169 research outputs found

    A game-theoretic approach to computation offloading in mobile cloud computing

    Get PDF
    We consider a three-tier architecture for mobile and pervasive computing scenarios, consisting of a local tier ofmobile nodes, a middle tier (cloudlets) of nearby computing nodes, typically located at the mobile nodes access points but characterized by a limited amount of resources, and a remote tier of distant cloud servers, which have practically infinite resources. This architecture has been proposed to get the benefits of computation offloading from mobile nodes to external servers while limiting the use of distant servers whose higher latency could negatively impact the user experience. For this architecture, we consider a usage scenario where no central authority exists and multiple non-cooperative mobile users share the limited computing resources of a close-by cloudlet and can selfishly decide to send their computations to any of the three tiers. We define a model to capture the users interaction and to investigate the effects of computation offloading on the users’ perceived performance. We formulate the problem as a generalized Nash equilibrium problem and show existence of an equilibrium.We present a distributed algorithm for the computation of an equilibrium which is tailored to the problem structure and is based on an in-depth analysis of the underlying equilibrium problem. Through numerical examples, we illustrate its behavior and the characteristics of the achieved equilibria

    Social-aware hybrid mobile offloading

    Get PDF
    Mobile offloading is a promising technique to aid the constrained resources of a mobile device. By offloading a computational task, a device can save energy and increase the performance of the mobile applications. Unfortunately, in existing offloading systems, the opportunistic moments to offload a task are often sporadic and short-lived. We overcome this problem by proposing a social-aware hybrid offloading system (HyMobi), which increases the spectrum of offloading opportunities. As a mobile device is always co- located to at least one source of network infrastructure throughout of the day, by merging cloudlet, device-to-device and remote cloud offloading, we increase the availability of offloading support. Integrating these systems is not trivial. In order to keep such coupling, a strong social catalyst is required to foster user's participation and collaboration. Thus, we equip our system with an incentive mechanism based on credit and reputation, which exploits users' social aspects to create offload communities. We evaluate our system under controlled and in-the-wild scenarios. With credit, it is possible for a device to create opportunistic moments based on user's present need. As a result, we extended the widely used opportunistic model with a long-term perspective that significantly improves the offloading process and encourages unsupervised offloading adoption in the wild

    Mobile Cloud Computing as Mobile offloading Solution: Frameworks, Focus and Implementation Challenges

    Get PDF
    Mobile devices have been operating under limited resource capacity including memory, processing speed, storage and battery life. Due to the advancement of technology, complex applications have been designed and implemented, and these application demand computing device with high capacity. Cloud computing emerged as solution for computing device with limited capacity. However, integrating mobile operating environment with cloud computing has been a challenge due to dynamicity of mobile device environment including unreliability of wireless communication. This paper reviews recent studies in Mobile Cloud Computing to assess its implementation as one of task offloading solution for mobile device. The study reviewed common framework that are used to implement Mobile Cloud Computing, the focus of the current studies and finally highlighted open issues that need to be addressed when implementing optimal Mobile Cloud Computing.Keywords: Mobile Cloud Computing, task offloading, Mobile device, cloudletDOI: 10.7176/CEIS/11-5-04Publication date:September 30th 202
    • …
    corecore