• Corpus ID: 14286131

Joint Optimization of Radio Resources and Code Partitioning in Mobile Cloud Computing

@article{Lorenzo2013JointOO,
  title={Joint Optimization of Radio Resources and Code Partitioning in Mobile Cloud Computing},
  author={Paolo Di Lorenzo and Sergio Barbarossa and Stefania Sardellitti},
  journal={ArXiv},
  year={2013},
  volume={abs/1307.3835}
}
The aim of this paper is to propose a computation offloading st rategy, to be used in mobile cloud computing, in order to minimize the energy expenditure at the mobile handset necessary to run an application under a latency constraint. We exploit the concept of call graph, which models a generic computer program as a set of procedures related to each other through a weighted directed graph. Our goal is to derive the partition of the call graph establishin g which procedures are to be executed… 

Figures and Tables from this paper

Joint Optimization of Offloading and Resource Allocation Scheme for Mobile Edge Computing

A new strategy named Joint Offloading and Resource allocation in WiFi-based MEC architecture (JOR-MEC) is proposed, which outperforms the related prominent baseline strategies in terms of energy consumption and completion delay.

A Code-Oriented Partitioning Computation Offloading Strategy for Multiple Users and Multiple Mobile Edge Computing Servers

An offloading strategy to decide the execution location, CPU frequency, and transmission power for UE while minimizing the execution overhead (i.e., a weighted sum of energy consumption and computational time) of UE's applications, which is an NP-hard problem.

Q-Learning Algorithm for Joint Computation Offloading and Resource Allocation in Edge Cloud

A new joint task assignment and resource allocation approach in a multi-user WiFi-based MEC architecture, named QL-Joint Task Assignment and Resource Allocation (QL-JTAR), based on a Q-Learning algorithm, which outperforms the related prominent strategies in terms of energy consumption and delay, while ensuring near-optimal solution.

A novel variable neighborhood search for the offloading and resource allocation in Mobile-Edge Computing

Tests performed over generated instances of different sizes, prove the efficiency of the proposed Variable Neighborhood Search (VNS) in terms of cost and runtime, for solving the offloading problem in MEC architectures.

Energy-Efficient Resource Allocation for Application Including Dependent Tasks in Mobile Edge Computing

The proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method and obtains less energy consumption and better performance.

Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling

This paper investigates partial computation offloading by jointly optimizing the computational speed of smart mobile device (SMD), transmit power of SMD, and offloading ratio with two system design objectives: energy consumption of ECM minimization and latency of application execution minimization.

Ultra-reliable cloud mobile computing with service composition and superposition coding

This paper proposes to apply the framework of reliable service composition to the problem of optimal task offloading in MCC over fading channels, with the aim of providing layered, or composable, services at differentiated reliability levels.

Multi-Objective Decision-Making for Mobile Cloud Offloading: A Survey

Methods of multi-objective decision making for time- and energy-aware task offloading for MCC are explored to ensure the right computational tasks are executed in the right way, at the right time and place.

Computation Offloading With Data Caching Enhancement for Mobile Edge Computing

This paper proposes an optimal offloading with caching-enhancement scheme (OOCS) for femto-cloud scenario and mobile edge computing scenario, respectively, and considers the scenario where multiple mobile users offload duplicated computation tasks to the network edge, and share the computation results among them.

Optimal Offloading and Resource Allocation in Mobile-Edge Computing with Inter-User Task Dependency

It is proved that the optimal offloading decision follows an one-climb policy, based on which a reduced-complexity algorithm is proposed to obtain the optimalOffloading decision in polynomial time.
...

References

SHOWING 1-10 OF 79 REFERENCES

Computation offloading for mobile cloud computing based on wide cross-layer optimization

Theoretical results proving the existence of an optimal solution of the problem are provided and simulation results show for which classes of application and under what kind of channel conditions, computation offloading can provide a significant performance gain.

Joint allocation of computation and communication resources in multiuser mobile cloud computing

This paper proposes a method to jointly optimize the transmit power, the number of bits per symbol and the CPU cycles assigned to each application in order to minimize the power consumption at the mobile side, under an average latency constraint dictated by the application requirements.

Computation offloading strategies based on energy minimization under computational rate constraints

The aim of this paper is to propose a computation offloading strategy to be used in mobile cloud computing in order to minimize the energy expenditure at the mobile handset, while guaranteeing a

Joint multi-user resource scheduling and computation offloading in small cell networks

  • Wael LabidiM. SarkissM. Kamoun
  • Computer Science
    2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
  • 2015
This paper investigates for this problem offline and online dynamic programming approaches and devise deterministic solutions to find the optimal scheduling-offloading policy and shows that the offline strategy is optimal in terms of energy saving compared to the online strategy.

From Mobiles to Clouds: Developing Energy-Aware Offloading Strategies for Workflows

Simulation studies indicate that the offload algorithm can significantly improve the energy efficiency and execution speed of mobile workflows and how different hardware specifications can affect offload efficiency.

Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones

Numerical results illustrate that a significant amount of energy can be saved by optimally offloading the mobile application to the cloud clone, and the energy-optimal execution policy is obtained.

Energy and time optimization for wireless computation offloading

  • L. TangQianmu Li
  • Computer Science
    2015 International Conference on Wireless Communications & Signal Processing (WCSP)
  • 2015
This paper investigates the problem of energy and time optimization for wireless computation offloading under the scenario with multiple mobile device users, and derives the optimal portion of task to be offloaded for each mobile user.

A Dynamic Offloading Algorithm for Mobile Computing

A dynamic offloading algorithm based on Lyapunov optimization is presented, which has low complexity to solve the offloading problem and shows that the proposed algorithm saves more energy than the existing algorithm while meeting the requirement of application execution time.

Performance Analysis of Offloading Systems in Mobile Wireless Environments

The surrogate unreachability when mobile devices move following random waypoint (RWP) mobility scheme is investigated and the failure recovery time and total execution time of pervasive applications that run under the control of offloading systems are model.

A Framework for Partitioning and Execution of Data Stream Applications in Mobile Cloud Computing

This work studies the computation partitioning, which aims at optimizing the partition of a data stream application between mobile and cloud such that the application has maximum speed/throughput in processing the streaming data.
...