DeServE: delay-agnostic service offloading in mobile edge clouds

Abstract

The mobile edge computing platform [2, 3] generally measured the delay based on the total time required to offload the services of edge devices to edge servers. On the other hand, the service delay is also depended on the response time of edge services from different mobile applications. Hence, there exists a disparity between the actual and measured service delay experienced by the mobile edge devices. This type problem arises due to the fact that the wireless radio network infrastructure is shared by the multiple mobile devices. As a result, the congestion occurs in the network and the arrival packets are likely to be dropped by the network switches in the access network. In such situation, the real-time critical edge applications mostly care about the quality-of-service (QoS) for different mobile devices, while offloading the edge services to edge servers. Thus, we improve the QoS of edge devices using delay-agnostic service offloading scheme to meet the offloading requirements of those delay-agnostic applications. Prior works have devoted to filling the gap at edge network by introducing the priority-based computational offloading [1] or energy-efficient resource allocation [4] schemes for edge computing applications. However, the priority-based service offloading and resource allocation do not provide the fair QoS to mobile devices, as the actual bottleneck is usually existed in the delay-agnostic nature of mobile applications. Therefore, although the existing offloading schemes perform well for multi-modal applications in terms of energy efficiency and computational overhead [1]. However, in those works, they assumed that the delay requirement of services to be fixed, but in real-life the delay requirement of services may vary radically. This type of situation is considered to be delay-agnostic property for edge devices, in this poster. Looking at the above points, we propose DESERVE, which introduces a delay-agnostic service offloading scheme for mobile edge computing platform in order to improve the QoS of each individual. The overview of DESERVE is depicted in Figure 1. For the edge devices, the flexible and optimal resource allocation technique is exploited for delay-agnostic service offloading scheme in edge computing platform. The resource allocation technique is leveraged for edge devices using the advanced techniques of software defined networks (SDN). However, an adaptive service identifier is deployed specifically for the identification of critical edge applications at the edge of mobile edge platform, instead of installing centralized SDN controller. After the identification of critical edge services, the identified services are forwarded to the controller and the corresponding rules to be offloaded for those services in the edge servers of edge platform.