Offloading resource-intensive jobs to the cloud and nearby users is a promising approach to enhance mobile devices. This paper investigates a hybrid offloading system that takes both infrastructure-based networks and Ad-hoc networks into the scope. Specifically, we propose EDOS, an edge assisted offloading system that consists of two major components, an Edge Assistant (EA) and Offload Agent (OA). EA runs on the routers/towers to manage registered remote cloud servers and local service providers and OA operates on the users' devices to discover the services in proximity. We present the system with a suite of protocols to collect the potential service providers and algorithms to allocate tasks according to user-specified constraints. To evaluate EDOS, we prototype it on commercial mobile devices and evaluate it with both experiments on a small-scale testbed and simulations. The results show that EDOS is effective and efficient for offloading jobs.
翻译:将资源密集型工作卸载到云层和附近用户,这是加强移动设备的一个很有希望的办法。本文调查了一个混合卸载系统,该系统将基于基础设施的网络和Ad-hoc网络都纳入范围。具体地说,我们提议EDOS,这是一个由两个主要部分组成的边端辅助卸载系统,由边缘助理(EA)和卸载代理(OA)组成。EA在路由器/拖车上运行,以管理注册的远程云服务器和当地服务供应商,OA在用户的装置上运行,以发现附近的服务。我们向该系统提供一套协议,收集潜在的服务供应商和算法,以便根据用户的具体限制来分配任务。为了评价EDOS,我们将其原型放在商业移动设备上,并用小规模测试床和模拟实验来评价它。结果显示EDOS对卸载工作是有效和高效的。