scholarly journals Energy-Delay Tradeoff for Virtual Machine Placement in Virtualized Multi-Access Edge Computing: A Two-Sided Matching Approach

2020 ◽  
Author(s):  
Long Zhang ◽  
Shanshan Zhuge ◽  
Yao Wang ◽  
Haitao Xu ◽  
Enchang Sun
Keyword(s):  
Virtual Machines ◽  
Cost Minimization ◽  
Cost Effective ◽  
Edge Computing ◽  
Vm Placement ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Effective Manner ◽  
Multi Access

By decoupling network functions from the underlying physical machines (PMs) at the edge of the networks, the virtualized multi-access edge computing (MEC) enables deployment of new network services and elastic network scaling to reduce maintenance costs in a more flexible, scalable and cost-effective manner. Although there are appealing performance gains to be achieved, the placement of virtual machines (VMs) on top of the sharing PMs to support computation-intensive applications for the smart mobile devices becomes a major challenge, especially for an increasing network scale. In this paper, we attempt to deal with the VM placement problem in virtualized MEC system, which is targeted for finding a performance balance between energy consumption and computing/offloading delay. To capture such a tradeoff for VM placement, we formulate a weighted sum based cost minimization problem as a pure 0-1 integer linear programming problem, which is NP-complete and very complex to solve with lower complexity. Based on the one-to-one mapping relation constraint, the VM placement problem is converted into a many-to-many two-sided matching problem between the VM instances and the PMs. Motivated by the student project allocation problem, we develop an extended two-sided matching algorithm with lower computational complexity for solving the many-to-many matching problem. Simulation results are presented to demonstrate the effectiveness of our proposed matching algorithm, and the normalization factor is of great significance to obtain lower total cost.

scholarly journals Energy-Delay Tradeoff for Virtual Machine Placement in Virtualized Multi-Access Edge Computing: A Two-Sided Matching Approach

2021 ◽  
Author(s):  
Long Zhang ◽  
Shanshan Zhuge ◽  
Yao Wang ◽  
Haitao Xu ◽  
Enchang Sun
Keyword(s):  
Virtual Machines ◽  
Cost Minimization ◽  
Cost Effective ◽  
Edge Computing ◽  
Vm Placement ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Effective Manner ◽  
Multi Access

By decoupling network functions from the underlying physical machines (PMs) at the edge of the networks, the virtualized multi-access edge computing (MEC) enables deployment of new network services and elastic network scaling to reduce maintenance costs in a more flexible, scalable and cost-effective manner. Although there are appealing performance gains to be achieved, the placement of virtual machines (VMs) on top of the sharing PMs to support computation-intensive applications for the smart mobile devices becomes a major challenge, especially for an increasing network scale. In this paper, we attempt to deal with the VM placement problem in virtualized MEC system, which is targeted for finding a performance balance between energy consumption and computing/offloading delay. To capture such a tradeoff for VM placement, we formulate a weighted sum based cost minimization problem as a pure 0-1 integer linear programming problem, which is NP-complete and very complex to solve with lower complexity. Based on the one-to-one mapping relation constraint, the VM placement problem is converted into a many-to-many two-sided matching problem between the VM instances and the PMs. Motivated by the student project allocation problem, we develop an extended two-sided matching algorithm with lower computational complexity for solving the many-to-many matching problem. Simulation results are presented to demonstrate the effectiveness of our proposed matching algorithm, and the normalization factor is of great significance to obtain lower total cost.

scholarly journals Energy-Delay Tradeoff for Virtual Machine Placement in Virtualized Multi-Access Edge Computing: A Two-Sided Matching Approach

2020 ◽  
Author(s):  
Long Zhang ◽  
Shanshan Zhuge ◽  
Yao Wang ◽  
Haitao Xu ◽  
Enchang Sun
Keyword(s):  
Virtual Machines ◽  
Cost Minimization ◽  
Cost Effective ◽  
Edge Computing ◽  
Vm Placement ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Effective Manner ◽  
Multi Access

