementation of it. Also, we describe how various execution strategies can be expressed using the model, and we look at applications that benefit from its flexibility. 1 Introduction Shared objects have become a popular model...