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Optimizing Applications for Mobile Cloud Computing Through MOCCAA
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PRE
AI
DOI：10.1007/s10723-019-09492-0.png)
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Abstract
En 中文
Mobile Cloud Computing (MCC) aims at leveraging remote resources to boost application performance on mobile devices while conserving resources such as battery, memory, and storage. Offloading computations and outsourcing tasks are, however, associated with numerous challenges known from distributed systems. Typical mobile applications have a monolithic design and are not laid out for a distributed deployment and execution. In this work, we present how to design and partition such applications and how these partitions stay synchronized in a cost-efficient manner at runtime. We introduce our comprehensive and extendable framework MOCCAA (MObile Cloud Computing AdaptAble) that supports developers along this path. Its performance gain is mainly achieved through a new graph partitioning heuristic that is searching for the maximally beneficial cut, through minimized monitoring efforts for resource consumption prediction, through scalable and location-aware resource discovery and management, and through our graph-based delta synchronization of local and remote object states. In particular, the graph partitioning heuristic and the delta synchronization allow us to reduce synchronization costs and improve quality dimensions such as latency and bandwidth consumption.
Keywords:
Mobile Cloud Computing
Delta synchronization
Graph partitioning
Maximum Cut
Resource prediction
Resource management
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2.9
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764
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1.3K
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