scholarly journals Environment-Sensitive Performance Tuning for Distributed Service Orchestration

2015 ◽  
pp. 209-223
Author(s):  
Yu Lin ◽  
Franjo Ivančić ◽  
Pallavi Joshi ◽  
Gogul Balakrishnan ◽  
Malay Ganai ◽  
...  
Keyword(s):  
Performance Tuning ◽  
Service Orchestration ◽  
Distributed Service

scholarly journals Distributed Service Orchestration: Eventually Consistent Cloud Operation and Integration

2016 ◽  
Author(s):  
Merlijn Sebrechts ◽  
Thomas Vanhove ◽  
Gregory Van Seghbroeck ◽  
Tim Wauters ◽  
Bruno Volckaert ◽  
...  
Keyword(s):  
Service Orchestration ◽  
Distributed Service

scholarly journals On Blockchain-Based Cross-Service Communication and Resource Orchestration on Edge Clouds

Informatics ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 13
Author(s):  
Konstantinos Papadakis-Vlachopapadopoulos ◽  
Ioannis Dimolitsas ◽  
Dimitrios Dechouniotis ◽  
Eirini Eleni Tsiropoulou ◽  
Ioanna Roussaki ◽  
...  
Keyword(s):  
Network Function Virtualization ◽  
Network Resources ◽  
Service Orchestration ◽  
Network Slicing ◽  
Network Function ◽  
Resource Orchestration ◽  
Full Capacity ◽  
Cloud Datacenter ◽  
Set Up ◽  
The Internet Of Things

With the advent of 5G verticals and the Internet of Things paradigm, Edge Computing has emerged as the most dominant service delivery architecture, placing augmented computing resources in the proximity of end users. The resource orchestration of edge clouds relies on the concept of network slicing, which provides logically isolated computing and network resources. However, though there is significant progress on the automation of the resource orchestration within a single cloud or edge cloud datacenter, the orchestration of multi-domain infrastructure or multi-administrative domain is still an open challenge. Towards exploiting the network service marketplace at its full capacity, while being aligned with ETSI Network Function Virtualization architecture, this article proposes a novel Blockchain-based service orchestrator that leverages the automation capabilities of smart contracts to establish cross-service communication between network slices of different tenants. In particular, we introduce a multi-tier architecture of a Blockchain-based network marketplace, and design the lifecycle of the cross-service orchestration. For the evaluation of the proposed approach, we set up cross-service communication in an edge cloud and we demonstrate that the orchestration overhead is less than other cross-service solutions.

Robust resource demand estimation using hierarchical Bayesian model in a distributed service system

2020 ◽  
Author(s):  
Sumanta Mukherjee ◽  
Krishnasuri Narayanam ◽  
Nupur Aggarwal ◽  
Digbalay Bose ◽  
Amith Singhee
Keyword(s):  
Bayesian Model ◽  
Service System ◽  
Demand Estimation ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Model ◽  
Resource Demand ◽  
Distributed Service

Architectural support for performance tuning

1994 ◽  
Vol 22 (2) ◽  
pp. 48-59 ◽  
Author(s):  
A. Singhal ◽  
A. J. Goldberg
Keyword(s):  
Performance Tuning ◽  
Architectural Support

scholarly journals Delay, Memory, and Messaging Tradeoffs in Distributed Service Systems

2016 ◽  
Vol 44 (1) ◽  
pp. 1-12 ◽  
Author(s):  
David Gamarnik ◽  
John N. Tsitsiklis ◽  
Martin Zubeldia
Keyword(s):  
Service Systems ◽  
Distributed Service

scholarly journals Method for Dynamic Service Orchestration in Fog Computing

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1796
Author(s):  
Nerijus Morkevicius ◽  
Algimantas Venčkauskas ◽  
Nerijus Šatkauskas ◽  
Jevgenijus Toldinas
Keyword(s):  
Fog Computing ◽  
Optimization Method ◽  
Service Orchestration ◽  
Multi Objective ◽  
System A ◽  
Service Distribution ◽  
Judgment Matrix ◽  
Hierarchy Process ◽  
Application Specific ◽  
Constrained Devices

Fog computing is meant to deal with the problems which cloud computing cannot solve alone. As the fog is closer to a user, it can improve some very important QoS characteristics, such as a latency and availability. One of the challenges in the fog architecture is heterogeneous constrained devices and the dynamic nature of the end devices, which requires a dynamic service orchestration to provide an efficient service placement inside the fog nodes. An optimization method is needed to ensure the required level of QoS while requiring minimal resources from fog and end devices, thus ensuring the longest lifecycle of the whole IoT system. A two-stage multi-objective optimization method to find the best placement of services among available fog nodes is presented in this paper. A Pareto set of non-dominated possible service distributions is found using the integer multi-objective particle swarm optimization method. Then, the analytical hierarchy process is used to choose the best service distribution according to the application-specific judgment matrix. An illustrative scenario with experimental results is presented to demonstrate characteristics of the proposed method.

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