scholarly journals VNF Placement Optimization at the Edge and Cloud †

2019 ◽  
Vol 11 (3) ◽  
pp. 69 ◽  
Author(s):  
Aris Leivadeas ◽  
George Kesidis ◽  
Mohamed Ibnkahla ◽  
Ioannis Lambadaris
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Research Area ◽  
End Users ◽  
Network Function Virtualization ◽  
Future Research ◽  
Cloud Infrastructure ◽  
Network Function ◽  
Computing Paradigm ◽  
Network Functions

Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers’ goal of low deployment costs.

scholarly journals A Study on Federated Cloud Computing Environment

2021 ◽  
Vol 10 (2) ◽  
pp. 187-193
Author(s):  
Sapana Sanjay Bhuskute ◽  
◽  
Sujata Kadu ◽  
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Geographical Location ◽  
Cloud Service ◽  
Service Level ◽  
Research Area ◽  
Future Research ◽  
Cloud Environment ◽  
Computing Paradigm ◽  
Cloud Service Providers

Federated cloud computing is the advancement in the area of the general cloud computing paradigm. In a federated cloud environment, multiple cloud service providers share their computing assets, servers, and various facilities to fulfill customer demands. Federated cloud computing terminology consists of the aggregation of services considered by interoperability characteristics and creates the integration of several cloud service providers regardless of any geographical location. It improves the performance, utilization of facilities, minimizes response time and pricing model by partial subcontracting various computing resources and facilities from the nearby cost-efficient province. Customers also get profited from service level agreements signed between the cloud service providers through intermediator cloud brokers. This work aims to survey the federated cloud environment, its various architectural types, advantages associated with the federation, challenges associated with a federated cloud environment, and future research directions in the federated cloud computing research area.

Virtualization Evolution

Web Services ◽  
2019 ◽  
pp. 1762-1789
Author(s):  
Harilaos Koumaras ◽  
Christos Damaskos ◽  
George Diakoumakos ◽  
Michail-Alexandros Kourtis ◽  
George Xilouris ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Software Defined Networking ◽  
Telecommunications Industry ◽  
Network Function Virtualization ◽  
Future Perspectives ◽  
Network Function ◽  
Computing Paradigm ◽  
Cloud Networking

This chapter discusses the evolution of the cloud computing paradigm and its applicability in various sections of the computing and networking/telecommunications industry, such as the cloud networking, the cloud offloading, and the network function virtualization. The new heterogeneous virtualized ecosystem that is formulated creates new needs and challenges for management and administration at the network part. For this purpose, the approach of Software-Defined Networking is discussed and its future perspectives are further analyzed.

From Cloud Computing to Fog Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cost Savings ◽  
End Users ◽  
Internet Technology ◽  
Future Research ◽  
Computing Paradigm ◽  
Close Proximity ◽  
Iot Devices ◽  
Communication Control

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

scholarly journals Design of Security Technique through Secure Logging for Cloud Forensics

2019 ◽  
Vol 8 (6) ◽  
pp. 4035-4043
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Computer Forensics ◽  
Cloud Infrastructure ◽  
Cloud Forensics ◽  
Denial Of Service Attack ◽  
Computing Paradigm ◽  
Cloud Models

Cloud computing has a new edge computing paradigm these days. Sometimes cloud computing architectures don’t support for computer forensics investigations. Analyzing various types of logs and logging mechanism plays an important role in computer forensics. Distributed nature and the multi-tenant cloud models, where many users share the same processing and network resources, collecting, storing and analyzing logs from a cloud is very hard. User activity logs can be a valuable source of information in cloud forensic investigations. Generally, Cloud service providers have access to activity logs of cloud user and CSP can tamper the logs so that investigator cannot reach to the real culprit. In such an environment, log security is one of challenge in the cloud. Logging technique is used to monitor employee’s behavior, to keep track of malicious activities and prevent cloud networks from intrusion by well-known organizations. Ensuring the reliability and integrity of logs is crucial. Most existing solutions for secure logging are designed for traditional systems rather than the complexity of a cloud environment. In the proposed framework secure logging environment is provided by storing and processing activity logs and encrypting using advanced encryption method. It detects DDoS (distributed denial of service) attack on cloud infrastructure by using the published logs on cloud and thus helpful in cloud forensics. It is detected by the investigator using available application activity logs in the cloud server. Searchable encryption algorithm will be used to increase the security of the logging mechanism and to maintain confidentiality and privacy of user data. Proof of past (PPL) logs is created by storing logs at more than one place. This PPL helps in the verification process of changed logs by CSP the actual implementation of this application on AWS Infrastructure as a service ( IAAS ) cloud shows real-time use of this structure