By decoupling network functions from the underlying physical machines (PMs) at the edge of the networks, the virtualized multi-access edge computing (MEC) enables deployment of new network services and elastic network scaling to reduce maintenance costs in a more flexible, scalable and cost-effective manner. Although there are appealing performance gains to be achieved, the placement of virtual machines (VMs) on top of the sharing PMs to support computation-intensive applications for the smart mobile devices becomes a major challenge, especially for an increasing network scale. In this paper, we attempt to deal with the VM placement problem in virtualized MEC system, which is targeted for finding a performance balance between energy consumption and computing/offloading delay. To capture such a tradeoff for VM placement, we formulate a weighted sum based cost minimization problem as a pure 0-1 integer linear programming problem, which is NP-complete and very complex to solve with lower complexity. Based on the one-to-one mapping relation constraint, the VM placement problem is converted into a many-to-many two-sided matching problem between the VM instances and the PMs. Motivated by the student project allocation problem, we develop an extended two-sided matching algorithm with lower computational complexity for solving the many-to-many matching problem. Simulation results are presented to demonstrate the effectiveness of our proposed matching algorithm, and the normalization factor is of great significance to obtain lower total cost.

scholarly journals Matching-based cache placement decision for 5G network caching

2021 ◽  
Author(s):  
Shadi Sadeghpour Kharkan
Keyword(s):  
Graph Matching ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Cell Network ◽  
5G Network ◽  
Backhaul Link ◽  
Random Placement ◽  
Cache Placement ◽  
Bottleneck Link

In this thesis, we present a cache placement scheme to deal with backhaul link constraint in Small Cell Network for 5G wireless network. We formulated the cache placement problem as a graph matching problem and presented an optimal file-helper matching algorithm. We defined stability criterion for the matching and found that our matching solution is stable in the sense that every helper finds at least one file to cache given that no file exceed minimum cache size. We achieved a unique placement of a file within a cluster of helpers to increase the number of files cached within a cluster. Further, our experimental evaluation demonstrates that our algorithm increases local and neighbor hit ratios as compared to a random placement, which in turn significantly decreases the traffic that goes over the backhaul bottleneck link.

Balancing Power And Performance In HPC Clouds

2020 ◽  
Vol 63 (6) ◽  
pp. 880-899
Author(s):  
Lixia Chen ◽  
Jian Li ◽  
Ruhui Ma ◽  
Haibing Guan ◽  
Hans-Arno Jacobsen
Keyword(s):  
Energy Consumption ◽  
High Performance ◽  
Virtual Machines ◽  
Support Vector ◽  
Frequency Scaling ◽  
Vm Placement ◽  
Placement Problem ◽  
Dynamic Voltage ◽  
And Performance ◽  
Save Energy

Abstract With energy consumption in high-performance computing clouds growing rapidly, energy saving has become an important topic. Virtualization provides opportunities to save energy by enabling one physical machine (PM) to host multiple virtual machines (VMs). Dynamic voltage and frequency scaling (DVFS) is another technology to reduce energy consumption. However, in heterogeneous cloud environments where DVFS may be applied at the chip level or the core level, it is a great challenge to combine these two technologies efficiently. On per-core DVFS servers, cloud managers should carefully determine VM placements to minimize performance interference. On full-chip DVFS servers, cloud managers further face the choice of whether to combine VMs with different characteristics to reduce performance interference or to combine VMs with similar characteristics to take better advantage of DVFS. This paper presents a novel mechanism combining a VM placement algorithm and a frequency scaling method. We formulate this VM placement problem as an integer programming (IP) to find appropriate placement configurations, and we utilize support vector machines to select suitable frequencies. We conduct detailed experiments and simulations, showing that our scheme effectively reduces energy consumption with modest impact on performance. Particularly, the total energy delay product is reduced by up to 60%.

scholarly journals Hardening the Security of Multi-Access Edge Computing through Bio-Inspired VM Introspection

2021 ◽  
Vol 5 (4) ◽  
pp. 52
Author(s):  
Huseyn Huseynov ◽  
Tarek Saadawi ◽  
Kenichi Kourai
Keyword(s):  
New York ◽  
Mobile Networks ◽  
Virtual Machines ◽  
Malicious Code ◽  
Edge Computing ◽  
Security And Privacy ◽  
Remote Memory ◽  
Potential Threat ◽  
Institute Of Technology ◽  
Multi Access

