2012 · 346 citations · 37 references
ComputingCloud ComputingComputer ScienceDistributed SystemsMobile ComputingMobile SystemsEnergy-efficient Cloud ComputingEnergy-efficient Mobile ComputingJob SchedulingMobile Cloud ComputingResource ProvisioningResource SchedulingCloud Computing ResourcesEnergy-aware Task SchedulingMobile Cloud ArchitectureProgress MonitoringProgress Monitoring SystemsResource-constrained ComputingService ProviderService Provider Collaboration
Mobile devices are increasingly used for complex processing and encounter many entities that can provide computational resources, moving beyond traditional cloud-based models to mobile‑to‑mobile interactions. This work investigates mobile‑to‑mobile computation, designing Serendipity to let a mobile initiator leverage nearby mobile devices for faster, energy‑efficient processing. Serendipity employs a simple job structure, collaborative task allocation and monitoring, and connectivity‑aware dissemination algorithms to distribute work among mobile peers. Prototype evaluation shows Serendipity improves performance and energy efficiency in intermittent connectivity scenarios.
Mobile devices are increasingly being relied on for services that go beyond simple connectivity and require more complex processing. Fortunately, a mobile device encounters, possibly intermittently, many entities capable of lending it computational resources. At one extreme is the traditional cloud-computing context where a mobile device is connected to remote cloud resources maintained by a service provider with which it has an established relationship. In this paper we consider the other extreme, where a mobile device's contacts are only with other mobile devices, where both the computation initiator and the remote computational resources are mobile, and where intermittent connectivity among these entities is the norm. We present the design and implementation of a system, Serendipity, that enables a mobile computation initiator to use remote computational resources available in other mobile systems in its environment to speedup computing and conserve energy. We propose a simple but powerful job structure that is suitable for such a system. Serendipity relies on the collaboration among mobile devices for task allocation and task progress monitoring functions. We develop algorithms that are designed to disseminate tasks among mobile devices by accounting for the specific properties of the available connectivity. We also undertake an extensive evaluation of our system, including experience with a prototype, that demonstrates Serendipity's performance.
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