scholarly journals Path Mapping Approach for Network Function Virtualization Resource Allocation with Network Function Decomposition Support

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1173 ◽  
Author(s):  
Basheer Raddwan ◽  
Khalil AL-Wagih ◽  
Ibrahim A. Al-Baltah ◽  
Mohamed A. Alrshah ◽  
Mohammed A. Al-Maqri
Keyword(s):  
Resource Allocation ◽  
Execution Time ◽  
Service Providers ◽  
Virtual Network ◽  
Network Function Virtualization ◽  
Network Function ◽  
Function Decomposition ◽  
Mapping Approach ◽  
Network Functions ◽  
The Impact

Recently, Network Function Virtualization (NFV) and Software Defined Networking (SDN) have attracted many mobile operators. For the flexible deployment of Network Functions (NFs) in an NFV environment, NF decompositions and control/user plane separation have been introduced in the literature. That is to map traditional functions into their corresponding Virtual Network Functions (VNFs). This mapping requires the NFV Resource Allocation (NFV-RA) for multi-path service graphs with a high number of virtual nodes and links, which is a complex NP-hard problem that inherited its complexity from the Virtual Network Embedding (VNE). This paper proposes a new path mapping approach to solving the NFV-RA problem for decomposed Network Service Chains (NSCs). The proposed solution has symmetrically considered optimizing an average embedding cost with an enhancement on average execution time. The proposed approach has been compared to two other existing schemes using 6 and 16 scenarios of short and long simulation runs, respectively. The impact of the number of nodes, links and paths of the service requests on the proposed scheme has been studied by solving more than 122,000 service requests. The proposed Integer Linear Programming (ILP) and heuristic schemes have reduced the execution time up to 39.58% and 6.42% compared to existing ILP and heuristic schemes, respectively. Moreover, the proposed schemes have also reduced the average embedding cost and increased the profit for the service providers.

Cloud Computing

2015 ◽  
pp. 288-302 ◽  
Author(s):  
Manzoor Ahmed Khan ◽  
Fikret Sivrikaya
Keyword(s):  
Cloud Computing ◽  
Network Function Virtualization ◽  
Mobile Cloud ◽  
End User ◽  
Content Centric Networking ◽  
Server Side ◽  
Network Function ◽  
Computing Paradigm ◽  
Network Technologies ◽  
Rapid Transformation

The growth pattern of mobile devices and wireless network technologies leads to revolutionized communication markets with constant advancements (e.g., partly realized 4G and yet-awaited 5G wireless networks, content centric networking, and mobile cloud computing). From the thin-client paradigm of the early computing history, where the bulk of the computing power was on the server side, we have witnessed a rapid transformation to powerful mobile end-user devices with ubiquitous connectivity. The cloud-computing paradigm is now promising to bridge those two ends in order to combine the best of both worlds. This chapter presents: 1) basic concepts of cloud computing in examining the different perspectives of stakeholders in the cloud market, 2) survey of existing approaches and solutions, 3) applications of cloud computing, 4) architectural approaches to cloud computing, including traditional and mobile cloud architectures, and 5) an overview of the related Software-Defined Networking and Network Function Virtualization concepts.

From Cloud Computing to Fog Computing

2021 ◽  
pp. 999-1010
Author(s):  
Sanjay P. Ahuja ◽  
Niharika Deval
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Cost Savings ◽  
End Users ◽  
Internet Technology ◽  
Future Research ◽  
Computing Paradigm ◽  
Key Characteristics ◽  
Iot Devices ◽  
Communication Control

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

Virtualization Evolution

2016 ◽  
pp. 2345-2372
Author(s):  
Harilaos Koumaras ◽  
Christos Damaskos ◽  
George Diakoumakos ◽  
Michail-Alexandros Kourtis ◽  
George Xilouris ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Software Defined Networking ◽  
Telecommunications Industry ◽  
Network Function Virtualization ◽  
Future Perspectives ◽  
Network Function ◽  
Computing Paradigm ◽  
Cloud Networking

This chapter discusses the evolution of the cloud computing paradigm and its applicability in various sections of the computing and networking/telecommunications industry, such as the cloud networking, the cloud offloading, and the network function virtualization. The new heterogeneous virtualized ecosystem that is formulated creates new needs and challenges for management and administration at the network part. For this purpose, the approach of Software-Defined Networking is discussed and its future perspectives are further analyzed.

Virtualization Evolution

2015 ◽  
pp. 279-306
Author(s):  
Harilaos Koumaras ◽  
Christos Damaskos ◽  
George Diakoumakos ◽  
Michail-Alexandros Kourtis ◽  
George Xilouris ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Software Defined Networking ◽  
Telecommunications Industry ◽  
Network Function Virtualization ◽  
Future Perspectives ◽  
Network Function ◽  
Computing Paradigm ◽  
Cloud Networking

This chapter discusses the evolution of the cloud computing paradigm and its applicability in various sections of the computing and networking/telecommunications industry, such as the cloud networking, the cloud offloading, and the network function virtualization. The new heterogeneous virtualized ecosystem that is formulated creates new needs and challenges for management and administration at the network part. For this purpose, the approach of Software-Defined Networking is discussed and its future perspectives are further analyzed.

scholarly journals The Value of Simple Heuristics for Virtualized Network Function Placement

2020 ◽  
Vol 12 (10) ◽  
pp. 161
Author(s):  
Zahra Jahedi ◽  
Thomas Kunz
Keyword(s):  
Mathematical Models ◽  
Optimization Model ◽  
Service Providers ◽  
Network Function Virtualization ◽  
Np Hard ◽  
Placement Problem ◽  
Network Function ◽  
Main Challenge ◽  
Wide Range ◽  
Network Functions

Network Function Virtualization (NFV) can lower the CAPEX and/or OPEX for service providers and allow for quick deployment of services. Along with the advantages come some challenges. The main challenge in the use of Virtualized Network Functions (VNF) is the VNFs’ placement in the network. There is a wide range of mathematical models proposed to place the Network Functions (NF) optimally. However, the critical problem of mathematical models is that they are NP-hard, and consequently not applicable to larger networks. In wireless networks, we are considering the scarcity of Bandwidth (BW) as another constraint that is due to the presence of interference. While there exist many efforts in designing a heuristic model that can provide solutions in a timely manner, the primary focus with such heuristics was almost always whether they provide results almost as good as optimal solution. Consequently, the heuristics themselves become quite non-trivial, and solving the placement problem for larger networks still takes a significant amount of time. In this paper, in contrast, we focus on designing a simple and scalable heuristic. We propose four heuristics, which are gradually becoming more complex. We compare their performance with each other, a related heuristic proposed in the literature, and a mathematical optimization model. Our results demonstrate that while more complex placement heuristics do not improve the performance of the algorithm in terms of the number of accepted placement requests, they take longer to solve and therefore are not applicable to larger networks.In contrast, a very simple heuristic can find near-optimal solutions much faster than the other more complicated heuristics while keeping the number of accepted requests close to the results achieved with an NP-hard optimization model.

Sign in / Sign up

Export Citation Format

Share Document