Computation Resource Leasing for Priority Aggregation Local Computing Network

In large scale smart edge networks, computation resource is generally underutilized due to the uneven distribution of computation resource in time and space domain. This may correspond to a simple fact that no device is capable for 'storing' and 'exchanging' idle computation resource. Thus, this paper proposes a computation resource leasing (CRL) concept using priority as an intermediary to restore and exchange the permission for computation resource for priority aggregation local computing network (PALCN). Each device in PALNC is able to gain priority as a reward for leasing its computing resource to others. CRL also offers a priority oriented algorithm to match the computation request with idle source nodes and a priority management model. Our analysis and numerical results show that the system can efficiently utilize local idle computation sources over time and space domain and filtrate the big task that local computation can not finish.

[1]  Jae-Hyun Kim,et al.  Novel LIPA/SIPTO offloading algorithm according to the network utilization and offloading preference , 2014, 2014 International Conference on Information and Communication Technology Convergence (ICTC).

[2]  Weishan Zhang,et al.  Towards a Genetic Algorithm Based Approach for Task Migrations , 2014, 2014 International Conference on Identification, Information and Knowledge in the Internet of Things.

[3]  Jörg Henkel,et al.  Computation offloading and resource allocation for low-power IoT edge devices , 2016, 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT).

[4]  Azzedine Boukerche,et al.  A Task-Centric Mobile Cloud-Based System to Enable Energy-Aware Efficient Offloading , 2018, IEEE Transactions on Sustainable Computing.

[5]  Yongqiang Zhang,et al.  Energy-Efficient Dynamic Task Offloading for Energy Harvesting Mobile Cloud Computing , 2018, 2018 IEEE International Conference on Networking, Architecture and Storage (NAS).

[6]  Min Chen,et al.  Task Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network , 2018, IEEE Journal on Selected Areas in Communications.

[7]  Yichuan Wang,et al.  Energy Saving Strategy for Task Migration Based on Genetic Algorithm , 2018, 2018 International Conference on Networking and Network Applications (NaNA).

[8]  Xu Chen,et al.  Decentralized Computation Offloading Game for Mobile Cloud Computing , 2014, IEEE Transactions on Parallel and Distributed Systems.

[9]  Yong Wang,et al.  CPN Based Validation on Pervasive Cloud Task Migration , 2015, 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom).