English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Mobile-edge computing (MEC) is a new paradigm that provides cloud computing services at the edge of networks. To achieve better performance with limited computing resources, peer offloading between cooperative edge servers (e.g., MEC-enabled base stations) has been proposed as an effective technique to handle bursty and spatially imbalanced arrival of computation tasks. While various performance metrics of peer offloading policies have been considered in the literature, the worst case response time, a common quality of service (QoS) requirement in real-time applications, yet receives much less attention. To fill the gap, we formulate the peer offloading problem based on a stochastic arrival model and propose two online algorithms for cases with and without prior knowledge of task arrival rate. Our goal is to maximize the utility function of time-average throughput under constraints of energy consumption and worst case response time. Both theoretical analysis and numerical results show that our algorithms are able to produce close to optimal performance.

Peer Offloading in Mobile-Edge Computing With Worst Case Response Time Guarantees