The extreme bandwidth and performance of 5G mobile networks changes the way we develop and utilize digital services. Within a few years, 5G will not only touch technology and applications, but dramatically change the economy, our society and individual life. One of the emerging technologies that enables the evolution to 5G by bringing cloud capabilities near to the end users is Edge Computing or also known as Multi-Access Edge Computing (MEC) that will become pertinent towards the evolution of 5G. This evolution also entails growth in the threat landscape and increase privacy in concerns at different application areas, hence security and privacy plays a central role in the evolution towards 5G. Since MEC application instantiated in the virtualized infrastructure, in this paper we present a distributed application that aims to constantly introspect multiple virtual machines (VMs) in order to detect malicious activities based on their anomalous behavior. Once suspicious processes detected, our IDS in real-time notifies system administrator about the potential threat. Developed software is able to detect keyloggers, rootkits, trojans, process hiding and other intrusion artifacts via agent-less operation, by operating remotely or directly from the host machine. Remote memory introspection means no software to install, no notice to malware to evacuate or destroy data. Experimental results of remote VMI on more than 50 different malicious code demonstrate average anomaly detection rate close to 97%. We have established wide testbed environment connecting networks of two universities Kyushu Institute of Technology and The City College of New York through secure GRE tunnel. Conducted experiments on this testbed deliver high response time of the proposed system.

Edge Computing: Continuous Surveillance and Management of Production Operations in a Cost Effective Manner

2020 ◽  
Author(s):  
Abhishek Sharma ◽  
Prince Samuel ◽  
Gian-Marcio Gey ◽  
Sujit Kumar
Keyword(s):  
Cost Effective ◽  
Edge Computing ◽  
Effective Manner

scholarly journals Matching-based cache placement decision for 5G network caching

2021 ◽  
Author(s):  
Shadi Sadeghpour Kharkan
Keyword(s):  
Graph Matching ◽  
Placement Problem ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Cell Network ◽  
5G Network ◽  
Backhaul Link ◽  
Random Placement ◽  
Cache Placement ◽  
Bottleneck Link

In this thesis, we present a cache placement scheme to deal with backhaul link constraint in Small Cell Network for 5G wireless network. We formulated the cache placement problem as a graph matching problem and presented an optimal file-helper matching algorithm. We defined stability criterion for the matching and found that our matching solution is stable in the sense that every helper finds at least one file to cache given that no file exceed minimum cache size. We achieved a unique placement of a file within a cluster of helpers to increase the number of files cached within a cluster. Further, our experimental evaluation demonstrates that our algorithm increases local and neighbor hit ratios as compared to a random placement, which in turn significantly decreases the traffic that goes over the backhaul bottleneck link.

scholarly journals A Survey on the Use of Preferences for Virtual Machine Placement in Cloud Data Centers

2021 ◽  
Vol 54 (5) ◽  
pp. 1-39
Author(s):  
Abdulaziz Alashaikh ◽  
Eisa Alanazi ◽  
Ala Al-Fuqaha
Keyword(s):  
Virtual Machine ◽  
Data Centers ◽  
Rapid Development ◽  
Cost Effective ◽  
Vm Placement ◽  
Placement Problem ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Design Factors ◽  
The Given

With the rapid development of virtualization techniques, cloud data centers allow for cost-effective, flexible, and customizable deployments of applications on virtualized infrastructure. Virtual machine (VM) placement aims to assign each virtual machine to a server in the cloud environment. VM Placement is of paramount importance to the design of cloud data centers. Typically, VM placement involves complex relations and multiple design factors as well as local policies that govern the assignment decisions. It also involves different constituents including cloud administrators and customers that might have disparate preferences while opting for a placement solution. Thus, it is often valuable to return not only an optimized solution to the VM placement problem but also a solution that reflects the given preferences of the constituents. In this article, we provide a detailed review on the role of preferences in the recent literature on VM placement. We examine different preference representations found in the literature, explain their existing usage, and explain the adopted solving approaches. We further discuss key challenges and identify possible research opportunities to better incorporate preferences within the context of VM placement.

Sign in / Sign up

Export Citation Format

Share Document