0000000001238307

AUTHOR

Liqing Liu

showing 5 related works from this author

Multi-objective optimization for computation offloading in mobile-edge computing

2017

Mobile-edge cloud computing is a new cloud platform to provide pervasive and agile computation augmenting services for mobile devices (MDs) at anytime and anywhere by endowing ubiquitous radio access networks with computing capabilities. Although offloading computations to the cloud can reduce energy consumption at the MDs, it may also incur a larger execution delay. Usually the MDs have to pay cloud resource they used. In this paper, we utilize queuing theory to bring a thorough study on the energy consumption, execution delay and price cost of offloading process in a mobile-edge cloud system. Specifically, both wireless transmission and computing capabilities are explicitly and jointly co…

computational modeling020203 distributed computingMobile edge computingOptimization problemta213delaysbusiness.industryComputer scienceDistributed computingcloud computing020206 networking & telecommunicationsCloud computing02 engineering and technologyEnergy consumptionbase stationsMulti-objective optimizationBase stationenergy consumptioncomputers0202 electrical engineering electronic engineering information engineeringComputation offloadingbusinessoptimizationMobile deviceComputer network2017 IEEE Symposium on Computers and Communications (ISCC)
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Dynamic Resource Allocation and Computation Offloading for Edge Computing System

2020

In this work, we propose a dynamic optimization scheme for an edge computing system with multiple users, where the radio and computational resources, and offloading decisions, can be dynamically allocated with the variation of computation demands, radio channels and the computation resources. Specifically, with the objective to minimize the energy consumption of the considered system, we propose a joint computation offloading, radio and computational resource allocation algorithm based on Lyapunov optimization. Through minimizing the derived upper bound of the Lyapunov drift-plus-penalty function, the main problem is divided into several sub-problems at each time slot and are addressed sepa…

Lyapunov functionMathematical optimizationComputer scienceComputation020206 networking & telecommunicationsLyapunov optimizationEdge computing02 engineering and technologyEnergy consumptionDynamic computation offloadingComputational resourcesymbols.namesake0202 electrical engineering electronic engineering information engineeringsymbolsResource allocationComputation offloadingSDG 7 - Affordable and Clean EnergyResource allocationLyapunov optimizationEdge computing
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Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds

2016

Nowadays, although the data processing capabilities of the modern mobile devices are developed in a fast speed, the resources are still limited in terms of processing capacity and battery lifetime. Some applications, in particular the computationally intensive ones, such as multimedia and gaming, often require more computational resources than a mobile device can afford. One way to address such a problem is that the mobile device can offload those tasks to the centralized cloud with data centers, the nearby cloudlet or ad hoc mobile cloud. In this paper, we propose a data offloading and task allocation scheme for a cloudlet-assisted ad hoc mobile cloud in which the master device (MD) who ha…

Computer Networks and CommunicationsComputer sciencemobile cloud computingDistributed computingMobile computingCloud computing02 engineering and technologyad hoc mobile cloudoffloading0202 electrical engineering electronic engineering information engineeringStackelberg competitionCloudletElectrical and Electronic Engineering020203 distributed computingbusiness.industrycloud computing020206 networking & telecommunicationsEnergy consumptionMobile ad hoc networkstackelberg gameMobile cloud computingTask (computing)businessMobile deviceInformation SystemsComputer networkcloudlet
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Socially-aware Dynamic Computation Offloading Scheme for Fog Computing System with Energy Harvesting Devices

2018

Fog computing is considered as a promising technology to meet the ever-increasing computation requests from a wide variety of mobile applications. By offloading the computation-intensive requests to the fog node or the central cloud, the performance of the applications, such as energy consumption and delay, are able to be significantly enhanced. Meanwhile, utilizing the recent advances of social network and energy harvesting (EH) techniques, the system performance could be further improved. In this paper, we take the social relationships of the EH mobile devices (MDs) into the design of computational offloading scheme in fog computing. With the objective to minimize the social group executi…

pilvipalvelutsocial-aware mobile networkexecution costmobiililaitteetenergy consumptionGeneralized Nash Equilibrium Problemenergiankulutusfog computingenergian kerääminencomputation offloading
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Multi-objective Optimization for Computation Offloading in Fog Computing

2018

Fog computing system is an emergent architecture for providing computing, storage, control, and networking capabilities for realizing Internet of Things. In the fog computing system, the mobile devices (MDs) can offload its data or computational expensive tasks to the fog node within its proximity, instead of distant cloud. Although offloading can reduce energy consumption at the MDs, it may also incur a larger execution delay including transmission time between the MDs and the fog/cloud servers, and waiting and execution time at the servers. Therefore, how to balance the energy consumption and delay performance is of research importance. Moreover, based on the energy consumption and delay,…

pilvipalvelutexecution delayenergy consumptioncloud computingcostenergiankulutusfog computingpower allocationmonitavoiteoptimointioffloading probability
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