Energy-efficient job stealing for CPU-intensive processing in mobile devices

Rodríguez, Juan Manuel; Mateos, Cristian; Zunino, Alejandro

doi:10.1007/s00607-012-0245-5

Cited by 26 publications

(22 citation statements)

References 53 publications

(156 reference statements)

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“…In literature, several resource allocation schemes has been developed for allocation of tasks to mobile ad hoc systems. Authors in (Rodriguez et al, 2012) have proposed several job stealing techniques to reduce the processing energy consumption. Authors in (Hariharasudhan et al, 2015) have proposed a scheme that addresses network connectivity, node mobility and energy consumption problems.…”

Section: Related Workmentioning

confidence: 99%

“…The first phase exploits the history of user mobility patterns to select nodes that will remain connected for long time and the second phase considers application tasks and distance between nodes to reduce communication cost. An efficient and robust resource allocation scheme to address node mobility and energy consumption problems has been developed in Rodriguez et al (1999). Compared to existing schemes, our proposed scheme focuses on allocation of real-time tasks and aims to reduce energy consumption.…”

Section: Related Workmentioning

confidence: 99%

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A Mobile Ad hoc Cloud Computing and Networking Infrastructure for Automated Video Surveillance System

Shah¹

2017

Journal of Computer Science

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Mobile automated video surveillance system involves application of real-time image and video processing algorithms which require a vast quantity of computing and storage resources. To support the execution of mobile automated video surveillance system, a mobile ad hoc cloud computing and networking infrastructure is proposed in which multiple mobile devices interconnected through a mobile ad hoc network are combined to create a virtual supercomputing node. An energy efficient resource allocation scheme has also been proposed for allocation of realtime automated video surveillance tasks. To enable communication between mobile devices, a Wi-Fi Direct based mobile ad hoc cloud networking infrastructure has been developed. More specifically, a routing layer has been developed to support communication between Wi-Fi Direct devices in a group and multi-hop communication between devices across the group. The proposed system has been implemented on a group of Wi-Fi Direct enabled Samsung mobile devices.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A Mobile Ad hoc Cloud Computing and Networking Infrastructure for Automated Video Surveillance System

Shah¹

2017

Journal of Computer Science

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“…Third, the battery technologies and energy management algorithms have been significantly improved during the recently years (e.g., [13], [14]). Finally, today's data storage technologies make it possible to store tens of gigabytes of data in a small memory card, which means that some of today's smartphones are almost as capable as desktop computers from several years back [35].…”

Section: System Model On Distributed Computationmentioning

confidence: 99%

Motivating Smartphone Collaboration in Data Acquisition and Distributed Computing

Duan

Kubo

Sugiyama

et al. 2014

IEEE Trans. on Mobile Comput.

110

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This paper analyzes and compares different incentive mechanisms for a master to motivate the collaboration of smartphone users on both data acquisition and distributed computing applications. To collect massive sensitive data from users, we propose a reward-based collaboration mechanism, where the master announces a total reward to be shared among collaborators, and the collaboration is successful if there are enough users wanting to collaborate. We show that if the master knows the users' collaboration costs, then he can choose to involve only users with the lowest costs. However, without knowing users' private information, then he needs to offer a larger total reward to attract enough collaborators. Users will benefit from knowing their costs before the data acquisition. Perhaps surprisingly, the master may benefit as the variance of users' cost distribution increases.To utilize smartphones' computation resources to solve complex computing problems, we study how the master can design an optimal contract by specifying different task-reward combinations for different user types. Under complete information, we show that the master involves a user type as long as the master's preference characteristic outweighs that type's unit cost. All collaborators achieve a zero payoff in this case. If the master does not know users' private cost information, however, he will conservatively target at a smaller group of users with small costs, and has to give most benefits to the collaborators.If V < n 0 C 0 , then the master's announced total reward R is also smaller than n 0 C 0 to make a profit. This reward is not enough to compensate even n 0 users with smallest costs, thus no users will join. Regarding this, the master will not seek users' collaboration in Stage I

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“…The scheme is based on a decentralized architecture and also does not provide any mechanism to address node mobility. In , various job stealing techniques such as random stealing, best rank aware stealing, and worst rank aware stealing based on a centralized architecture were developed to reduce the processing energy consumption. The rank is calculated based on a benchmark factor for each device, the estimated uptime of a device, and the number of jobs assigned to that device.…”

Section: Related Workmentioning

confidence: 99%

Energy efficient and robust allocation of interdependent tasks on mobile ad hoc computational grid

Shah

2014

Concurrency and Computation

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Summary A mobile ad hoc computational grid is a distributed computing infrastructure that allows mobile nodes to share computing resources in a mobile ad hoc environment. Compared to traditional distributed systems such as grids and clouds, resource allocation in mobile ad hoc computational grids is not straightforward because of node mobility, limited battery power and an infrastructure‐less network environment. The existing schemes are either based on a decentralized architecture that results in poor allocation decisions or assume independent tasks. This paper presents a scheme that allocates interdependent tasks and aims to reduce task completion time and the amount of energy consumed in transmission of data. This scheme comprises two key algorithms: resource selection and resource allocation. The resource selection algorithm is designed to select nodes that remain connected for a longer period, whereas the resource assignment or allocation algorithm is developed to allocate interdependent tasks to the nodes that are accessible at the minimum transmission power. The scheme is based on a hybrid architecture that results in effective allocation decisions, reduces the communication cost associated with the exchange of control information, and distributes the processing burden among the nodes. The paper also investigates the relationship between the data transfer time and transmission energy consumption and presents a power‐based routing protocol to reduce data transfer costs and transmission energy consumption. Copyright © 2014 John Wiley & Sons, Ltd.

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Energy-efficient job stealing for CPU-intensive processing in mobile devices

Cited by 26 publications

References 53 publications

A Mobile Ad hoc Cloud Computing and Networking Infrastructure for Automated Video Surveillance System

A Mobile Ad hoc Cloud Computing and Networking Infrastructure for Automated Video Surveillance System

Motivating Smartphone Collaboration in Data Acquisition and Distributed Computing

Energy efficient and robust allocation of interdependent tasks on mobile ad hoc computational grid

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