Nigel Davies
Adrian Friday
Stephen P. Wade
Abstract
Mobile computing environments increasingly consist of a range of supporting technologies offering a diverse set of capabilities to applications and end-systems. Such environments are characterised by sudden and dramatic changes in the quality-of-service (QoS) available to applications and users. Recent work has shown that distributed systems platforms can assist applications to take advantage of these changes in QoS and, more specifically, facilitate applications to adapt to their environment. However, the current state-of-the-art in these platforms reflects their fixed network origins through their choice of synchronous connection-oriented communications paradigms. In this paper we argue that these paradigms are not well suited to operation in the emerging mobile environments. Furthermore, we offer an alternative programming paradigm based on tuple spaces which, we believe, offers a number of benefits within a mobile context. The paper presents the design, implementation and evaluation of a new platform based on this paradigm.
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Index Terms
- L2imbo: a distributed systems platform for mobile computing
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Reviews
Violet R. Syrotiuk
L 2 imbo is a new platform for support of heterogeneous mobile computing environments that must be able to dynamically adapt to changing quality of service (QoS). This research paper begins by reviewing some existing mobile distributed systems platforms, such as Mobile DCE, MOST, and Rover. All of these platforms provide connection-oriented communication that is based on remote procedure call (RPC), with no general mechanisms for informing applications about changes in QoS or about associated adaptation to the changes. L 2 imbo is instead based on tuple spaces, an asynchronous programming model. L 2 imbo extends the Linda coordination language in four ways. First, multiple tuple spaces are provided. Second, a tuple type hierarchy is introduced. Third, associating deadlines with tuples allows tuples to be ordered, providing a means to associate QoS attributes with tuples. Fourth, agents that implement system and application functions are introduced. Such agents provide services for QoS monitoring, the creation of tuple spaces, the propagation of tuples between spaces, and management of inter-tuple type relationships. Adaptation to a change in the QoS is achieved simply, through a filtering agent that maps tuples according to the QoS level. The performance of a prototype L 2 imbo system compares favorably to various forms of RPC interactions, even in traditional worst-case scenarios for tuple space platforms. While the tuple space platform is interesting, there seem to be several “centralized” protocols that run on hosts (such as the distributed tuple space protocol), which may limit the performance and scalability of the technique.
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